Vision-servoed localization and behavior-based planning for an autonomous quadruped legged robot

摘要

Planning actions for real robots in dynamic and uncertain environments is a challenging problem. Using 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 a system integrating perception, planning, and action for the Sony quadruped legged robots. We consider the robotic soccer task, as Sony provided the robots to us specifically for the RoboCup robotic soccer competitions. The quadruped legged robots are fully autonomous and thus must have onboard vision, localization and agent behavior. We briefly present our perception algorithm that does automated color classification and tracks colored blobs in real time. We then briefly introduce our Sensor Resetting Localization (SRL) algorithm which is an extension of Monte Carlo Localization. Vision and localization provide the state input for ac...