Vision-Servoed Localization and Behavior-Based Planning for an Autonomous Quadruped Legged Robot

Planning for real robots to act in dynamic and uncertain environments is a challenging problem. A complete model of the world is not viable and an integration of deliberation and behavior-based reactive planning is most appropriate for goal achievement and uncertainty handling. This paper reports on our successful development of the integration of perception, planning, and action for the Sony quadruped legged robots. We address the particular robotic soccer task, as Sony provided the robots to us specifically for the RoboCup robotic soccer competitions. The quadruped legged robots are fully autonomous, so must have onboard vision, localization and agent behavior. We brie y present our perception algorithm that does automated color classi cation and tracks colored blobs in real time. We then brie y introduce our Sensor Resetting Localization (SRL) algorithm which is an extension of Monte Carlo Localization. SRL is robust to movement modelling errors and to limited computational power. ...

• Type: Conference
• Year: 2000
• Where: AIPS
• Authors: Manuela M. Veloso, Elly Winner, Scott Lenser, James Bruce, Tucker R. Balch
• Keywords: AIPS 2000, Artificial Intelligence, Quadruped Legged Robots, Real Robots, Sensor Resetting Localization