Bi-Level Belief Space Search for Compliant Part Mating Under Uncertainty

TL;DR

This paper introduces BILBA, a model-based planner that computes compliant motions for low-clearance part mating, leveraging contact to reduce uncertainty and improve autonomous assembly success.

Contribution

The paper presents a novel bi-level belief space search method that integrates contact schedule derivation with compliant motion planning for assembly tasks.

Findings

BILBA efficiently computes robust assembly plans in simulation.

BILBA successfully performs real-world peg-in-hole insertion tasks.

The approach reduces uncertainty and improves success in low-clearance assembly.

Abstract

The problem of mating two parts with low clearance remains difficult for autonomous robots. We present bi-level belief assembly (BILBA), a model-based planner that computes a sequence of compliant motions which can leverage contact with the environment to reduce uncertainty and perform challenging assembly tasks with low clearance. Our approach is based on first deriving candidate contact schedules from the structure of the configuration space obstacle of the parts and then finding compliant motions that achieve the desired contacts. We demonstrate that BILBA can efficiently compute robust plans on multiple simulated tasks as well as a real robot rectangular peg-in-hole insertion task.