Gait Generation Balancing Joint Load and Mobility for Legged Modular Robots with Easily Detachable Joints

TL;DR

This paper introduces an optimization framework for modular legged robots that balances joint load and mobility, ensuring durability and performance across various terrains.

Contribution

It presents a novel multi-objective optimization method using NSGA-III to generate gait motions that balance load reduction and mobility in modular robots.

Findings

Successfully reduces joint load during locomotion

Maintains mobility and stability across diverse terrains

Validated through simulations and physical experiments

Abstract

While modular robots offer versatility, excessive joint torque during locomotion poses a significant risk of mechanical failure, especially for detachable joints. To address this, we propose an optimization framework using the NSGA-III algorithm. Unlike conventional approaches that prioritize mobility alone, our method derives Pareto optimal solutions to minimize joint load while maintaining necessary locomotion speed and stability. Simulations and physical experiments demonstrate that our approach successfully generates gait motions for diverse environments, such as slopes and steps, ensuring structural integrity without compromising overall mobility.