ICRA 2011 Paper Abstract


Paper TuA203.2

Elfring, Jos (Eindhoven University of Technology), van de Molengraft, Marinus Jacobus Gerardus (University of Technology Eindhoven), Janssen, Rob Josephus Maria (Eindhoven University of Technology), Steinbuch, Maarten (Eindhoven University of Technology)

Two Level World Modeling for Cooperating Robots Using a Multiple Hypotheses Filter

Scheduled for presentation during the Regular Sessions "Autonomous Navigation II" (TuA203), Tuesday, May 10, 2011, 10:20−10:35, Room 3D

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 29, 2020

Keywords Autonomous Agents, Autonomous Navigation, Networked Robots


Robots increasingly operate in dynamic environments and in order to operate safely, reliable world models are indispensable. A world model is the robotís view of the world and contains information about obstacle locations and velocities. A two level algorithm is proposed. It is of particular use for teams of cooperating robots and the algorithm is based on a multiple hypotheses filter. Each robot features a low level world model with a fast update rate which can be used for obstacle avoidance. The local world models are combined to one global view of the world that is shared between all robots and can be used for the implementation of team strategies. Labeling and tracking is added to the multiple hypotheses filter in order to reduce the sensitivity to track loss in case of temporary occlusions of objects or false measurements. The algorithm was extensively tested during the 2010 RoboCup Middle Size League world championships in Singapore, the results of which are presented.



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