Jrl ('Jeremy's robotics library') is a robotics library containing robot models for popular robots as well as efficient, pytorch based parallelized implementations of forward kinematics, inverse kinematics, and robot-robot + robot-environment collision checking.
Robots
Robot models include (run with scripts/visualize_robot.py to view):
| jrl name | full name |
|---|---|
| Panda | Franka Panda |
| Fetch | Fetch |
| FetchArm | Fetch - Arm (no lift joint) |
| Iiwa7 | Kuka LBR IIWA7 |
| Rizon4 | Flexiv Rizon 4 |
| Ur5 | Ur5 |
Functions
Available operations include (all part of the Robot class):
| function | description |
|---|---|
forward_kinematics_batch() |
(batched) forward kinematics |
jacobian_batch_pt() |
(batched) Jacobian of the manipulators forward kinematics map (w.r.t. joint angles) |
inverse_kinematics_single_step_levenburg_marquardt() |
(batched) Inverse kinematics step using Levenburg-Marquardt |
inverse_kinematics_single_step_batch_pt() |
(batched) Inverse kinematics step using the jacobian pseudo-inverse method |
self_collision_distances_batch() |
(batched) Pairwise distance between each link of the robot |
self_collision_distances_jacobian_batch() |
(batched) Jacobian of self_collision_distances_batch() w.r.t. joint angles |
env_collision_distances_batch() |
(batched) Pairwise distance between each link of the robot and each cuboid in the environment |
env_collision_distances_jacobian_batch() |
(batched) Jacobian of env_collision_distances_batch() w.r.t. joint angles |
Quickstart code. This script will load a Panda robot model and then run forward and inverse kinematics on randomly sampled configs. See demo.py for the complete script, which includes robot-robot and robot-environment collision checking.
from jrl.robots import Panda
from jrl.evaluation import pose_errors_cm_deg
import torch
def assert_poses_almost_equal(poses_1, poses_2):
pos_errors_cm, rot_errors_deg = pose_errors_cm_deg(poses_1, poses_2)
assert (pos_errors_cm.max().item() < 0.01) and (rot_errors_deg.max().item() < 0.1)
robot = Panda()
joint_angles, poses = robot.sample_joint_angles_and_poses(n=5, return_torch=True) # sample 5 random joint angles and matching poses
# Run forward-kinematics
poses_fk = robot.forward_kinematics_batch(joint_angles)
assert_poses_almost_equal(poses, poses_fk)
# Run inverse-kinematics
ik_sols = joint_angles + 0.1 * torch.randn_like(joint_angles)
for i in range(5):
ik_sols = robot.inverse_kinematics_single_step_levenburg_marquardt(poses, ik_sols)
assert_poses_almost_equal(poses, robot.forward_kinematics_batch(ik_sols))Note: This project uses the w,x,y,z format for quaternions.
Clone the repo and install with poetry. Don't use the version on pypi - it will remain out of date until this project hardens
git clone https://github.com/jstmn/jrl.git && cd jrl/
poetry install --without dev
# or:
poetry install # includes dev dependencies, like the linter
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