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The design of LEO: A 2D bipedal walking robot for online autonomous Reinforcement Learning

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4 Author(s)
Erik Schuitema ; Delft Bio-Robotics Lab, Faculty 3ME, Delft University of Technology, Mekelweg 2, 2628CD, The Netherlands ; Martijn Wisse ; Thijs Ramakers ; Pieter Jonker

Real robots demonstrating online Reinforcement Learning (RL) to learn new tasks are hard to find. The specific properties and limitations of real robots have a large impact on their suitability for RL experiments. In this work, we derive the main hardware and software requirements that a RL robot should fulfill, and present our biped robot LEO that was specifically designed to meet these requirements. We verify its aptitude in autonomous walking experiments using a pre-programmed controller. Although there is room for improvement in the design, the robot was able to walk, fall and stand up without human intervention for 8 hours, during which it made over 43; 000 footsteps.

Published in:

Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on

Date of Conference:

18-22 Oct. 2010