Demonstrations of Robot Competitions

COMPETITIONS Robot Competitions : What Did We Learn ?

Robot Learning from Failed Demonstrations

Robot learning from demonstration (RLfD) seeks to enable lay users to encode desired robot behaviors as autonomous controllers. Current work uses a human’s demonstration of the target task to initialize the robot’s policy, and then improves its performance either through practice (with a known reward function), or additional human interaction. In this article, we focus on the initialization ste...

A Retrospective of the AAAI Robot Competitions

by the authors at the Thirteenth National Conference on Artificial Intelligence (AAAI-96). The piece begins with a short history of the competition, then discusses the technical challenges and the political and cultural issues associated with bringing it off every year. We also cover the science and engineering involved with the robot tasks and the educational and commercial aspects of the comp...

Research relevance of mobile robot competitions

A number of international competitions for mobile robots have been created and conducted over the last 20 years. This article discusses three of the arguably most prominent event series. We highlight scope, rules, robot designs and robot evolution over the years for the Micromouse Contest, AAAI Mobile Robot Competition and RoboCup Robot Soccer and discuss their contributions to mobile robot res...

Shaping of Robot Behaviors by Demonstrations

This paper is concerned with the learning of robots behaviors in real environments. To face the constraints imposed by both physical and human spaces, it insists on the interest of a shaping process relying on learning by demonstrations. A mechanism for learning by demonstration is brie y described based on robot vision. The paper then discusses several general points related to learning by dem...