同型ヒューマノイドロボット群のリアルタイム視覚追跡と識別
Real-Time Visual Tracking and Identification for a Team of Homogeneous Humanoid Robots
固定カメラの画像からHOG記述子と多クラス分類器でロボットを検出し、ハンガリアン法で位置と向きに基づく最適な識別・追跡を行うシステムを構築、2台のヒューマノイドで実証した。
著者: Hafez Farazi, Sven Behnke
分類: cs.RO, cs.CV
原文アブストラクト
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 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
