carla-simulator / carla-autoware Goto Github PK
View Code? Open in Web Editor NEWIntegration of AutoWare AV software with the CARLA simulator
License: MIT License
Integration of AutoWare AV software with the CARLA simulator
License: MIT License
Hello!
when I do the roslaunch $CARLA_AUTOWARE_ROOT/devel.launch,it goes wrong and the following error occurredResourceNotFound: points_preprocessor ROS path [0]=/opt/ros/kinetic/share/ros ROS path [1]=/home/wuxuyang/carla-autoware/catkin_ws/src ROS path [2]=/home/wuxuyang/catkin_ws/src ROS path [3]=/opt/ros/kinetic/share
Can someone help me?
This is in regards to the sensors.json
file (https://github.com/carla-simulator/carla-autoware/blob/master/carla-autoware-agent/agent/config/sensors.json).
What is the reasoning for choosing some of the positions as to where the different sensors are attached to the ego vehicle?
rotation_frequency
set to 20, is the expectation that Carla runs at 20 fps?Hi,
When I am trying to run the code below,
export CARLA_AUTOWARE_ROOT=~/carla-autoware/autoware_launch
export CARLA_MAPS_PATH=~/carla-autoware/autoware_data/maps
source $CARLA_AUTOWARE_ROOT/../catkin_ws/devel/setup.bash
export PYTHONPATH=$PYTHONPATH:~/carla-python/carla/dist/carla-<carla-version>-py2.7-linux-x86_64.egg:~/carla-python/carla/
roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
I got some weird error that no one seems to have had:
... logging to /home/ubuntu/.ros/log/67f78d5c-7578-11ea-a5d1-0a2a123dc1e4/roslaunch-ip-172-31-32-244-11127.log
Checking log directory for disk usage. This may take a while.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.
RLException: unused args [sensor_height] for include of [/home/ubuntu/autoware.ai/install/points_preprocessor/share/points_preprocessor/launch/ray_ground_filter.launch]
The traceback for the exception was written to the log file
I followed the exact same steps as described in the readme. I run an instance of carla in a docker container. I built autoware from source.
The only thing that may be tricky can be that I am running on a EC2 instance on AWS. However, I doubt this is likely the issue.
Thanks for any suggestions!
Hello everyone,
who encounter this problem : follow the build doc exectly, but when roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
... logging to /home/ai/.ros/log/1e2b660a-d472-11e9-bc24-b06ebfc0c66c/roslaunch-DeepLearning-29621.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.
Traceback (most recent call last):
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/init.py", line 306, in main
p.start()
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/parent.py", line 268, in start
self._start_infrastructure()
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/parent.py", line 217, in _start_infrastructure
self._load_config()
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/parent.py", line 132, in _load_config
roslaunch_strs=self.roslaunch_strs, verbose=self.verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/config.py", line 451, in load_config_default
loader.load(f, config, verbose=verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 749, in load
self._load_launch(launch, ros_config, is_core=core, filename=filename, argv=argv, verbose=verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 721, in _load_launch
self._recurse_load(ros_config, launch.childNodes, self.root_context, None, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 685, in _recurse_load
val = self._include_tag(tag, context, ros_config, default_machine, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 95, in call
return f(*args, **kwds)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 627, in _include_tag
default_machine, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 685, in _recurse_load
val = self._include_tag(tag, context, ros_config, default_machine, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 95, in call
return f(*args, **kwds)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 627, in _include_tag
default_machine, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 685, in _recurse_load
val = self._include_tag(tag, context, ros_config, default_machine, is_core, verbose)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 95, in call
return f(*args, **kwds)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 589, in _include_tag
inc_filename = self.resolve_args(tag.attributes['file'].value, context)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/xmlloader.py", line 183, in resolve_args
return substitution_args.resolve_args(args, context=context.resolve_dict, resolve_anon=self.resolve_anon)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/substitution_args.py", line 370, in resolve_args
resolved = _resolve_args(resolved, context, resolve_anon, commands)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/substitution_args.py", line 383, in _resolve_args
resolved = commands[command](resolved, a, args, context)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/substitution_args.py", line 151, in _find
source_path_to_packages=source_path_to_packages)
File "/opt/ros/kinetic/lib/python2.7/dist-packages/roslaunch/substitution_args.py", line 197, in _find_executable
full_path = _get_executable_path(rp.get_path(args[0]), path)
File "/usr/lib/python2.7/dist-packages/rospkg/rospack.py", line 203, in get_path
raise ResourceNotFound(name, ros_paths=self._ros_paths)
ResourceNotFound: waypoint_follower
ROS path [0]=/opt/ros/kinetic/share/ros
ROS path [1]=/home/ai/carla-autoware/catkin_ws/src
ROS path [2]=/home/ai/autoware.ai/install/ymc/share
ROS path [3]=/home/ai/autoware.ai/install/xsens_driver/share
ROS path [4]=/home/ai/autoware.ai/install/wf_simulator/share
ROS path [5]=/home/ai/autoware.ai/install/lattice_planner/share
ROS path [6]=/home/ai/autoware.ai/install/waypoint_planner/share
ROS path [7]=/home/ai/autoware.ai/install/waypoint_maker/share
ROS path [8]=/home/ai/autoware.ai/install/way_planner/share
ROS path [9]=/home/ai/autoware.ai/install/vlg22c_cam/share
ROS path [10]=/home/ai/autoware.ai/install/vision_ssd_detect/share
ROS path [11]=/home/ai/autoware.ai/install/vision_segment_enet_detect/share
ROS path [12]=/home/ai/autoware.ai/install/vision_lane_detect/share
ROS path [13]=/home/ai/autoware.ai/install/vision_darknet_detect/share
ROS path [14]=/home/ai/autoware.ai/install/vision_beyond_track/share
ROS path [15]=/home/ai/autoware.ai/install/vehicle_socket/share
ROS path [16]=/home/ai/autoware.ai/install/vehicle_model/share
ROS path [17]=/home/ai/autoware.ai/install/vehicle_gazebo_simulation_launcher/share
ROS path [18]=/home/ai/autoware.ai/install/vehicle_gazebo_simulation_interface/share
ROS path [19]=/home/ai/autoware.ai/install/vehicle_engage_panel/share
ROS path [20]=/home/ai/autoware.ai/install/vehicle_description/share
ROS path [21]=/home/ai/autoware.ai/install/trafficlight_recognizer/share
ROS path [22]=/home/ai/autoware.ai/install/op_utilities/share
ROS path [23]=/home/ai/autoware.ai/install/op_simulation_package/share
ROS path [24]=/home/ai/autoware.ai/install/op_local_planner/share
ROS path [25]=/home/ai/autoware.ai/install/op_global_planner/share
ROS path [26]=/home/ai/autoware.ai/install/lidar_kf_contour_track/share
ROS path [27]=/home/ai/autoware.ai/install/op_ros_helpers/share
ROS path [28]=/home/ai/autoware.ai/install/ff_waypoint_follower/share
ROS path [29]=/home/ai/autoware.ai/install/dp_planner/share
ROS path [30]=/home/ai/autoware.ai/install/op_simu/share
ROS path [31]=/home/ai/autoware.ai/install/op_planner/share
ROS path [32]=/home/ai/autoware.ai/install/op_utility/share
ROS path [33]=/home/ai/autoware.ai/install/lidar_euclidean_cluster_detect/share
ROS path [34]=/home/ai/autoware.ai/install/vector_map_server/share
ROS path [35]=/home/ai/autoware.ai/install/road_occupancy_processor/share
ROS path [36]=/home/ai/autoware.ai/install/costmap_generator/share
ROS path [37]=/home/ai/autoware.ai/install/object_map/share
ROS path [38]=/home/ai/autoware.ai/install/naive_motion_predict/share
ROS path [39]=/home/ai/autoware.ai/install/map_file/share
ROS path [40]=/home/ai/autoware.ai/install/libvectormap/share
ROS path [41]=/home/ai/autoware.ai/install/lane_planner/share
ROS path [42]=/home/ai/autoware.ai/install/imm_ukf_pda_track/share
ROS path [43]=/home/ai/autoware.ai/install/decision_maker/share
ROS path [44]=/home/ai/autoware.ai/install/vector_map/share
ROS path [45]=/home/ai/autoware.ai/install/vectacam/share
ROS path [46]=/home/ai/autoware.ai/install/udon_socket/share
ROS path [47]=/home/ai/autoware.ai/install/twist_generator/share
ROS path [48]=/home/ai/autoware.ai/install/twist_gate/share
ROS path [49]=/home/ai/autoware.ai/install/twist_filter/share
ROS path [50]=/home/ai/autoware.ai/install/tablet_socket/share
ROS path [51]=/home/ai/autoware.ai/install/state_machine_lib/share
ROS path [52]=/home/ai/autoware.ai/install/sound_player/share
ROS path [53]=/home/ai/autoware.ai/install/sick_lms5xx/share
ROS path [54]=/home/ai/autoware.ai/install/sick_ldmrs_tools/share
ROS path [55]=/home/ai/autoware.ai/install/sick_ldmrs_driver/share
ROS path [56]=/home/ai/autoware.ai/install/sick_ldmrs_msgs/share
ROS path [57]=/home/ai/autoware.ai/install/sick_ldmrs_description/share
ROS path [58]=/home/ai/autoware.ai/install/runtime_manager/share
ROS path [59]=/home/ai/autoware.ai/install/points2image/share
ROS path [60]=/home/ai/autoware.ai/install/rosinterface/share
ROS path [61]=/home/ai/autoware.ai/install/rosbag_controller/share
ROS path [62]=/home/ai/autoware.ai/install/roi_object_filter/share
ROS path [63]=/home/ai/autoware.ai/install/range_vision_fusion/share
ROS path [64]=/home/ai/autoware.ai/install/mpc_follower/share
ROS path [65]=/home/ai/autoware.ai/install/qpoases_vendor/share
ROS path [66]=/home/ai/autoware.ai/install/pure_pursuit/share
ROS path [67]=/home/ai/autoware.ai/install/pos_db/share
ROS path [68]=/home/ai/autoware.ai/install/points_preprocessor/share
ROS path [69]=/home/ai/autoware.ai/install/points_downsampler/share
ROS path [70]=/home/ai/autoware.ai/install/pixel_cloud_fusion/share
ROS path [71]=/home/ai/autoware.ai/install/lidar_localizer/share
ROS path [72]=/home/ai/autoware.ai/install/pcl_omp_registration/share
ROS path [73]=/home/ai/autoware.ai/install/pc2_downsampler/share
ROS path [74]=/home/ai/autoware.ai/install/oculus_socket/share
ROS path [75]=/home/ai/autoware.ai/install/obj_db/share
ROS path [76]=/home/ai/autoware.ai/install/nmea_navsat/share
ROS path [77]=/home/ai/autoware.ai/install/ndt_tku/share
ROS path [78]=/home/ai/autoware.ai/install/ndt_gpu/share
ROS path [79]=/home/ai/autoware.ai/install/ndt_cpu/share
ROS path [80]=/home/ai/autoware.ai/install/multi_lidar_calibrator/share
ROS path [81]=/home/ai/autoware.ai/install/mrt_cmake_modules/share
ROS path [82]=/home/ai/autoware.ai/install/mqtt_socket/share
ROS path [83]=/home/ai/autoware.ai/install/microstrain_driver/share
ROS path [84]=/home/ai/autoware.ai/install/memsic_imu/share
ROS path [85]=/home/ai/autoware.ai/install/marker_downsampler/share
ROS path [86]=/home/ai/autoware.ai/install/map_tools/share
ROS path [87]=/home/ai/autoware.ai/install/map_tf_generator/share
ROS path [88]=/home/ai/autoware.ai/install/log_tools/share
ROS path [89]=/home/ai/autoware.ai/install/lidar_shape_estimation/share
ROS path [90]=/home/ai/autoware.ai/install/lidar_point_pillars/share
ROS path [91]=/home/ai/autoware.ai/install/lidar_naive_l_shape_detect/share
ROS path [92]=/home/ai/autoware.ai/install/lidar_fake_perception/share
ROS path [93]=/home/ai/autoware.ai/install/lidar_apollo_cnn_seg_detect/share
ROS path [94]=/home/ai/autoware.ai/install/libwaypoint_follower/share
ROS path [95]=/home/ai/autoware.ai/install/lgsvl_simulator_bridge/share
ROS path [96]=/home/ai/autoware.ai/install/lanelet2_validation/share
ROS path [97]=/home/ai/autoware.ai/install/lanelet2_examples/share
ROS path [98]=/home/ai/autoware.ai/install/lanelet2_python/share
ROS path [99]=/home/ai/autoware.ai/install/lanelet2_routing/share
ROS path [100]=/home/ai/autoware.ai/install/lanelet2_traffic_rules/share
ROS path [101]=/home/ai/autoware.ai/install/lanelet2_projection/share
ROS path [102]=/home/ai/autoware.ai/install/lanelet2_maps/share
ROS path [103]=/home/ai/autoware.ai/install/lanelet2_io/share
ROS path [104]=/home/ai/autoware.ai/install/lanelet2_core/share
ROS path [105]=/home/ai/autoware.ai/install/kvaser/share
ROS path [106]=/home/ai/autoware.ai/install/kitti_launch/share
THX, anyway
I built the carla-autoware-bridge as described in the install notes.
When executing
roslaunch carla_autoware_bridge carla_autoware_bridge.launch
the vehiclecmd_to_ackermanndrive node is dying with the following error message:
Traceback (most recent call last): File "/home/reich/carla-autoware/catkin_ws/src/carla_autoware_bridge/src/vehiclecmd_to_ackermanndrive", line 4, in <module> from ackermann_msgs.msg import AckermannDrive ImportError: No module named ackermann_msgs.msg [vehiclecmd_to_ackermanndrive-6] process has died [pid 30370, exit code 1, cmd /home/reich/carla-autoware/catkin_ws/src/carla_autoware_bridge/src/vehiclecmd_to_ackermanndrive __name:=vehiclecmd_to_ackermanndrive __log:=/home/reich/.ros/log/ed39ca24-2679-11e9-8cb1-485b3976f12a/vehiclecmd_to_ackermanndrive-6.log]. log file: /home/reich/.ros/log/ed39ca24-2679-11e9-8cb1-485b3976f12a/vehiclecmd_to_ackermanndrive-6*.log
As the normal ros-bridge is already dependent on the AckermannDrive message, I wonder, where this message is defined as I didn't find any .msg file for it.
Could someone help me in this regard?
Is there a documentation or tutorial on how to run Carla scenarios with carla-autoware ?
when I do roslaunch carla_autoware_agent carla_autoware_agent.launch town:=Town01 host:=10.3.147.140
, it goes wrong and [carla_ego_vehicle_ego_vehicle-4] process has died [pid 13695, exit code 1, cmd /home/autoware/carla_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py __name:=carla_ego_vehicle_ego_vehicle __log:=/home/autoware/.ros/log/3b70b1fe-0c41-11eb-9010-ac1f6b8091ec/carla_ego_vehicle_ego_vehicle-4.log]. log file: /home/autoware/.ros/log/3b70b1fe-0c41-11eb-9010-ac1f6b8091ec/carla_ego_vehicle_ego_vehicle-4*.log
occured. Only map changed in the carla, there isn't a car generated in the road.
I want to get some suggestions to fix this.
When I used the carla_autoware_bridge_with_manual_control.launch for other towns, the GNSS in pygame window always showed zeros for the car location.
Does it have the GNSS information for carla autoware bridge?
Thanks.
i want to add renault twizzy vehicle model with all actual physics data, but using the usual unreal engine and the 4 wheel shell the physics are not specific to what i actually want
I am getting the following error message:
pathspec 'joel-mb/timeout' did not match any files(s) known to git
On deeper inspection, I believe the code is trying to checkout `joel-mb/timeout' but that branch does not exist.
Should I checkout a stable branch/tag from 'carla-autoware' ? If yes, which one is the stable branch/tag?
Hello,
I am looking for simple guide to use Autoware in the Challenge.
My problems are:
Thanks.
According to this Video: https://www.youtube.com/watch?v=Z7PLkcY9Mtk it is possible to run Openplanner with Carla. After the debugging the GUI of Autoware 12, because I use Ubuntu 18, I tried to launch files according the slides p 34 https://drive.google.com/file/d/1tTBMXOifFdjpgMEmM9Qjn7lO0nYpPs3A/view.
Did someone manage to run this? In the video, the author used an older OpenPlanner version, which I can not use because of Ubuntu 18.
--> https://answers.ros.org/question/345529/how-to-start-op-local-planner-in-carla/
In Autoware, range_fusion package will be removed in the future.(autowarefoundation/autoware#1884)
Hello!
After build the image with the following command:
cd carla-autoware && ./build.sh
I got
REPOSITORY TAG IMAGE ID CREATED SIZE
carla-autoware latest 609bb5968338 13 hours ago 11GB
But Whether I run. /run.sh or sudo docker run -it carla -autoware:latest /bin/bash I get a prompt that
chroot: cannot change root Directory to '/': Operation not permitted
How can I fix this bug?Thanks!
File "/home/autoware/carla_ws/src/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/bridge.py", line 24, in
import carla
File "build/bdist.linux-x86_64/egg/carla/init.py", line 8, in
File "build/bdist.linux-x86_64/egg/carla/libcarla.py", line 7, in
File "build/bdist.linux-x86_64/egg/carla/libcarla.py", line 6, in bootstrap
ImportError: libxerces-c-3.1.so: cannot open shared object file: No such file or directory
Hi I have been installing dockers for both Carla 0.9.10.1 and carla-autoware in this repo, and running them in parallel.
Previously I could see the map and access the topics for the ego using rviz after roslaunch carla_autoware_agent carla_autoware_agent.launch town:=Town01
, problem I encountered earlier is it "Failed transform from base_link to ego_vehicle/lidar/lidar1", and the ego vehicle nevers moved.
However I build the carla-autoware image again yesterday, and I got 'Sensor will not be spawned', 'Inbound TXP/IP connection failed' and 'necessary topic are not subscribed' error, in rviz there is no map showing and many of the topics for the ego are missing, please see screenshots below. Could anyone please guide me on how to properly build the carla-autoware image, and how to run carla 0.9.10.1 docker with this carla-autoware? thanks
Hello,
we have created a custom Map for Carla, which works just fine. Now we want to use autoware to drive our vehicle in the town.
I was already able to create a point cloud of the Town using the pcl_recorder.
We now want autoware to calculate its own path. For this, autoware requires a vector map of the town afaik
Until now I was not able to find a way to convert our town into the proper format needed by autoware.
So how do I create a vector map of our carla map for autoware, or how was it done with the already provided ones.
Much thanks in advance!
Hi,
The agent just doesn't work after a couple of turns, it happens every time I run autoware
https://drive.google.com/file/d/17421n3pFJwFab53uSruxy9wzysnjIik1/view?usp=sharing
Did anyone else have this issue happen to him?
Hi,
I experienced very slow performance after running 1) the carla docker, and 2) the carla-autoware docker (built following this instruction https://github.com/carla-simulator/carla-autoware/tree/master/docker), and 3) python API.
following are my current running procedure
carla
nvidia-docker run -p 2000-2001:2000-2001 -it --rm carlasim/carla:0.9.6 ./CarlaUE4.sh
carla-autoware
./run.sh
export CARLA_AUTOWARE_ROOT=~/carla-autoware/autoware_launch
export CARLA_MAPS_PATH=~/carla-autoware/autoware_data/maps
source $CARLA_AUTOWARE_ROOT/../catkin_ws/devel/setup.bash
export PYTHONPATH=$PYTHONPATH:~/carla-python/carla/dist/carla-<carla-version>-py2.7-linux-x86_64.egg:~/carla-python/carla/
roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
rviz via autoware runtime manager
./run.sh
cd Autoware/install
source setup.bash
Autoware$ roslaunch runtime_manager runtime_manager.launch
run customised python API through Pycharm
the resulted frame rates are very low, and I feel the communication might not be synchronised. Anyone experiences the same? any ideas on how to increase the performance? I notice on the carla ros manual control the FPS is constantly at 20. Thanks
Hi all,
I am running the carla-autoware bridge with CARLA 0.9.5 and autoware 1.12.0. The setup works and the agent follows the waypoint published, but it does not avoid obstacles on its route.
I am running autoware with lidar_euclidean_clustering, naive_motion_planning and costmap_generator for detection and astar_avoid, velocity_set and pure_pursuit for motion planning.
I expected the agent to detect the obstacles and calculate local waypoints accordingly to avoid a collision. Instead the agent sticks to its initial route even though the obstacles are detected by the lidar detector.
Can somebody help me with this issue?
Hi,
Thank you for your great work. I'm trying to run ndt_matching with the vehicle moving in Town03 and ndt_matching doesn't work as expected as the transformation between /world
frame to /map
isn't specified correctly.
So my question here is how to get the correct values for the transformation between /world
frame to /map
frame in terms of x, y, z, roll, pitch, and yaw?
Thanks in advance,
Hello!
I was trying to build Carla Autoware Bridge as Docs said,But when I do the step Run,I found that I don't have the corresponding file autoware-contents as it said in step Run line 2,dose anybody knows?
#Terminal 2
export CARLA_AUTOWARE_ROOT=/carla-autoware/autoware_launch/autoware-contents/maps
export CARLA_MAPS_PATH=
source /ros/install/setup.bash
source $CARLA_AUTOWARE_ROOT/../catkin_ws/devel/setup.bash
export PYTHONPATH=$PYTHONPATH:/carla-python/carla/dist/carla--py2.7-linux-x86_64.egg:/carla-python/carla/
roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
I have installed newest version of carla and carla autoware docker and now i want to set carla autoware waypoint setting in the rviz
Any ideas how to set that.
Hi.
I am Masaya Kataoka and I am a Autoware developer.
I want to integrate carla with Autoware, in order to improve userbility, we propose to rename this repo to the carla_ros and release these packages as a ros package.
It seems that in some town(for example town4), autopilot can't traverse the map quickly, so I tried to do creation with manual driving, for example, change the option in line 3 in carla_autoware_bridge_capture_pcl_map.launch to do manual driving with mapping,
The reaction in pygame is quite slow in this case, is that because of my hardware to slow?
e.g. recent intel processors and nvidia card, fps in server = 10, and client fps >>10,
Hi all,
I am running the carla-autoware demo using carla version 0.9.5, autoware version 1.11.0
I have started the carla server and autoware successfully and the manual control works fine in carla and visualization in Rviz is also fine. However, when I tried to set start/end of route, the problem showed up.
Here is what I have done:
Best
I am following the steps in this presentation. I was wondering where I can find rviz_op_config.rviz.
Hi,
I followed the setup and run the agent instructions of the branch joel-mb/package_0_9_10
and modified run.sh
as discussed in #92 .
Everything seems fine until when the rviz window pops up. A screenshot is shown below:
The only error message that ever appeared in the docker window is:
[ERROR] [1599623780.456602301, 52.439418315]: Failed transform from base_link to ego_vehicle/lidar/lidar1
Could you give me some hints on what goes wrong here?
autoware@adl-Nuvo-5000:~$ roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
... logging to /home/autoware/.ros/log/a200d16a-7d7c-11e9-a0c4-78d004236ed8/roslaunch-adl-Nuvo-5000-24380.log
Checking log directory for disk usage. This may take awhile.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.
while processing /home/autoware/carla-autoware/autoware_launch/autoware.launch:
while processing /home/autoware/carla-autoware/autoware_launch/my_localization.launch:
while processing /home/autoware/Autoware/ros/install/points_downsampler/share/points_downsampler/launch/points_downsample.launch:
Invalid roslaunch XML syntax: [Errno 2] No such file or directory: u'/home/autoware/Autoware/ros/install/points_downsampler/share/points_downsampler/launch/points_downsample.launch'
The traceback for the exception was written to the log file
That's excellent!
I want to officially incorporate into autoware.
If you do not mind, we will cooperate as well.
Hi, My name is masaya Kataoka and I am Autoware Developer.
I removed model publisher package from Autoware and add vehicle_description package instead last month.
(autowarefoundation/autoware#1848)
Hi @fabianoboril @fpasch,
the bridge is almost working with the carla 0.9.7.4 (https://github.com/carla-simulator/carla/releases). But the autonomous vehicle loses the localization all the time. I also had this problem with 0.9.6 when I had the wrong HD Maps. When I downloaded it here https://bitbucket.org/carla-simulator/autoware-contents/src/master/maps/ for 0.9.6 it works fine.
Even when I use these HD Maps it does not work out for 0.9.7. Then, I tried to use the HD maps from the precompiled version (~/CARLA_0.9.7.4/HDMaps), which did not succeed.
Are there other HD maps somewhere? Could be somewhere else the error, why it is not working?
My setup:
Carla
#download docker image (e.g. version 0.9.6)
docker pull carlasim/carla:0.9.6
#extract the Carla Python API from the image
cd ~
mkdir carla-python
docker run --rm --entrypoint tar carlasim/carla:0.9.6 cC /home/carla/PythonAPI . | tar xvC ~/carla-python
Carla Autoware Bridge
cd ~
git lfs clone https://github.com/carla-simulator/carla-autoware.git
cd carla-autoware
git submodule update --init
cd docker
./build.sh
Run
Terminal 1:
nvidia-docker run -p 2000-2001:2000-2001 -it --rm carlasim/carla:0.9.6 ./CarlaUE4.sh
Terminal 2:
<in docker directory> ./run.sh
autoware@lh:~/Autoware$ roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
Terminal 3:
<in docker directory> ./run.sh
rviz
https://gitlab.com/autowarefoundation/autoware.ai/autoware/-/wikis/ROSBAG-Demo
Launch RViz through the RViz button in the bottom-right corner of the ARM and load the default.rviz config provided with Autoware. To do this got to File -> Open Config and navigate to autoware.ai/src/autoware/documentation/autoware_quickstart_examples/launch/rosbag_demo/default.rviz
When I start, roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
, I get the following error:
terminate called after throwing an instance of 'std::runtime_error'
what(): Time is out of dual 32-bit range
Failed to find match for field 'intensity'.
Failed to find match for field 'intensity'.
[ndt_matching-26] process has died [pid 5809, exit code -6, cmd /home/autoware/Autoware/install/lidar_localizer/lib/lidar_localizer/ndt_matching __name:=ndt_matching __log:=/home/autoware/.ros/log/0b4e2286-5175-11ea-a5ab-00d861527c29/ndt_matching-26.log].
log file: /home/autoware/.ros/log/0b4e2286-5175-11ea-a5ab-00d861527c29/ndt_matching-26*.log
Failed to find match for field 'intensity'.
Failed to find match for field 'intensity'.
BTW:
sudo apt install ros-kinetic-desktop-full
in the autoware docker fixed the joint_state_publisher error
Hi,
I am using Carla 0.9.9 with Autoware 1.14.
I am able to get everything setup and arrive at this screen
However, my vehicle does not move no matter I used the carla's ROS node for publishing waypoint or I used the tool on RVIS.
My vehicle does move in manual control mode.
After looking into the issue, I found that I am missing the waypoint_follower node that is specified in the launch file.
I went to the Autoware Gitlab and searched for it, it seems like that file is only in 1.12.
Can the maintainer make sure that this file can be in the newer versions of autoware or the launch file correspond to the correct version of autoware?
It seems that Carla 0.9.4 only generate 3D points without intensity, is there any plan to have point could points in the form of [x, y, z, intensity]? In real world application, e.g. localization, intensity is quite an important field, thank you!
Right now I am able to get the car moving by setting 2d nav goal
in rviz. But it seems that I cannot set new destinations for the car, even when it's reached the current destination. Are there any suggestions for this?
Hello,
I've set up the project according to the instructions in the README. However I've not been able to find a launch script which creates an rviz node with the correct configuration. I tried launching 'carla ros bridge with rviz' from within the carla autoware but rviz doesn't show any data.
Can I get a guideline on how to setup rviz with this project?
Thanks,
Ishaan
I have installed carla autoware agent docker version im able to navigate and drive the car around the map provided and publishing waypoints. However i would like to create, generate my own waypoint coordinate those coordiante can be csv or xml how can i upload them into my map.
Hi guys!
I've created my own map and ran it successfully in Carla, now I'd like to run it in Autoware.
So does anyone know how to convert it like the ones provided with this repo?
I start the simulator on my host machine by this command
./CarlaUE4.sh -windowed -ResX=800 -ResY=600 -carla-server
after the simulator is up, I fire the launch file from the docker container by
roslaunch carla_autoware_agent carla_autoware_agent.launch town:=Town01
the simulator crashes. this is the full log of Carla
4.24.3-0+++UE4+Release-4.24 518 0
Disabling core dumps.
LowLevelFatalError [File:Unknown] [Line: 3762]
Failed to link program [Program V_3AA5F7CCAD2B351344BE53DDA22E8BAEBA78720A_P_ABADFE631118A2CF0719C49D3F936DABF0CE8865]. Current total programs: 281, precompile: 0
Signal 11 caught.
Malloc Size=65538 LargeMemoryPoolOffset=65554
CommonUnixCrashHandler: Signal=11
Malloc Size=65535 LargeMemoryPoolOffset=131119
Malloc Size=128368 LargeMemoryPoolOffset=259504
Engine crash handling finished; re-raising signal 11 for the default handler. Good bye.
and this is the full log of the roslaunch
... logging to /home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/roslaunch-bignrz-Lenovo-ideapad-520-15IKB-822.log
Checking log directory for disk usage. This may take a while.
Press Ctrl-C to interrupt
Done checking log file disk usage. Usage is <1GB.
started roslaunch server http://bignrz-Lenovo-ideapad-520-15IKB:36051/
SUMMARY
========
PARAMETERS
* /astar_avoid/angle_goal_range: 6.0
* /astar_avoid/avoid_start_velocity: 3.0
* /astar_avoid/avoid_waypoints_velocity: 10.0
* /astar_avoid/closest_search_size: 30
* /astar_avoid/curve_weight: 1.2
* /astar_avoid/distance_heuristic_weight: 1.0
* /astar_avoid/enable_avoidance: False
* /astar_avoid/lateral_goal_range: 0.5
* /astar_avoid/longitudinal_goal_range: 2.0
* /astar_avoid/minimum_turning_radius: 6.0
* /astar_avoid/obstacle_threshold: 100
* /astar_avoid/potential_weight: 10.0
* /astar_avoid/replan_interval: 2.0
* /astar_avoid/reverse_weight: 2.0
* /astar_avoid/robot_base2back: 1.0
* /astar_avoid/robot_length: 4.5
* /astar_avoid/robot_width: 1.75
* /astar_avoid/safety_waypoints_size: 100
* /astar_avoid/search_waypoints_delta: 2
* /astar_avoid/search_waypoints_size: 50
* /astar_avoid/theta_size: 48
* /astar_avoid/time_limit: 1000.0
* /astar_avoid/update_rate: 10
* /astar_avoid/use_back: False
* /astar_avoid/use_potential_heuristic: True
* /astar_avoid/use_wavefront_heuristic: False
* /carla/ackermann_control/accel_Kd: 0.05
* /carla/ackermann_control/accel_Ki: 0.0
* /carla/ackermann_control/accel_Kp: 0.05
* /carla/ackermann_control/min_accel: 1.0
* /carla/ackermann_control/speed_Kd: 0.5
* /carla/ackermann_control/speed_Ki: 0.0
* /carla/ackermann_control/speed_Kp: 0.05
* /carla/ego_vehicle/role_name: ['hero', 'ego_veh...
* /carla/fixed_delta_seconds: 0.05
* /carla/host: localhost
* /carla/port: 2000
* /carla/synchronous_mode: False
* /carla/synchronous_mode_wait_for_vehicle_control_command: True
* /carla/timeout: 10
* /carla/town: Town01
* /carla_ackermann_control_ego_vehicle/role_name: ego_vehicle
* /carla_ego_vehicle_ego_vehicle/role_name: ego_vehicle
* /carla_ego_vehicle_ego_vehicle/sensor_definition_file: /home/autoware/ca...
* /carla_ego_vehicle_ego_vehicle/spawn_ego_vehicle: True
* /carla_ego_vehicle_ego_vehicle/spawn_point:
* /carla_ego_vehicle_ego_vehicle/vehicle_filter: vehicle.toyota.prius
* /costmap_generator/expand_polygon_size: 1.0
* /costmap_generator/grid_length_x: 50
* /costmap_generator/grid_length_y: 30
* /costmap_generator/grid_max_value: 1.0
* /costmap_generator/grid_min_value: 0.0
* /costmap_generator/grid_position_x: 20
* /costmap_generator/grid_position_y: 0
* /costmap_generator/grid_resolution: 0.2
* /costmap_generator/lidar_frame: velodyne
* /costmap_generator/map_frame: map
* /costmap_generator/maximum_lidar_height_thres: 0.3
* /costmap_generator/minimum_lidar_height_thres: -2.2
* /costmap_generator/size_of_expansion_kernel: 9
* /costmap_generator/use_objects_box: True
* /costmap_generator/use_objects_convex_hull: False
* /costmap_generator/use_points: True
* /costmap_generator/use_wayarea: True
* /decision_maker/auto_engage: True
* /decision_maker/auto_mission_change: False
* /decision_maker/auto_mission_reload: False
* /decision_maker/change_threshold_angle: 15
* /decision_maker/change_threshold_dist: 1.0
* /decision_maker/disuse_vector_map: True
* /decision_maker/goal_threshold_dist: 3.0
* /decision_maker/goal_threshold_vel: 0.1
* /decision_maker/insert_stop_line_wp: True
* /decision_maker/param_num_of_steer_behind: 30
* /decision_maker/sim_mode: False
* /decision_maker/state_behavior_file_name: /home/autoware/Au...
* /decision_maker/state_mission_file_name: /home/autoware/Au...
* /decision_maker/state_motion_file_name: /home/autoware/Au...
* /decision_maker/state_vehicle_file_name: /home/autoware/Au...
* /decision_maker/stop_sign_id: stop_sign
* /decision_maker/stopline_reset_count: 20
* /decision_maker/stopped_vel: 0.1
* /decision_maker/use_fms: False
* /decision_maker/use_ll2: False
* /detection/fusion_tools/range_fusion_visualization_01/objects_src_topic: /objects
* /detection/lidar_detector/cluster_detect_visualization_01/objects_src_topic: /objects_filtered
* /detection/lidar_detector/object_roi_filter_clustering/exception_list: [person, bicycle]
* /detection/lidar_detector/object_roi_filter_clustering/objects_src_topic: /objects
* /detection/lidar_detector/object_roi_filter_clustering/sync_topics: False
* /detection/lidar_detector/object_roi_filter_clustering/wayarea_gridmap_layer: wayarea
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/accel_Kd: 0.05
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/accel_Ki: 0.0
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/accel_Kp: 0.03
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/speed_Kd: 0.4
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/speed_Ki: 0.0
* /dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175/speed_Kp: 0.15
* /image_tracker_rects/image_out: /image_tracker_rects
* /image_tracker_rects/image_src: /image_raw
* /image_tracker_rects/object_src: /detection/image_...
* /imm_ukf_pda_01/detection_probability: 0.9
* /imm_ukf_pda_01/gate_probability: 0.99
* /imm_ukf_pda_01/gating_threshold: 9.22
* /imm_ukf_pda_01/lane_direction_chi_threshold: 2.71
* /imm_ukf_pda_01/life_time_threshold: 8
* /imm_ukf_pda_01/merge_distance_threshold: 0.5
* /imm_ukf_pda_01/nearest_lane_distance_threshold: 1.0
* /imm_ukf_pda_01/prevent_explosion_threshold: 1000
* /imm_ukf_pda_01/static_num_history_threshold: 3
* /imm_ukf_pda_01/static_velocity_threshold: 0.5
* /imm_ukf_pda_01/tracking_frame: /world
* /imm_ukf_pda_01/use_sukf: False
* /imm_ukf_pda_01/use_vectormap: False
* /imm_ukf_pda_01/vectormap_frame: /map
* /lidar_euclidean_cluster_detect/clip_max_height: 2.5
* /lidar_euclidean_cluster_detect/clip_min_height: -2.5
* /lidar_euclidean_cluster_detect/cluster_merge_threshold: 1.5
* /lidar_euclidean_cluster_detect/cluster_size_max: 100000
* /lidar_euclidean_cluster_detect/cluster_size_min: 20
* /lidar_euclidean_cluster_detect/clustering_distance: 0.75
* /lidar_euclidean_cluster_detect/clustering_distances: [0.5,1.1,1.6,2.1,...
* /lidar_euclidean_cluster_detect/clustering_ranges: [15,30,45,60]
* /lidar_euclidean_cluster_detect/downsample_cloud: False
* /lidar_euclidean_cluster_detect/keep_lane_left_distance: 5
* /lidar_euclidean_cluster_detect/keep_lane_right_distance: 5
* /lidar_euclidean_cluster_detect/keep_lanes: False
* /lidar_euclidean_cluster_detect/leaf_size: 0.1
* /lidar_euclidean_cluster_detect/output_frame: velodyne
* /lidar_euclidean_cluster_detect/points_node: /points_no_ground
* /lidar_euclidean_cluster_detect/pose_estimation: True
* /lidar_euclidean_cluster_detect/remove_ground: False
* /lidar_euclidean_cluster_detect/remove_points_upto: 0.0
* /lidar_euclidean_cluster_detect/use_diffnormals: False
* /lidar_euclidean_cluster_detect/use_gpu: True
* /lidar_euclidean_cluster_detect/use_multiple_thres: False
* /lidar_naive_l_shape_detect/num_points_thres: 10
* /lidar_naive_l_shape_detect/random_ponts: 160
* /lidar_naive_l_shape_detect/sensor_height: 2.4
* /lidar_naive_l_shape_detect/slope_dist_thres: 2.0
* /localizer: velodyne
* /naive_motion_predict/filter_out_close_object_threshold: 1.5
* /naive_motion_predict/interval_sec: 0.1
* /naive_motion_predict/num_prediction: 10
* /naive_motion_predict/sensor_height: 2.0
* /ndt_matching/get_height: True
* /ndt_matching/gnss_reinit_fitness: 500.0
* /ndt_matching/imu_topic: /imu_raw
* /ndt_matching/imu_upside_down: False
* /ndt_matching/method_type: 0
* /ndt_matching/offset: linear
* /ndt_matching/output_log_data: False
* /ndt_matching/queue_size: 1
* /ndt_matching/use_gnss: True
* /ndt_matching/use_imu: True
* /ndt_matching/use_local_transform: False
* /ndt_matching/use_odom: True
* /op_global_planner/enableDynamicMapUpdate: False
* /op_global_planner/enableLaneChange: False
* /op_global_planner/enableReplan: True
* /op_global_planner/enableRvizInput: True
* /op_global_planner/enableSmoothing: True
* /op_global_planner/mapFileName:
* /op_global_planner/mapSource: 0
* /op_global_planner/pathDensity: 0.75
* /op_global_planner/velocitySource: 1
* /points_map_loader/area: noupdate
* /points_map_loader/arealist_path:
* /points_map_loader/pcd_paths: ['/home/autoware/...
* /pure_pursuit/add_virtual_end_waypoints: False
* /pure_pursuit/const_lookahead_distance: 4.0
* /pure_pursuit/const_velocity: 5.0
* /pure_pursuit/is_linear_interpolation: True
* /pure_pursuit/lookahead_ratio: 2.0
* /pure_pursuit/minimum_lookahead_distance: 6.0
* /pure_pursuit/publishes_for_steering_robot: False
* /pure_pursuit/velocity_source: 0
* /range_vision_fusion_01/camera_info_src: /camera_info
* /range_vision_fusion_01/detected_objects_range: /detection/lidar_...
* /range_vision_fusion_01/detected_objects_vision: /detection/image_...
* /range_vision_fusion_01/min_car_dimensions: [3,2,2]
* /range_vision_fusion_01/min_person_dimensions: [1,2,1]
* /range_vision_fusion_01/overlap_threshold: 0.6
* /range_vision_fusion_01/sync_topics: False
* /ray_ground_filter/base_frame: base_link
* /ray_ground_filter/clipping_height: 3.5
* /ray_ground_filter/concentric_divider_distance: 0.0
* /ray_ground_filter/general_max_slope: 3.0
* /ray_ground_filter/ground_point_topic: /points_ground
* /ray_ground_filter/input_point_topic: /points_raw
* /ray_ground_filter/local_max_slope: 5.0
* /ray_ground_filter/min_height_threshold: 0.05
* /ray_ground_filter/min_point_distance: 0.5
* /ray_ground_filter/no_ground_point_topic: /points_no_ground
* /ray_ground_filter/radial_divider_angle: 0.1
* /ray_ground_filter/reclass_distance_threshold: 0.2
* /robot_description: <?xml version="1....
* /rosbag_fname:
* /rosdistro: melodic
* /rosversion: 1.14.6
* /tf_pitch: 0.0
* /tf_roll: 0.0
* /tf_x: 0
* /tf_y: 0.0
* /tf_yaw: 0.0
* /tf_z: 2.4
* /twist_filter/lateral_accel_limit: 5.0
* /twist_filter/lateral_jerk_limit: 5.0
* /twist_filter/lowpass_gain_angular_z: 0.0
* /twist_filter/lowpass_gain_linear_x: 0.0
* /twist_filter/lowpass_gain_steering_angle: 0.0
* /twist_gate/loop_rate: 30.0
* /twist_gate/use_decision_maker: False
* /use_gui: False
* /use_sim_time: True
* /vehicle_info/wheel_base: 2.7
* /vehiclecmd_to_ackermanndrive/wheelbase: 2.7
* /velocity_set/decelerate_vel_min: 1.3
* /velocity_set/deceleration_obstacle: 1.5
* /velocity_set/deceleration_range: 0
* /velocity_set/deceleration_stopline: 0.6
* /velocity_set/detection_height_bottom: -1.7
* /velocity_set/detection_height_top: 2.5
* /velocity_set/detection_range: 1.3
* /velocity_set/enable_multiple_crosswalk_detection: True
* /velocity_set/points_threshold: 10
* /velocity_set/points_topic: points_no_ground
* /velocity_set/remove_points_upto: 0.5
* /velocity_set/stop_distance_obstacle: 15.0
* /velocity_set/stop_distance_stopline: 5.0
* /velocity_set/temporal_waypoints_size: 100
* /velocity_set/use_crosswalk_detection: False
* /velocity_set/velocity_change_limit: 15
* /velocity_set/velocity_offset: 4
* /vision_beyond_track_01/camera_height: 1.2
* /vision_beyond_track_01/camera_info_src: /camera_info
* /vision_beyond_track_01/objects_topic_src: /detection/image_...
* /vision_darknet_detect/gpu_device_id: 0
* /vision_darknet_detect/image_raw_node: //image_raw
* /vision_darknet_detect/names_file: /home/autoware//a...
* /vision_darknet_detect/network_definition_file: /home/autoware/Au...
* /vision_darknet_detect/nms_threshold: 0.3
* /vision_darknet_detect/pretrained_model_file: /home/autoware//a...
* /vision_darknet_detect/score_threshold: 0.5
* /voxel_grid_filter/measurement_range: 200
* /voxel_grid_filter/output_log: False
* /voxel_grid_filter/points_topic: points_raw
* /wayarea2grid/grid_frame: map
* /wayarea2grid/grid_length_x: 150
* /wayarea2grid/grid_length_y: 150
* /wayarea2grid/grid_position_x: 0
* /wayarea2grid/grid_position_y: 0
* /wayarea2grid/grid_position_z: -2
* /wayarea2grid/grid_resolution: 0.3
* /wayarea2grid/sensor_frame: velodyne
* /waypoint_replanner/use_decision_maker: True
* /waypoint_velocity_visualizer/base_waypoints_rgba: [1.0, 1.0, 1.0, 0.5]
* /waypoint_velocity_visualizer/command_twist_rgba: [1.0, 0.0, 0.0, 0.5]
* /waypoint_velocity_visualizer/control_buffer_size: 100
* /waypoint_velocity_visualizer/current_twist_rgba: [0.0, 0.0, 1.0, 0.5]
* /waypoint_velocity_visualizer/final_waypoints_rgba: [0.0, 1.0, 0.0, 0.5]
* /waypoint_velocity_visualizer/plot_height_ratio: 1.0
* /waypoint_velocity_visualizer/plot_height_shift: 0.2
* /waypoint_velocity_visualizer/plot_metric_interval: 1.0
* /waypoint_velocity_visualizer/use_bar_plot: False
* /waypoint_velocity_visualizer/use_line_plot: True
* /waypoint_velocity_visualizer/use_text_plot: True
* /yolo3_rects/image_out: /image_rects
* /yolo3_rects/image_src: /image_raw
* /yolo3_rects/object_src: /detection/image_...
NODES
/
astar_avoid (waypoint_planner/astar_avoid)
can_odometry (autoware_connector/can_odometry)
can_status_translator (autoware_connector/can_status_translator)
carla_ackermann_control_ego_vehicle (carla_ackermann_control/carla_ackermann_control_node.py)
carla_ego_vehicle_ego_vehicle (carla_ego_vehicle/carla_ego_vehicle.py)
carla_ros_bridge (carla_ros_bridge/bridge.py)
carla_to_autoware_vehicle_status (carla_autoware_bridge/carla_to_autoware_vehicle_status)
config_waypoint_follower_rostopic (rostopic/rostopic)
config_waypoint_replanner_topic (rostopic/rostopic)
costmap_generator (costmap_generator/costmap_generator)
decision_maker (decision_maker/decision_maker_node)
dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175 (dynamic_reconfigure/dynparam)
ego_vehiclecamerafront_to_camera (tf/static_transform_publisher)
ego_vehiclegnss_to_gps (tf/static_transform_publisher)
ego_vehiclelidar_to_velodyne (tf/static_transform_publisher)
goal_relay_ego_vehicle (topic_tools/relay)
imag_relay (topic_tools/relay)
image_tracker_rects (detected_objects_visualizer/visualize_rects)
imm_ukf_pda_01 (imm_ukf_pda_track/imm_ukf_pda)
info_relay (topic_tools/relay)
initialpose_relay_ego_vehicle (topic_tools/relay)
joint_state_publisher (joint_state_publisher/joint_state_publisher)
lane_rule (lane_planner/lane_rule)
lane_select (lane_planner/lane_select)
lane_stop (lane_planner/lane_stop)
lidar_euclidean_cluster_detect (lidar_euclidean_cluster_detect/lidar_euclidean_cluster_detect)
lidar_naive_l_shape_detect (lidar_naive_l_shape_detect/lidar_naive_l_shape_detect)
map_to_mobility (tf/static_transform_publisher)
naive_motion_predict (naive_motion_predict/naive_motion_predict)
ndt_matching (lidar_localizer/ndt_matching)
odometry_to_posestamped (carla_autoware_bridge/odometry_to_posestamped)
op_global_planner (op_global_planner/op_global_planner)
points_map_loader (map_file/points_map_loader)
points_relay (topic_tools/relay)
pose_relay (topic_tools/relay)
pure_pursuit (pure_pursuit/pure_pursuit)
range_vision_fusion_01 (range_vision_fusion/range_vision_fusion)
ray_ground_filter (points_preprocessor/ray_ground_filter)
robot_state_publisher (robot_state_publisher/state_publisher)
rviz (rviz/rviz)
twist_filter (twist_filter/twist_filter)
twist_gate (twist_gate/twist_gate)
ukf_track_relay_01 (topic_tools/relay)
vector_map_loader (map_file/vector_map_loader)
vehiclecmd_to_ackermanndrive (carla_autoware_bridge/vehiclecmd_to_ackermanndrive)
vel_relay (topic_tools/relay)
velocity_set (waypoint_planner/velocity_set)
vision_beyond_track_01 (vision_beyond_track/vision_beyond_track)
vision_darknet_detect (vision_darknet_detect/vision_darknet_detect)
voxel_grid_filter (points_downsampler/voxel_grid_filter)
wayarea2grid (object_map/wayarea2grid)
waypoint_marker_publisher (waypoint_maker/waypoint_marker_publisher)
waypoint_replanner (waypoint_maker/waypoint_replanner)
waypoint_velocity_visualizer (waypoint_maker/waypoint_velocity_visualizer)
world_to_map (tf/static_transform_publisher)
yolo3_rects (detected_objects_visualizer/visualize_rects)
/detection/fusion_tools/
range_fusion_visualization_01 (detected_objects_visualizer/visualize_detected_objects)
/detection/l_shaped/
naive_shape_visualization_01 (detected_objects_visualizer/visualize_detected_objects)
/detection/lidar_detector/
cluster_detect_visualization_01 (detected_objects_visualizer/visualize_detected_objects)
object_roi_filter_clustering (roi_object_filter/roi_object_filter)
/detection/lidar_tracker/
ukf_track_visualization_01 (detected_objects_visualizer/visualize_detected_objects)
/prediction/motion_predictor/
naive_prediction_visualization_01 (detected_objects_visualizer/visualize_detected_objects)
ROS_MASTER_URI=http://localhost:11311
process[carla_ros_bridge-1]: started with pid [837]
process[goal_relay_ego_vehicle-2]: started with pid [838]
process[initialpose_relay_ego_vehicle-3]: started with pid [841]
process[carla_ego_vehicle_ego_vehicle-4]: started with pid [847]
process[carla_ackermann_control_ego_vehicle-5]: started with pid [853]
/usr/local/lib/python2.7/dist-packages/simple_pid/PID.py:22: UserWarning: time.monotonic() not available in python < 3.3, using time.time() as fallback
warnings.warn('time.monotonic() not available in python < 3.3, using time.time() as fallback')
[INFO] [1605816706.478239, 0.000000]: Trying to connect to localhost:2000
[WARN] [1605816706.490677, 0.000000]: Version mismatch detected: You are trying to connect to a simulator that might be incompatible with this API. Client API version: 0.9.10.1. Simulator API version: 784d9b9f
WARNING: Version mismatch detected: You are trying to connect to a simulator that might be incompatible with this API
WARNING: Client API version = 0.9.10.1
WARNING: Simulator API version = 784d9b9f
process[dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175-6]: started with pid [856]
process[world_to_map-7]: started with pid [874]
[INFO] [1605816707.991011, 0.000000]: Loading town 'Town01' (previous: 'Town03').
[INFO] [1605816708.017669, 0.000000]: Reconfigure Request: speed (0.05, 0.0, 0.5),accel (0.05, 0.0, 0.05),
[INFO] [1605816708.383527, 0.000000]: Reconfigure Request: speed (0.15, 0.0, 0.4),accel (0.03, 0.0, 0.05),
process[map_to_mobility-8]: started with pid [878]
[dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175-6] process has finished cleanly
log file: /home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/dynparam_bignrz_Lenovo_ideapad_520_15IKB_822_1709611057771487175-6*.log
[INFO] [1605816708.848634, 0.000000]: listening to server localhost:2000
[INFO] [1605816708.849817, 0.000000]: using vehicle filter: vehicle.toyota.prius
[INFO] [1605816708.851037, 0.000000]: Waiting for CARLA world (topic: /carla/world_info)...
process[ego_vehiclegnss_to_gps-9]: started with pid [907]
process[ego_vehiclelidar_to_velodyne-10]: started with pid [919]
process[ego_vehiclecamerafront_to_camera-11]: started with pid [925]
process[points_relay-12]: started with pid [932]
process[imag_relay-13]: started with pid [937]
process[info_relay-14]: started with pid [943]
[INFO] [1605816712.413236, 0.000000]: synchronous_mode: False
[INFO] [1605816712.414577, 0.000000]: fixed_delta_seconds: 0.05
process[odometry_to_posestamped-15]: started with pid [949]
process[vehiclecmd_to_ackermanndrive-16]: started with pid [955]
process[carla_to_autoware_vehicle_status-17]: started with pid [963]
process[joint_state_publisher-18]: started with pid [969]
process[robot_state_publisher-19]: started with pid [984]
[ WARN] [1605816715.201172985]: The 'state_publisher' executable is deprecated. Please use 'robot_state_publisher' instead
process[points_map_loader-20]: started with pid [995]
shutdown request: new node registered with same name
[vehiclecmd_to_ackermanndrive-16] process has finished cleanly
log file: /home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/vehiclecmd_to_ackermanndrive-16*.log
process[vector_map_loader-21]: started with pid [1005]
process[wayarea2grid-22]: started with pid [1013]
process[ray_ground_filter-23]: started with pid [1019]
process[can_odometry-24]: started with pid [1026]
process[voxel_grid_filter-25]: started with pid [1035]
[ERROR] [1605816718.874604, 0.000000]: Timeout while waiting for world info!
process[ndt_matching-26]: started with pid [1043]
process[lidar_euclidean_cluster_detect-27]: started with pid [1049]
[carla_ego_vehicle_ego_vehicle-4] process has died [pid 847, exit code 1, cmd /home/autoware/carla_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py __name:=carla_ego_vehicle_ego_vehicle __log:=/home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/carla_ego_vehicle_ego_vehicle-4.log].
log file: /home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/carla_ego_vehicle_ego_vehicle-4*.log
process[detection/lidar_detector/object_roi_filter_clustering-28]: started with pid [1060]
[ INFO] [1605816719.985509373]: [roi_object_filter] objects_src_topic: /detection/lidar_detector/objects
[ INFO] [1605816719.986526428]: [roi_object_filter] wayarea_gridmap_topic: /grid_map_wayarea
[ INFO] [1605816719.987341764]: [roi_object_filter] sync_topics: 0
[ INFO] [1605816719.988166746]: [roi_object_filter] wayarea_gridmap_layer: wayarea
[ INFO] [1605816719.988589362]: [roi_object_filter] wayarea_no_road_value: 255s
[ INFO] [1605816719.989384114]: [roi_object_filter] exception_list: [person, bicycle]
[ INFO] [1605816720.007628424]: [roi_object_filter] Publishing filtered objects in /detection/lidar_detector/objects_filtered
[ INFO] [1605816720.007709486]: [roi_object_filter] Ready. Waiting for data...
process[detection/lidar_detector/cluster_detect_visualization_01-29]: started with pid [1068]
[ INFO] [1605816720.436846154]: [visualize_detected_objects] objects_src_topic: /detection/lidar_detector/objects_filtered
[ INFO] [1605816720.437765023]: [visualize_detected_objects] object_speed_threshold: 0.10
[ INFO] [1605816720.438075660]: [visualize_detected_objects] arrow_speed_threshold: 0.25
[ INFO] [1605816720.438422122]: [visualize_detected_objects] marker_display_duration: 0.20
[ INFO] [1605816720.438762127]: [visualize_detected_objects] label_color: {R:255.0, G:255.0, B:255.0, A:1.0}
[ INFO] [1605816720.439050459]: [visualize_detected_objects] arrow_color: {R:0.0, G:255.0, B:0.0, A:0.8}
[ INFO] [1605816720.439354891]: [visualize_detected_objects] hull_color: {R:51.0, G:204.0, B:51.0, A:0.8}
[ INFO] [1605816720.439634377]: [visualize_detected_objects] box_color: {R:51.0, G:128.0, B:204.0, A:0.8}
[ INFO] [1605816720.439941486]: [visualize_detected_objects] model_color: {R:190.0, G:190.0, B:190.0, A:0.5}
[ INFO] [1605816720.440229635]: [visualize_detected_objects] centroid_color: {R:77.0, G:121.0, B:255.0, A:0.8}
[ INFO] [1605816720.442510364]: [visualize_detected_objects] object_src_topic: /detection/lidar_detector/objects_filtered
[ INFO] [1605816720.445040350]: [visualize_detected_objects] markers_out_topic: /detection/lidar_detector/objects_markers
process[lidar_naive_l_shape_detect-30]: started with pid [1075]
process[detection/l_shaped/naive_shape_visualization_01-31]: started with pid [1081]
[ INFO] [1605816721.477490153]: [visualize_detected_objects] objects_src_topic: /detection/l_shaped/objects
[ INFO] [1605816721.479171039]: [visualize_detected_objects] object_speed_threshold: 0.10
[ INFO] [1605816721.479637007]: [visualize_detected_objects] arrow_speed_threshold: 0.25
[ INFO] [1605816721.480076367]: [visualize_detected_objects] marker_display_duration: 0.20
[ INFO] [1605816721.480524839]: [visualize_detected_objects] label_color: {R:255.0, G:255.0, B:255.0, A:1.0}
[ INFO] [1605816721.480914771]: [visualize_detected_objects] arrow_color: {R:0.0, G:255.0, B:0.0, A:0.8}
[ INFO] [1605816721.481587213]: [visualize_detected_objects] hull_color: {R:51.0, G:204.0, B:51.0, A:0.8}
[ INFO] [1605816721.482340658]: [visualize_detected_objects] box_color: {R:51.0, G:128.0, B:204.0, A:0.8}
[ INFO] [1605816721.483012833]: [visualize_detected_objects] model_color: {R:190.0, G:190.0, B:190.0, A:0.5}
[ INFO] [1605816721.483534410]: [visualize_detected_objects] centroid_color: {R:77.0, G:121.0, B:255.0, A:0.8}
[ INFO] [1605816721.486744139]: [visualize_detected_objects] object_src_topic: /detection/l_shaped/objects
[ INFO] [1605816721.488561771]: [visualize_detected_objects] markers_out_topic: /detection/l_shaped/objects_markers
process[imm_ukf_pda_01-32]: started with pid [1087]
[ERROR] [1605816722.415947, 0.000000]: Error: time-out of 10000ms while waiting for the simulator, make sure the simulator is ready and connected to localhost:2000
process[detection/lidar_tracker/ukf_track_visualization_01-33]: started with pid [1093]
[ INFO] [1605816722.710205380]: [visualize_detected_objects] objects_src_topic: /detection/lidar_tracker/objects
[ INFO] [1605816722.711285417]: [visualize_detected_objects] object_speed_threshold: 0.10
[ INFO] [1605816722.711699633]: [visualize_detected_objects] arrow_speed_threshold: 0.25
[ INFO] [1605816722.712176802]: [visualize_detected_objects] marker_display_duration: 0.20
[ INFO] [1605816722.712547553]: [visualize_detected_objects] label_color: {R:255.0, G:255.0, B:255.0, A:1.0}
[ INFO] [1605816722.712910734]: [visualize_detected_objects] arrow_color: {R:0.0, G:255.0, B:0.0, A:0.8}
[ INFO] [1605816722.713262170]: [visualize_detected_objects] hull_color: {R:51.0, G:204.0, B:51.0, A:0.8}
[ INFO] [1605816722.713601004]: [visualize_detected_objects] box_color: {R:51.0, G:128.0, B:204.0, A:0.8}
[ INFO] [1605816722.714023585]: [visualize_detected_objects] model_color: {R:190.0, G:190.0, B:190.0, A:0.5}
[ INFO] [1605816722.714420008]: [visualize_detected_objects] centroid_color: {R:77.0, G:121.0, B:255.0, A:0.8}
[ INFO] [1605816722.716427199]: [visualize_detected_objects] object_src_topic: /detection/lidar_tracker/objects
[ INFO] [1605816722.717280787]: [visualize_detected_objects] markers_out_topic: /detection/lidar_tracker/objects_markers
================================================================================REQUIRED process [carla_ros_bridge-1] has died!
process has finished cleanly
log file: /home/autoware/.ros/log/368092b6-2aa2-11eb-92f7-cc2f71e7786d/carla_ros_bridge-1*.log
Initiating shutdown!
================================================================================
process[ukf_track_relay_01-34]: started with pid [1105]
RLException: cannot add process [vision_darknet_detect-35] after process monitor has been shut down
The traceback for the exception was written to the log file
[ukf_track_relay_01-34] killing on exit
[detection/lidar_tracker/ukf_track_visualization_01-33] killing on exit
[imm_ukf_pda_01-32] killing on exit
[detection/l_shaped/naive_shape_visualization_01-31] killing on exit
[lidar_naive_l_shape_detect-30] killing on exit
[detection/lidar_detector/cluster_detect_visualization_01-29] killing on exit
[detection/lidar_detector/object_roi_filter_clustering-28] killing on exit
[lidar_euclidean_cluster_detect-27] killing on exit
[ndt_matching-26] killing on exit
[voxel_grid_filter-25] killing on exit
autoware@bignrz-Lenovo-ideapad-520-15IKB:/home/autoware$ terminate called after throwing an instance of 'boost::exception_detail::clone_impl<boost::exception_detail::error_info_injector<boost::lock_error> >'
what(): boost: mutex lock failed in pthread_mutex_lock: Invalid argument
Hello all,
My software version:
Ubuntu 18.04
ROS melodic
Autoware 1.14
Carla 0.9.10.1
Problem
I followed the tutorial, basically, it works. I can see the route and point cloud in RVIZ, great contribution!
However, the vehicle could not move.
I tried these parameters, they don't help. Under manual control mode, the vehicle cannot move as well.
<arg name='use_ground_truth_localization' default='false'/>
<arg name='use_ground_truth_detections' default='false'/>
<arg name='use_manual_control' default='true'/>
Error
There is a TF error.( I guess this is the main problem)
[ERROR] [1608667944.150539754, 100.767592988]: Failed transform from base_link to ego_vehicle/lidar/lidar1
Can you kindly give me some suggestions?
Thanks a lot!
Hello,I notice that a vector map is loaded in rviz which runs the open planner? I wander that currently if a vector map is provided in carla town.
When launching roslaunch $CARLA_AUTOWARE_ROOT/devel.launch
and RVIZ I can not set the navigation goal. (I use ros melodic, autoware 1.12, carla 0.9.7 and ubuntu 18.)
In rviz a expand the Global Waypoints
:
global_velocity_lane_1/0 For frame [map]: No transform to fixed frame [velodyne]. TF error: [Lookup would require extrapolation into the future. Requested time 138126.064153380 but the latest data is at time 138036.874152051, when looking up transform from frame [map] to frame [velodyne]]
global_velocity_lane_1/1 ...
global_velocity_lane_1/2 ...
global_velocity_lane_1/3 ...
Additonally I checked the Rostopic:
➜ autoware.ai rostopic info /global_waypoints_mark
Type: visualization_msgs/MarkerArray
Publishers:
* /waypoint_marker_publisher (http://lh:34171/)
Subscribers:
* /rviz_1581516562359664169 (http://lh:36479/)
How to fix this?
Hello, I want to test an older version of carla-autoware (specifically commit 7b71fba) but when I call git checkout 7b71fba05be482458cf8cd95d92f68150448f01a
I get the following error
git checkout 7b71fba05be482458cf8cd95d92f68150448f01a
Downloading autoware_data/map/map.pcd (127 MB)
Error downloading object: autoware_data/map/map.pcd (1ffe294): Smudge error: Error downloading autoware_data/map/map.pcd (1ffe294e6b4da8a342cf1dce1b0d7733db4e3e5a712440baf70e0e9e64c62a72): batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access.
Errors logged to [suppressed]
Use `git lfs logs last` to view the log.
error: external filter git-lfs smudge -- %f failed 2
error: external filter git-lfs smudge -- %f failed
fatal: autoware_data/map/map.pcd: smudge filter lfs failed
Is there any workaround to this issue?
Edit: on master git clone
and git submodule update --init
work fine.
Hi
We are using the carla-autoware docker to do some test on our scenarios.
When we launch the devel.launch, the ego car did not following the path we set,and the logo said: no candidate, using the nearest waypoint of all waypoints.
Is this because of the lacking of vector map?
Or any other point we have missed?
THX
Hello, I am trying to connect the Autoware and carla, but when I use the command"git submodule update --init ", It shows the error as below, anyone can help?
fatal: reference is not a tree: 33bd00b6441875c4d086f9f6f33ad915ae44e1b1
Unable to checkout '33bd00b6441875c4d086f9f6f33ad915ae44e1b1' in submodule path 'docker/challenge/scenario_runner'
I got this run time error. Any idea on what am I missing?
[INFO] [1558636356.781753, 0.000000]: listening to server localhost:2000
[INFO] [1558636356.781993, 0.000000]: using vehicle filter: vehicle.toyota.prius*
Traceback (most recent call last):
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 258, in <module>
main()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 251, in main
ego_vehicle.run()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 233, in run
self.world = client.get_world()
RuntimeError: rpc::rpc_error during call in function version
I ran carla from UnrealEditor. (Not using nvidia-docker)
Autoware was build using colcon. (latest release)
Here is entire output
started core service [/rosout]
process[carla_manual_control_ego_vehicle-2]: started with pid [24935]
process[carla_ros_bridge-3]: started with pid [24936]
process[goal_relay-4]: started with pid [24937]
process[initialpose_relay-5]: started with pid [24945]
process[carla_ego_vehicle_ego_vehicle-6]: started with pid [24959]
process[carla_waypoint_publisher-7]: started with pid [24962]
process[carla_points_map_loader-8]: started with pid [24966]
process[world_to_map-9]: started with pid [24973]
process[map_to_mobility-10]: started with pid [24976]
process[egovehiclegnss_to_gps-11]: started with pid [24985]
process[egovehiclelidar_to_velodyne-12]: started with pid [25002]
process[egovehiclecamerafront_to_camera-13]: started with pid [25007]
process[points_relay-14]: started with pid [25017]
process[imag_relay-15]: started with pid [25025]
process[odometry_to_posestamped-16]: started with pid [25029]
process[vehiclecmd_to_ackermanndrive-17]: started with pid [25034]
process[carla_to_autoware_vehicle_status-18]: started with pid [25045]
process[carla_to_autoware_waypoints-19]: started with pid [25051]
process[carla_ackermann_control_ego_vehicle-20]: started with pid [25058]
process[ray_ground_filter-21]: started with pid [25060]
process[joint_state_publisher-22]: started with pid [25064]
process[robot_state_publisher-23]: started with pid [25075]
process[can_odometry-24]: started with pid [25079]
process[voxel_grid_filter-25]: started with pid [25088]
process[ndt_matching-26]: started with pid [25093]
process[lidar_euclidean_cluster_detect-27]: started with pid [25096]
process[detection/lidar_detector/cluster_detect_visualization_01-28]: started with pid [25100]
process[can_status_translator-29]: started with pid [25104]
process[pose_relay-30]: started with pid [25111]
process[vel_relay-31]: started with pid [25119]
process[waypoint_marker_publisher-32]: started with pid [25127]
process[lane_rule-33]: started with pid [25131]
process[lane_stop-34]: started with pid [25137]
process[lane_select-35]: started with pid [25143]
process[costmap_generator-36]: started with pid [25153]
/usr/local/lib/python2.7/dist-packages/simple_pid/PID.py:22: UserWarning: time.monotonic() not available in python < 3.3, using time.time() as fallback
warnings.warn('time.monotonic() not available in python < 3.3, using time.time() as fallback')
process[astar_avoid-37]: started with pid [25164]
process[velocity_set-38]: started with pid [25169]
process[config_waypoint_follower_rostopic-39]: started with pid [25188]
process[pure_pursuit-40]: started with pid [25205]
process[twist_filter-41]: started with pid [25212]
process[twist_gate-42]: started with pid [25216]
pygame 1.9.6
Hello from the pygame community. https://www.pygame.org/contribute.html
... logging to /home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/roslaunch-adl-Nuvo-5000-24966.log
[ INFO] [1558636356.298618714]: Initializing Ground Filter, please wait...
[ INFO] [1558636356.375458375]: Input point_topic: /points_raw
[ INFO] [1558636356.376912660]: [visualize_detected_objects] objects_src_topic: /detection/lidar_detector/objects
[ INFO] [1558636356.417324627]: [visualize_detected_objects] object_speed_threshold: 0.10
[ INFO] [1558636356.442487021]: sensor_height[meters]: 2.400000
[ INFO] [1558636356.468509089]: [visualize_detected_objects] arrow_speed_threshold: 0.25
[ INFO] [1558636356.499586816]: [visualize_detected_objects] marker_display_duration: 0.20
[ INFO] [1558636356.523532981]: general_max_slope[deg]: 5.000000
[ INFO] [1558636356.527102602]: [visualize_detected_objects] label_color: {R:255.0, G:255.0, B:255.0, A:1.0}
[ INFO] [1558636356.559799610]: [visualize_detected_objects] arrow_color: {R:0.0, G:255.0, B:0.0, A:0.8}
[ INFO] [1558636356.574173609]: local_max_slope[deg]: 8.000000
[ INFO] [1558636356.575093794]: [visualize_detected_objects] hull_color: {R:51.0, G:204.0, B:51.0, A:0.8}
[ INFO] [1558636356.588018424]: [visualize_detected_objects] box_color: {R:51.0, G:128.0, B:204.0, A:0.8}
[ INFO] [1558636356.596617704]: radial_divider_angle[deg]: 0.080000
[ INFO] [1558636356.597644559]: [visualize_detected_objects] model_color: {R:190.0, G:190.0, B:190.0, A:0.5}
[ INFO] [1558636356.610020981]: [visualize_detected_objects] centroid_color: {R:77.0, G:121.0, B:255.0, A:0.8}
[ INFO] [1558636356.618689191]: concentric_divider_distance[meters]: 0.010000
[ INFO] [1558636356.640319899]: min_height_threshold[meters]: 0.500000
[ INFO] [1558636356.666588162]: clipping_height[meters]: 0.200000
[ INFO] [1558636356.681490178]: [visualize_detected_objects] object_src_topic: /detection/lidar_detector/objects
[ INFO] [1558636356.689326101]: min_point_distance[meters]: 1.850000
[ INFO] [1558636356.689815268]: [visualize_detected_objects] markers_out_topic: /detection/lidar_detector/objects_markers
[INFO] [1558636356.696879, 0.000000]: Reconfigure Request: speed (0.05, 0.0, 0.5),accel (0.05, 0.0, 0.05),
[ INFO] [1558636356.705894218]: reclass_distance_threshold[meters]: 0.200000
[INFO] [1558636356.781753, 0.000000]: listening to server localhost:2000
[INFO] [1558636356.781993, 0.000000]: using vehicle filter: vehicle.toyota.prius*
Traceback (most recent call last):
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 258, in <module>
main()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 251, in main
ego_vehicle.run()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py", line 233, in run
self.world = client.get_world()
RuntimeError: rpc::rpc_error during call in function version
[INFO] [1558636356.802088, 0.000000]: Trying to connect to localhost:2000
[INFO] [1558636356.802977, 0.000000]: Done
Traceback (most recent call last):
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/client.py", line 59, in <module>
main()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/client.py", line 39, in main
carla_world = carla_client.get_world()
RuntimeError: rpc::rpc_error during call in function version
[INFO] [1558636356.903407, 0.000000]: Trying to connect to localhost:2000
[INFO] [1558636356.904752, 0.000000]: Done
Traceback (most recent call last):
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_waypoint_publisher/src/carla_waypoint_publisher/carla_waypoint_publisher.py", line 205, in <module>
main()
File "/home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_waypoint_publisher/src/carla_waypoint_publisher/carla_waypoint_publisher.py", line 189, in main
carla_world = carla_client.get_world()
RuntimeError: rpc::rpc_error during call in function version
[carla_ros_bridge-3] process has died [pid 24936, exit code 1, cmd /home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/client.py __name:=carla_ros_bridge __log:=/home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_ros_bridge-3.log].
log file: /home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_ros_bridge-3*.log
[ INFO] [1558636357.163887391]: Radial Divisions: 4500
[ INFO] [1558636357.167285794]: No Ground Output Point Cloud no_ground_point_topic: /points_no_ground
[ INFO] [1558636357.170719053]: Only Ground Output Point Cloud ground_topic: /points_ground
[ INFO] [1558636357.170753195]: Subscribing to... /points_raw
[ INFO] [1558636357.196055796]: Ready
[ WARN] [1558636357.213342678]: Waiting for subscribing topics...
[carla_ego_vehicle_ego_vehicle-6] process has died [pid 24959, exit code 1, cmd /home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_ego_vehicle/src/carla_ego_vehicle/carla_ego_vehicle.py __name:=carla_ego_vehicle_ego_vehicle __log:=/home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_ego_vehicle_ego_vehicle-6.log].
log file: /home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_ego_vehicle_ego_vehicle-6*.log
[carla_waypoint_publisher-7] process has died [pid 24962, exit code 1, cmd /home/autoware/carla-autoware/catkin_ws/src/ros-bridge/carla_waypoint_publisher/src/carla_waypoint_publisher/carla_waypoint_publisher.py __name:=carla_waypoint_publisher __log:=/home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_waypoint_publisher-7.log].
log file: /home/autoware/.ros/log/21800e9a-7d89-11e9-a0c4-78d004236ed8/carla_waypoint_publisher-7*.log
[ INFO] [1558636362.626762706]: euclidean_cluster > Setting points node to /points_raw
[ INFO] [1558636362.627217382]: Euclidean Clustering: Difference of Normals will not be used.
[ INFO] [1558636362.628208733]: [euclidean_clustering] downsample_cloud: 0
[ INFO] [1558636362.629025807]: [euclidean_clustering] remove_ground: 1
[ INFO] [1558636362.629961175]: [euclidean_clustering] leaf_size: 0.100000
[ INFO] [1558636362.630778136]: [euclidean_clustering] cluster_size_min 20
[ INFO] [1558636362.631564279]: [euclidean_clustering] cluster_size_max: 100000
[ INFO] [1558636362.632329344]: [euclidean_clustering] pose_estimation: 1
[ INFO] [1558636362.633066682]: [euclidean_clustering] clip_min_height: -1.300000
[ INFO] [1558636362.633871716]: [euclidean_clustering] clip_max_height: 0.500000
[ INFO] [1558636362.634954932]: [euclidean_clustering] keep_lanes: 0
[ INFO] [1558636362.635733841]: [euclidean_clustering] keep_lane_left_distance: 5.000000
[ INFO] [1558636362.636490109]: [euclidean_clustering] keep_lane_right_distance: 5.000000
[ INFO] [1558636362.637240591]: [euclidean_clustering] max_boundingbox_side: 10.000000
[ INFO] [1558636362.637990139]: [euclidean_clustering] cluster_merge_threshold: 1.500000
[ INFO] [1558636362.638884613]: [euclidean_clustering] output_frame: ego_vehicle/lidar/lidar1
[ INFO] [1558636362.639635739]: [euclidean_clustering] remove_points_upto: 0.000000
[ INFO] [1558636362.640409376]: [euclidean_clustering] clustering_distance: 0.750000
[ INFO] [1558636362.641123962]: [euclidean_clustering] use_gpu: 0
[ INFO] [1558636362.641888159]: [euclidean_clustering] use_multiple_thres: 0
[ INFO] [1558636362.642685150]: [euclidean_clustering] clustering_distances: [0.5,1.1,1.6,2.1,2.6]
[ INFO] [1558636362.643524764]: [euclidean_clustering] clustering_ranges: [15,30,45,60]
^C[twist_gate-42] killing on exit
[twist_filter-41] killing on exit
[pure_pursuit-40] killing on exit
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.