Multi-robot connective collaboration toward collective obstacle field traversal
Haodi Hu, Xingjue Liao, Wuhao Du, Feifei Qian

TL;DR
This study demonstrates how two connectable simple robots can collaboratively traverse complex obstacle fields by adjusting their connection length, inspired by fire ants, and uses energy landscape modeling to optimize their collective mobility.
Contribution
It introduces a minimalistic two-robot system with adjustable connection length, revealing how mechanical coupling enhances obstacle negotiation and providing a model for adaptive collective locomotion.
Findings
Optimal connection length improves traversability.
Connection length significantly affects collective mobility.
Energy landscape modeling explains the underlying mechanism.
Abstract
Environments with large terrain height variations present great challenges for legged robot locomotion. Drawing inspiration from fire ants' collective assembly behavior, we study strategies that can enable two ``connectable'' robots to collectively navigate over bumpy terrains with height variations larger than robot leg length. Each robot was designed to be extremely simple, with a cubical body and one rotary motor actuating four vertical peg legs that move in pairs. Two or more robots could physically connect to one another to enhance collective mobility. We performed locomotion experiments with a two-robot group, across an obstacle field filled with uniformly-distributed semi-spherical ``boulders''. Experimentally-measured robot speed suggested that the connection length between the robots has a significant effect on collective mobility: connection length C in [0.86, 0.9] robot unit…
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Robotic Path Planning Algorithms · Robot Manipulation and Learning
