Multi-humanoid world modeling in Standard Platform robot soccer

In the RoboCup Standard Platform League (SPL), the robot platform is the same humanoid NAO robot for all the competing teams. The NAO humanoids are fully autonomous with two onboard directional cameras, computation, multi-joint body, and wireless communication among them. One of the main opportunities of having a team of robots is to have robots share information and coordinate. We address the problem of each humanoid building a model of the world in real-time, given a combination of its own limited sensing, known models of actuation, and the communicated information from its teammates. Such multi-humanoid world modeling is challenging due to the biped motion, the limited perception, and the tight coupling between behaviors, sensing, localization, and communication. We describe the real-world opportunities, constraints and limitations imposed by the NAO humanoid robots. We contribute a modeling approach that differentiates among the motion model of different objects, in terms of their dynamics, namely the static landmarks (e.g., goal posts, lines, corners), the passive moving ball, and the controlled moving robots, both teammates and adversaries. We present experimental results with the NAO humanoid robots to illustrate the impact of our multi-humanoid world modeling approach. The challenges and approaches we present are relevant to the general problem of assessing and sharing information among multiple humanoid robots acting in a world with multiple types of objects.

[1]  Manuela M. Veloso,et al.  Efficient physics-based planning: sampling search via non-deterministic tactics and skills , 2009, AAMAS.

[2]  Hans Utz,et al.  Sharing Belief in Teams of Heterogeneous Robots , 2004, RoboCup.

[3]  Brett Browning,et al.  STP: Skills, tactics, and plays for multi-robot control in adversarial environments , 2005 .

[4]  Manuela M. Veloso,et al.  Prioritized Multihypothesis Tracking by a Robot with Limited Sensing , 2009, EURASIP J. Adv. Signal Process..

[5]  Manuela M. Veloso,et al.  Effective Multi-Model Motion Tracking using Action Models , 2009, Int. J. Robotics Res..

[6]  Peter Stone,et al.  Negative information and line observations for Monte Carlo localization , 2008, 2008 IEEE International Conference on Robotics and Automation.

[7]  Xiaoping Chen,et al.  Simplified Walking: A New Way to Generate Flexible Biped Patterns , 2009 .

[8]  Dieter Fox,et al.  Map-Based Multiple Model Tracking of a Moving Object , 2004, RoboCup.

[9]  Manuela M. Veloso,et al.  A real-time world model for multi-robot teams with high-latency communication , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[10]  Minoru Asada,et al.  Cooperative behavior based on a subjective map with shared information in a dynamic environment , 2005, Adv. Robotics.

[11]  Manuela M. Veloso,et al.  Sensor resetting localization for poorly modelled mobile robots , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).