lcford2 / Jrl

Jeremy's Robotics Library

Jrl

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.

Installation

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