Trajectory Optimization for Quadruped Mobile Manipulators that Carry Heavy Payload

TL;DR

This paper introduces a simplified, payload-aware trajectory optimization method for quadruped mobile manipulators, enabling efficient motion planning while carrying heavy payloads, validated through simulations and experiments.

Contribution

It presents a novel payload-aware trajectory optimization framework that accounts for payload dynamics, improving manipulability and efficiency in heavy payload scenarios.

Findings

Reduced leg outstretching during heavy payload manipulation

Enhanced manipulability in kinematically demanding motions

Validated effectiveness through simulations and real-world experiments

Abstract

This paper presents a simplified model-based trajectory optimization (TO) formulation for motion planning on quadruped mobile manipulators that carry heavy payload of known mass. The proposed payload-aware formulation simultaneously plans locomotion, payload manipulation and considers both robot and payload model dynamics while remaining computationally efficient. At the presence of heavy payload, the approach exhibits reduced leg outstretching (thus increased manipulability) in kinematically demanding motions due to the contribution of payload manipulation in the optimization. The framework's computational efficiency and performance is validated through a number of simulation and experimental studies with the bi-manual quadruped CENTAURO robot carrying on its arms a payload that exceeds 15 % of its mass and traversing non-flat terrain.