Affiliation:
1. University of Pennsylvania, Philadelphia, USA
2. University of California, Los Angeles, USA
Abstract
Robot soccer has become an effective benchmarking problem for robotics research as it requires many aspects of robotics including perception, self localization, motion planning and distributed coordination to work in uncertain and adversarial environments. Especially with humanoid robots that lack inherent stability, a capable and robust motion controller is crucial for generating walking and kicking motions without losing balance. In this paper, we describe the details of a motion controller to control a team of humanoid soccer robots, which consists of a hierarchy of controllers with different time frames and abstraction levels. A low level controller governs the real time control of each joint angle, either using target joint angles or target endpoint transforms. A mid-level controller handles bipedal locomotion and balancing of the robot. A high level controller decides the long term behavior of the robot, and finally the team level controller coordinates the behavior of a group of robots by means of asynchronous communication between the robots. The suggested motion system has been successfully used by many humanoid robot teams at the RoboCup international robot soccer competitions, which has awarded us five successful championships in a row.
Subject
Artificial Intelligence,Computer Science Applications,Software
Cited by
1 articles.
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1. Height Varying Humanoid Robot Walking through Model Predictive Control;2019 Latin American Robotics Symposium (LARS), 2019 Brazilian Symposium on Robotics (SBR) and 2019 Workshop on Robotics in Education (WRE);2019-10