Multi-modal people tracking for an awareness behavior of an interactive tour-guide robot

We propose a system for enhancing a human-robot interaction system. The goal is to embrace surrounding persons into a conversation with the robot by means of establishing or keeping eye contact. For this, a simple and hence computationally efficient people tracking algorithm has been developed, which in itself is an enhancement of existing approaches. As the foundation of our approach we use a vanilla Kalman filter that explicitly models the velocity in the state space, while the observations are transformed into a unified global coordinate system. We evaluate different integration strategies for multiple sensor cues. Furthermore, we extend an algorithm for group detection to be able to recognize individuals.

[1]  B. Schiele,et al.  Fast and Robust Face Finding via Local Context , 2003 .

[2]  Donald Reid.  An algorithm for tracking multiple targets , 1978 .

[3]  Yuichiro Yoshikawa,et al.  Responsive Robot Gaze to Interaction Partner , 2006, Robotics: Science and Systems.

[4]  Huosheng Hu,et al.  Vision and Laser Data Fusion for Tracking People with a Mobile Robot , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.

[5]  Robert E. Mahony,et al.  Visual servoing of an under-actuated dynamic rigid-body system: an image-based approach , 2002, IEEE Trans. Robotics Autom..

[6]  Warren E. Dixon,et al.  Navigation function based visual servo control , 2005, Proceedings of the 2005, American Control Conference, 2005..

[7]  Takeo Kanade,et al.  Inertial-aided KLT feature tracking for a moving camera , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  A G Pipe,et al.  An adaptive gaze stabilization controller inspired by the vestibulo-ocular reflex , 2008, Bioinspiration & biomimetics.

[9]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

[10]  Rainer Lienhart,et al.  An extended set of Haar-like features for rapid object detection , 2002, Proceedings. International Conference on Image Processing.

[11]  Peter I. Corke,et al.  A new partitioned approach to image-based visual servo control , 2001, IEEE Trans. Robotics Autom..

[12]  Kai Oliver Arras,et al.  People tracking in RGB-D data with on-line boosted target models , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Peter I. Corke,et al.  A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..

[14]  Rainer Stiefelhagen,et al.  Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics , 2008, EURASIP J. Image Video Process..

[15]  Wook Bahn,et al.  Vision system for mobile robots for tracking moving targets, based on robot motion and stereo vision information , 2011, 2011 IEEE/SICE International Symposium on System Integration (SII).

[16]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[17]  Daijin Kim,et al.  Robust Real-Time Face Detection Using Face Certainty Map , 2007, ICB.

[18]  Yaakov Bar-Shalom,et al.  Sonar tracking of multiple targets using joint probabilistic data association , 1983 .

[19]  Giulio Sandini,et al.  Visuo-inertial stabilization in space-variant binocular systems , 2000, Robotics Auton. Syst..

[20]  Wolfram Burgard,et al.  People Tracking with Mobile Robots Using Sample-Based Joint Probabilistic Data Association Filters , 2003, Int. J. Robotics Res..

[21]  A. Ito,et al.  Why robots need body for mind communication - an attempt of eye-contact between human and robot , 2004, RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication (IEEE Catalog No.04TH8759).

[22]  Huosheng Hu,et al.  Multisensor-Based Human Detection and Tracking for Mobile Service Robots , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[23]  Wolfram Burgard,et al.  Multi-model Hypothesis Group Tracking and Group Size Estimation , 2010, Int. J. Soc. Robotics.

[24]  J. Quinn,et al.  Accelerometer based line-of-sight stabilization approach for pointing and tracking systems , 1993, Proceedings of IEEE International Conference on Control and Applications.

[25]  Kwangsoo Kim,et al.  A novel line of sight control system for a robot vision tracking system, using vision feedback and motion-disturbance feedforward compensation , 2012, Robotica (Cambridge. Print).

[26]  Wolfram Burgard,et al.  Using Boosted Features for the Detection of People in 2D Range Data , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[27]  Erik Schaffernicht,et al.  Are You Still Following Me? , 2007, EMCR.