Package: safemotions
Learning Collision-free and Torque-limited Robot Trajectories based on Alternative Safe BehaviorsThis python package provides the code to learn torque-limited and collision-free robot trajectories without exceeding limits on the position, velocity, acceleration and jerk of each robot joint.InstallationThe package can be installed by runningpip install safemotions  # for safe trajectory generation only or
pip install safemotions[train]  # to include dependencies required to train and evaluate neural networks.Trajectory generationTo generate a random trajectory with a single robot runpython -m safemotions.random_agent --use_gui --check_braking_trajectory_collisions --check_braking_trajectory_torque_limits --torque_limit_factor=0.6 --plot_trajectoryFor a demonstration scenario with two robots runpython -m safemotions.random_agent --use_gui --check_braking_trajectory_collisions --robot_scene=1Collision-free trajectories for three robots can be generated by runningpython -m safemotions.random_agent --use_gui --check_braking_trajectory_collisions --robot_scene=2Pretrained networksVarious pretrained networks for reaching randomly sampled target points are provided.Make sure you use ray==1.4.1 to open the pretrained networks.Industrial robotsTo generate and plot trajectories for a reaching task with a single industrial robot runpython-msafemotions.evaluate--use_gui--plot_trajectory--plot_actual_torques--checkpoint=industrial/one_robot/collisionTrajectories for two and three industrial robots with alternating target points can be generated by runningpython-msafemotions.evaluate--use_gui--checkpoint=industrial/two_robots/collision/alternatingandpython-msafemotions.evaluate--use_gui--checkpoint=industrial/three_robots/collision/alternatingHumanoid robotsARMAR 6ARMAR 6x4Alternating target points--checkpoint=humanoid/armar6/collision/alternating--checkpoint=humanoid/armar6_x4/collision/alternatingSimultaneous target points--checkpoint=humanoid/armar6/collision/simultaneous--checkpoint=humanoid/armar6_x4/collision/simultaneousSingle target point--checkpoint=humanoid/armar6/collision/single--checkpoint=humanoid/armar6_x4/collision/singleTrainingNetworks can also be trained from scratch. For instance, a reaching task with a single robot can be learned by runningpython-msafemotions.train--logdir=safemotions_training--name=industrial_one_robot_collision--robot_scene=0--online_trajectory_time_step=0.1--hidden_layer_activation=swish--online_trajectory_duration=8.0--obstacle_scene=3--use_target_points--target_point_sequence=0--target_point_cartesian_range_scene=0--target_link_offset="[0, 0, 0.126]"--target_point_radius=0.065--obs_add_target_point_pos--obs_add_target_point_relative_pos--check_braking_trajectory_collisions--closest_point_safety_distance=0.01--acc_limit_factor_braking=1.0--jerk_limit_factor_braking=1.0--punish_action--action_punishment_min_threshold=0.95--action_max_punishment=0.4--target_point_reached_reward_bonus=5--pos_limit_factor=1.0--vel_limit_factor=1.0--acc_limit_factor=1.0--jerk_limit_factor=1.0--torque_limit_factor=1.0--punish_braking_trajectory_min_distance--braking_trajectory_min_distance_max_threshold=0.05--braking_trajectory_max_punishment=0.5--last_layer_activation=tanh--solver_iterations=50--normalize_reward_to_initial_target_point_distance--collision_check_time=0.033--iterations_per_checkpoint=50--time=200PublicationThe corresponding publication is available athttps://arxiv.org/abs/2103.03793.DisclaimerTHE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.