Bellotto, Nicola and Hu, Huosheng (2009) Multisensor-based human detection and tracking for mobile service robots. IEEE Transactions on Systems, Man and Cybernetics, Part B, 39 (1). pp. 167-181. ISSN 1083-4419
Full text URL: http://dx.doi.org/10.1109/TSMCB.2008.2004050
The one of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In the present paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based legs detection using the on-board LRF. The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to be very discriminative also in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera and the information is fused to the legs position using a sequential implementation of Unscented Kalman Filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms.
Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.
|Keywords:||People Tracking, Legs Detection, Sensor Fusion, Unscented Kalman Filter, Service Robotics.|
|Subjects:||H Engineering > H670 Robotics and Cybernetics|
|Divisions:||College of Science > School of Computer Science|
|Deposited By:||Nicola Bellotto|
|Deposited On:||12 Dec 2009 20:37|
|Last Modified:||18 Nov 2013 14:14|
Repository Staff Only: item control page