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jaguar-bot

This is a collection of packages that was used in our autonomous robot project.

jderobot

Software suite for robotics, computer vision and home automation

jerk-optimization-of-timed-elastic-band-algorithm

To make the trajectory produced by the time elastic band algorithm less jerky, an item considering jerk (derivative of acceleration) is added to the original optimazation framwork.

kitti_to_rosbag

Dataset tools for working with the KITTI dataset raw data ( http://www.cvlibs.net/datasets/kitti/raw_data.php ) and converting it to a ROS bag. Also allows a library for direct access to poses, velodyne scans, and images.

knowrob

KnowRob core packages and general issue tracker for the KnowRob knowledge base

kobuki

Software for iClebo Kobuki

kobuki-x

Custom Kobuki Implementations

kobuki_soft

Soft version of kobuki node.

lama_costmap

Jockeys for the Large Maps Framework (LaMa) based on LaserScan with possibly less than 360°

lane_center_keeping

lattice_planner

The lattice_planner package provides a move_base global planner plugin for a time-bounded A* lattice planner. The planner is designed to plan time dependent, dynamically feasible navigation paths for robots with differential drive constraints. It uses a dynamic cost map which is based on the ROS costmap representation from the costmap_2d package.

learn_heuristics_planner

linorobot_ackermann

Ackermann Steering ROS Platform

linux

Linux kernel source tree

long-term_topological_navigation

Relates to the Fentanes et al.: Now or later? predicting and maximising success of navigation actions from long-term experience. In ICRA`15

lrm_carina

CaRINA I ROS packages

mapf-map-explanations

master_thesis_local_planning_algorithms_in_ros

The main goal of this work is to compare several local planning algorithms (planners). The assumption is to compare, two algorithms which are already implemented in ROS environment and two selected motion planning algorithms. Based on the performed research of the available motion planning approaches, two algorithms have been selected, Potential field based algorithm and BUG0 algorithm (Chapters 2-3). In order to achieve the main goal of this master thesis, the whole test environment based on ROS has been created. The Gazebo2 simulator and the Pioneer 3-DX robot model have been used in that order. The Gazebo2 simulator and the robot model have been configured with the ROS environment compatibility (Chapter 4). Selected algorithms have been implemented in Python 2.7 programming language. Implemented algorithms and ROS algorithms have been configured with previously created test environment (Chapters 5-6). The robot working area became the rectangular building wit dimensions, 100x30[m]. About 40 obstacles, with different size, have been created in the building (Chapter 7.1). Next, the tests have been performed, in the prepared working area, in order to obtain the optimal parameters sets for each algorithm.

mav_control_rw

Control strategies for rotary wing Micro Aerial Vehicles using ROS

mav_trajectory_generation

Polynomial trajectory generation and optimization, especially for rotary-wing MAVs.

melvin

Navigation Planning and Control Stack for SBPL's Segbot

micros-drt

An implementation of ROS 1.x on DDS

mir_layered_costmap

Port of the costmap_2d package from the navigation stack in ROS Indigo.

motion_planning

FMT, Elastic Stretching, and Speed Optimization for AA203.

motionplanning.jl

Robotic motion planning in Julia

move_base_3d

move_base_flex

Move Base Flex: a backwards-compatible replacement for move_base

movebase_eklavya

mrvk_project

navigation

ROS Navigation stack. Code for finding where the robot is and how it can get somewhere else.