Collision-Inclusive Manipulation Planning for Occluded Object Grasping via Compliant Robot Motions

TL;DR

This paper introduces a collision-inclusive planning framework that leverages compliant robot motions and environmental constraints to improve occluded object grasping under uncertainties, demonstrated through real-world experiments.

Contribution

It presents a novel collision-inclusive planning approach that exploits environmental interactions and compliant motions to handle occlusions and uncertainties in manipulation tasks.

Findings

Effective in reducing physical and perception uncertainties.

Successfully addresses occluded grasping problems with no initial feasible grasp.

Demonstrated on both single-arm and dual-arm robotic setups.

Abstract

Robotic manipulation research has investigated contact-rich problems and strategies that require robots to intentionally collide with their environment, to accomplish tasks that cannot be handled by traditional collision-free solutions. By enabling compliant robot motions, collisions between the robot and its environment become more tolerable and can thus be exploited, but more physical uncertainties are introduced. To address contact-rich problems such as occluded object grasping while handling the involved uncertainties, we propose a collision-inclusive planning framework that can transition the robot to a desired task configuration via roughly modeled collisions absorbed by Cartesian impedance control. By strategically exploiting the environmental constraints and exploring inside a manipulation funnel formed by task repetitions, our framework can effectively reduce physical and perception uncertainties. With real-world evaluations on both single-arm and dual-arm setups, we show that our framework is able to efficiently address various realistic occluded grasping problems where a feasible grasp does not initially exist.