Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed.

[1]  Rudolf Tanner,et al.  People Detection and Tracking with TOF Sensor , 2008, 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance.

[2]  Yoko Watanabe,et al.  Simultaneous visual target tracking and navigation in a GPS-denied environment , 2009, 2009 International Conference on Advanced Robotics.

[3]  P. Mahalanobis.  On the generalized distance in statistics , 1936 .

[4]  Erwin Prassler,et al.  Fast and robust tracking of multiple moving objects with a laser range finder , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[5]  Xiaofeng Meng,et al.  Modeling and Predicting Future Trajectories of Moving Objects in a Constrained Network , 2006, 7th International Conference on Mobile Data Management (MDM'06).

[6]  Hans-Dieter Burkhard,et al.  Multi Robot Object Tracking and Self Localization Using Visual Percept Relations , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Kazunori Ohno,et al.  Development of 3D laser scanner for measuring uniform and dense 3D shapes of static objects in dynamic environment. , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.

[8]  Vivek Srivastava,et al.  Security System and Surveillance Using Real Time Object Tracking and Multiple Cameras , 2011 .

[9]  David Austin,et al.  Laser Motion Detection and Hypothesis Tracking from a Mobile Platforms , 2004 .

[10]  Thierry Fraichard,et al.  Motion prediction for moving objects: a statistical approach , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  Kazuhiko Takahashi,et al.  Moving-object tracking with multi-laser range sensors for mobile robot navigation , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[12]  Tucker R. Balch,et al.  Distributed sensor fusion for object position estimation by multi-robot systems , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[13]  Avinash C. Kak,et al.  Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing , 1998, IEEE Trans. Robotics Autom..

[14]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization, Mapping and Moving Object Tracking , 2007, Int. J. Robotics Res..

[15]  Manuel Mazo,et al.  Multi-robot tracking of a moving object using directional sensors , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[16]  Hyeran Byun,et al.  Human tracking and silhouette extraction for human–robot interaction systems , 2008, Pattern Analysis and Applications.

[17]  Jianwei Zhang,et al.  Multimodal People Tracking and Trajectory Prediction based on Learned Generalized Motion Patterns , 2006, 2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

[18]  Sebastian Thrun,et al.  Decentralized Sensor Fusion with Distributed Particle Filters , 2002, UAI.

[19]  William Whittaker,et al.  Conditional particle filters for simultaneous mobile robot localization and people-tracking , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[20]  Olivier Michel,et al.  Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004, ArXiv.

[21]  Dongbing Gu,et al.  Cooperative Target Tracking Control of Multiple Robots , 2012, IEEE Transactions on Industrial Electronics.

[22]  John B. Moore,et al.  Improved Extended Kalman Filter Design for Passive Tracking , 1979 .

[23]  Peter Axelsson,et al.  Processing of laser scanner data-algorithms and applications , 1999 .

[24]  Antonio Barrientos,et al.  Human Detection from a Mobile Robot Using Fusion of Laser and Vision Information , 2013, Sensors.

[25]  Young Min Kim,et al.  Design and calibration of a multi-view TOF sensor fusion system , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[26]  Zixing Cai,et al.  Real-time Detection of Dynamic Obstacle Using Laser Radar , 2008, 2008 The 9th International Conference for Young Computer Scientists.

[27]  Ovidio Salvetti,et al.  Object tracking in a stereo and infrared vision system , 2007 .

[28]  Antonio Fernández-Caballero,et al.  On motion detection through a multi-layer neural network architecture , 2003, Neural Networks.

[29]  M. Shah,et al.  Moving Object Detection and Tracking in Forward Looking Infra-Red Aerial Imagery , 2011 .

[30]  Klaus Dietmayer,et al.  3D vehicle detection using a laser scanner and a video camera , 2008 .

[31]  Jun Zhang,et al.  TRAFFIC VIDEO-BASED MOVING VEHICLE DETECTION AND TRACKING IN THE COMPLEX ENVIRONMENT , 2009, Cybern. Syst..

[32]  Jangmyung Lee,et al.  The Tracking of a Moving Object by a Mobile Robot Following the Object’s Sound , 2013, J. Intell. Robotic Syst..

[33]  Olivier Michel,et al.  Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004 .

[34]  Agnes Swadzba,et al.  Tracking objects in 6D for reconstructing static scenes , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[35]  Andreas Birk,et al.  Roboguard, A Teleoperated Mobile Security Robot , 2001 .

[36]  Bernhard Nebel,et al.  Cooperative sensing in dynamic environments , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[37]  Bruce A. MacDonald,et al.  A Real-Time Method to Detect and Track Moving Objects (DATMO) from Unmanned Aerial Vehicles (UAVs) Using a Single Camera , 2012, Remote. Sens..

[38]  Derek D. Lichti,et al.  Static Calibration and Analysis of the Velodyne HDL-64E S2 for High Accuracy Mobile Scanning , 2010, Remote. Sens..

[39]  Filiberto Pla,et al.  Segmenting Traffic Scenes from Grey Level and Motion Information , 2014, Pattern Analysis & Applications.

[40]  Thierry Fraichard,et al.  Motion estimation from range images in dynamic outdoor scenes , 2010, 2010 IEEE International Conference on Robotics and Automation.

[41]  Duc Phu Chau,et al.  Robust Mobile Object Tracking based on Multiple Feature Similarity and Trajectory Filtering , 2011, VISAPP.

[42]  Neil Davey,et al.  The recognition and analysis of animate objects using neural networks and active contour models , 2002, Neurocomputing.

[43]  Kostas J. Kyriakopoulos,et al.  Multi-robot multiple hypothesis tracking for pedestrian tracking , 2011, 2011 19th Mediterranean Conference on Control & Automation (MED).