IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020

TORM: Fast and Accurate Trajectory Optimization of Redundant Manipulator given an End-Effector Path

TORM: Fast and Accurate Trajectory Optimization of Redundant Manipulator given an End-Effector Path

by Mincheul Kang, Heechan Shin, Donghyuk Kim, and Sung-Eui Yoon

Korea Advanced Institute of Science and Technology (KAIST)






Abstract

A redundant manipulator has multiple inverse kinematics solutions per an end-effector pose. Accordingly, there can be many trajectories for joints that follow a given endeffector path in the Cartesian space. In this paper, we present a trajectory optimization of a redundant manipulator (TORM) to synthesize a trajectory that follows a given end-effector path accurately, while achieving the smoothness and collisionfree manipulation. Our method holistically incorporates three desired properties into the trajectory optimization process by integrating the Jacobian-based inverse kinematics solving method and an optimization-based motion planning approach. Specifically, we optimize a trajectory using two-stage gradient descent to reduce potential competition between different properties during the update. To avoid falling into local minima, we iteratively explore different candidate trajectories with our local update. We compare our method with the state-of-theart methods in test scenes including external obstacles and two non-obstacle problems. Our method robustly minimizes the pose error in a progressive manner while satisfying various desirable properties.



These figures show a sequence of maneuvering the Fetch manipulator to follow the specified end-effector path (red lines). Our method generates the trajectory that accurately follows the given end-effector path, while avoiding obstacles such as the pack of A4 paper and the table.

This shows the visualization results, where red lines are the given paths, and blue lines are computed end-effector paths. Numbers within parenthesis indicate the pose error. (a) and (b) are to trace the square, and (c) and (d) are to trace the "S". We must avoid the table across all scenes, and additionally consider the blue box in (c) and (d). Results of EIGS, (a) and (c), show noticeable pose errors in several parts. Our methods shown in (b) and (d) accurately follow the given path with smaller numerical errors.

This shows the visualized results of writing "hello" w/o obstacles for different methods. Red lines are the given paths, and blue lines are computed end-effector paths. Numbers within parenthesis indicate the pose error. (a) and (c) show relatively high pose errors, while (b) Stampede and (d) ours show accurately following the given path.

Contents

Paper: PDF (3.21MB)
Source Code: GitHub, ZIP


Bibtex: 
@inproceedings{kang2020torm,
	title={{TORM}: Fast and Accurate Trajectory Optimization of Redundant Manipulator given an End-Effector Path},
	author={Kang, Mincheul and Shin, Heechan and Kim, Donghyuk and Yoon, Sung-eui},
	booktitle={IROS},
	year={2020},
	organization={IEEE}
}