Narrow-Path, Dynamic Walking Using Integrated Posture Manipulation and Thrust Vectoring

TL;DR

This paper presents a novel control framework for a quadrupedal robot that combines posture manipulation and thrust vectoring to enable stable, dynamic walking through narrow pathways like pipes and slacklines, validated via simulations.

Contribution

It introduces an integrated control approach using polynomial approximation and collocation methods for optimal thruster commands in narrow-path walking.

Findings

Successful simulation of narrow-path walking with the Husky robot.

Effective modeling of the robot's dynamics using HROM.

Validated control strategy enhances stability during dynamic traversal.

Abstract

This research concentrates on enhancing the navigational capabilities of Northeastern Universitys Husky, a multi-modal quadrupedal robot, that can integrate posture manipulation and thrust vectoring, to traverse through narrow pathways such as walking over pipes and slacklining. The Husky is outfitted with thrusters designed to stabilize its body during dynamic walking over these narrow paths. The project involves modeling the robot using the HROM (Husky Reduced Order Model) and developing an optimal control framework. This framework is based on polynomial approximation of the HROM and a collocation approach to derive optimal thruster commands necessary for achieving dynamic walking on narrow paths. The effectiveness of the modeling and control design approach is validated through simulations conducted using Matlab.