Morphology Independent Learning in Modular Robots

David Johan Christensen, Mirko Bordignon, Ulrik Pagh Schultz, Danish Shaikh, Kasper Stoy

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


Hand-coding locomotion controllers for modular robots is difficult due to their polymorphic nature. Instead, we propose to use a simple and distributed reinforcement learning strategy. ATRON modules with identical controllers can be assembled in any configuration. To optimize the robot’s locomotion speed its modules independently and in parallel adjust their behavior based on a single global reward signal. In simulation, we study the learning strategy’s performance on different robot configurations. On the physical platform, we perform learning experiments with ATRON robots learning to move as fast as possible. We conclude that the learning strategy is effective and may be a practical approach to design gaits.
Original languageEnglish
Title of host publicationDistributed Autonomous Robotic Systems 8
EditorsHajime Asama, Haruhisa Kurokawa, Jun Ota, Kosuke Sekiyama
Publication date2009
ISBN (Print)978-3-642-00643-2
Publication statusPublished - 2009
Externally publishedYes
Event9. International Symposium on Distributed Autonomous Robotic Systems : DARS 2008 - Tsukuba, Japan
Duration: 1 Jan 2009 → …
Conference number: 9


Conference9. International Symposium on Distributed Autonomous Robotic Systems : DARS 2008
CityTsukuba, Japan
Period01/01/2009 → …


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