RelaxedIK: Real-time Synthesis of Accurate and Feasible Robot Arm Motion

Rakita, D., B. Mutlu, and M. Gleicher. “RelaxedIK: Real-Time Synthesis of Accurate and Feasible Robot Arm Motion”. Robotics: Science and Systems, 2018, pp. 26-30.


We present a real-time motion-synthesis method for robot manipulators, called RelaxedIK, that is able to not only ac- curately match end-effector pose goals as done by traditional IK solvers, but also create smooth, feasible motions that avoid joint- space discontinuities, self-collisions, and kinematic singularities. To achieve these objectives on-the-fly, we cast the standard IK formulation as a weighted-sum non-linear optimization problem, such that motion goals in addition to end-effector pose matching can be encoded as terms in the sum. We present a normalization procedure such that our method is able to effectively make trade- offs to simultaneously reconcile many, and potentially competing, objectives. Using these trade-offs, our formulation allows features to be relaxed when in conflict with other features deemed more important at a given time. We compare performance against a state-of-the-art IK solver and a real-time motion- planning approach in several geometric and real-world tasks on seven robot platforms ranging from 5-DOF to 8-DOF. We show that our method achieves motions that effectively follow position and orientation end-effector goals without sacrificing motion feasibility, resulting in more successful execution of tasks compared to the baseline approaches.

DOI: 10.15607/rss.2018.xiv.043


	doi = {10.15607/rss.2018.xiv.043},
	url = {},
	year = 2018,
	month = {jun},
	publisher = {Robotics: Science and Systems Foundation},
	author = {Daniel Rakita and Bilge Mutlu and Michael Gleicher},
	title = {{RelaxedIK}: Real-time Synthesis of Accurate and Feasible Robot Arm Motion},
	booktitle = {Robotics: Science and Systems {XIV}}