An analysis of RelaxedIK : an optimization-based framework for generating accurate and feasible robot arm motions
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An analysis of RelaxedIK : an optimization-based framework for generating accurate and feasible robot arm motions Daniel Rakita1
· Bilge Mutlu1 · Michael Gleicher1
Received: 7 December 2018 / Accepted: 9 June 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract We present a real-time motion-synthesis method for robot manipulators, called RelaxedIK, that is able to not only accurately match end-effector pose goals as done by traditional IK solvers, but also create smooth, feasible motions that avoid jointspace 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. We also empirically evaluate how our solver performs with different optimization solvers, gradient calculation methods, and choice of loss function in the objective function. Keywords Inverse kinematics · Real-time motion planning · Collision avoidance
1 Introduction To perform real-time tasks, a robotic manipulator must calculate how its joint angles should change at each update in order to meet kinematic goals rooted in its environment. For instance, a robot providing home-care assistance by spoonfeeding an individual in a wheelchair would have to make This is one of the several papers published in Autonomous Robots comprising the Special Issue on Robotics: Science and Systems. This research was supported by the National Science Foundation under Award 1208632 and the University of Wisconsin–Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation.
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Daniel Rakita [email protected] Bilge Mutlu [email protected] Michael Gleicher [email protected]
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Department of Computer Sciences, University of Wisconsin, Madison, USA
real-time motion decisions to simultaneously meet many objectives, including the robot manipulator approaching the patient’s head with smooth, self-collision-free motions, continuously updating the position and orientation of the spoon to account for potential head or torso motion, and keeping the spoon level such that the food does not spill. In this problem, a
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