Real-Time Visual Tracking and Identification for a Team of Homogeneous Humanoid Robots

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)

Abstract

The use of a team of humanoid robots to collaborate in completing a task is an increasingly important field of research. One of the challenges in achieving collaboration, is mutual identification and tracking of the robots. This work presents a real-time vision-based approach to the detection and tracking of robots of known appearance, based on the images captured by a stationary robot. A Histogram of Oriented Gradients descriptor is used to detect the robots and the robot headings are estimated by a multiclass classifier. The tracked robots report their own heading estimate from magnetometer readings. For tracking, a cost function based on position and heading is applied to each of the tracklets, and a globally optimal labeling of the detected robots is found using the Hungarian algorithm. The complete identification and tracking system was tested using two igus\(^\circledR \) Humanoid Open Platform robots on a soccer field. We expect that a similar system can be used with other humanoid robots, such as Nao and DARwIn-OP.

Notes

Acknowledgment

This work was partially funded by grant BE 2556/10 of the German Research Foundation (DFG). The authors would like to thank Philipp Allgeuer for help in editing the article and assisting in performing experimental tests.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Autonomous Intelligent Systems, Computer Science Institute VIUniversity of BonnBonnGermany

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