Online Discovery of Locomotion Modes for Wheel-Legged Hybrid Robots: a Transferability-based Approach

Abstract : Wheel-legged hybrid robots promise to combine the e ciency of wheeled robots with the versatility of legged robots: they are able to roll on simple terrains, to dynamically adapt their posture and even to walk on uneven grounds. Al- though di erent locomotion modes of such robots have been studied, a pivotal question remains: how to automatically adapt the locomotion mode when the environment changes? We here propose that the robot autonomously discov- ers its locomotion mode using optimization-based learning. To that aim, we introduce a new algorithm that relies on a forward model and a stochastic multi-objective optimization. Three objectives are optimized: (1) the average displacement speed, (2) the expended energy and (3) the transferability score, which re ects how well the behavior of the robot is in agreement with the pre- dictions of the forward model. This transferability function is approximated by conducting 20 experiments of one second on the real robot during the op- timization. In the three investigated situations ( at ground, grass-like terrain, tunnel-like environment), our method found e cient controllers for forward locomotion in 1 to 2 minutes: the robot used its wheels on the at ground, it walked on the grass-like terrain and moved with a lowered body in the tunnel- like environment.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [9 references]  Display  Hide  Download
Contributor : Sylvain Koos <>
Submitted on : Wednesday, October 19, 2011 - 6:38:26 PM
Last modification on : Thursday, March 21, 2019 - 2:42:23 PM
Document(s) archivé(s) le : Thursday, November 15, 2012 - 10:05:40 AM


Files produced by the author(s)


  • HAL Id : hal-00633930, version 1


Sylvain Koos, Jean-Baptiste Mouret. Online Discovery of Locomotion Modes for Wheel-Legged Hybrid Robots: a Transferability-based Approach. 14th International Conference on Climbing and Walking Robots, Sep 2011, Paris, France. pp.1. ⟨hal-00633930⟩



Record views


Files downloads