A Thesis on Loco-Manipulation with Non-impulsive Contact-Implicit Planning in a Slithering Robot

TL;DR

This paper introduces an optimization-based approach for loco-manipulation in snake robots, leveraging non-impulsive contact path planning to enhance object manipulation through locomotion, demonstrated via simulations and experiments.

Contribution

It presents a novel mathematical framework and optimization method for non-impulsive contact path planning in snake robot loco-manipulation.

Findings

Effective contact path planning demonstrated in high-fidelity simulations

Successful real-world experiments validate the approach

Enhanced object manipulation through locomotion in snake robots

Abstract

Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulation problem based on non-impulsive implicit contact path planning for our snake robot COBRA. This thesis presents the mathematical framework and show high-fidelity simulation results and experiments to demonstrate the effectiveness of our approach.