Cooperative Transportation by Humanoid Robots – Solving Piano Movers' Problem

Article type: Research Article

Authors: Iba, Hitoshi | Tohge, Takahiro | Inoue, Yutaka

Affiliations: Graduate School of Frontier Sciences, University of Tokyo, Japan. iba@iba.k.u-tokyo.ac.jp, tohge@iba.k.u-tokyo.ac.jp, inoue@iba.k.u-tokyo.ac.jp

Abstract: Recent developments in humanoid robots seem very promising for the sake of achieving higher-level tasks, such as those usually done by humans. Cooperative behavior allows multiple robots to tackle a task easily and effectively. In this paper, we try to solve a cooperative transportation task, i.e., a piano movers' problem, using two humanoid robots. We use Q-learning for the purpose of real-world adaptation. More precisely, the two robots gain environmental information through their respective monocular cameras, and learn to cooperatively navigate a narrow L-shaped aisle. We empirically show how the robustness of the acquired cooperative behavior for the test cases differed from the training L-shaped aisle.

Keywords: Humanoid Robot, Q-learning, Classifier System, Evolutionary Computation, Evolutionary Robotics

DOI: 10.3233/HIS-2004-13-407

Journal: International Journal of Hybrid Intelligent Systems, vol. 1, no. 3-4, pp. 189-201, 2004