<p>In this paper, we present a task space-based local motion planner that incorporates collision avoidance and constraints on end-effector motion during the execution of a task. &nbsp;Our key technical contribution is the development of a novel kinematic state evolution model of the robot where the collision avoidance is encoded as a complementarity constraint. We show that the kinematic state evolution with collision avoidance can be represented as a Linear Complementarity Problem (LCP). Using the LCP model along with Screw Linear Interpolation (ScLERP) in $SE(3)$, we show that it may be possible to compute a path between two given task space poses by directly moving from the start to the goal pose, even if there are potential collisions with obstacles. Using ScLERP as a interpolation method to trace path in taskspace allowed us to implicitly satisfy some desired task constraints. Furher complementarity constraints based obstacle avoidance scheme, allows the robot to use the obstacle in th environment as a guide to reach to the desired goal pose. Scalability of the planner is demonstrated with simulation results&nbsp;and experiments using a physical robot. We present simulation and experimental results with both collision avoidance and task constraints to show the efficacy of our approach.&nbsp;</p>

Task Space Planning With Complementarity Constraint-Based Obstacle Avoidance

Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2021/volume/85369

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