Mobile Robot Trajectory Analysis with the Help of Vision System

We present a vision-based motion analysis method for single and multiple mobile robots which allows quantifying the robot’s behaviour. The method defines how often and for how much each of the robots turn and move straight. The motion analysis relies on the robot trajectories acquired online or offline by an external camera and the algorithm is based on iteratively performed a linear regression to detect straight and curved paths for each robot. The method is experimentally validated with the indoor mobile robotic system. Potential applications include remote robot inspection, rescue robotics and multi-robotic system coordination.

[1]  Pratap Tokekar,et al.  Multi-target visual tracking with aerial robots , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Friedrich M. Wahl,et al.  Camera-based observation of obstacle motions to derive statistical data for mobile robot motion planning , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[3]  Nicolas Jouandeau,et al.  A Survey and Analysis of Multi-Robot Coordination , 2013 .

[4]  Frank E. Schneider,et al.  Methods and experiments for hazardous area activities using a multi-robot system , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[5]  Kevin D. Jones,et al.  Vision-based tracking and motion estimation for moving targets using small UAVs , 2006, 2006 American Control Conference.

[6]  F. Miyazaki,et al.  Visual servoing for non-holonomic mobile robots , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[7]  W. Eric L. Grimson,et al.  Learning Patterns of Activity Using Real-Time Tracking , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Nikolaus Correll,et al.  SwisTrack - a flexible open source tracking software for multi-agent systems , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Feng-Li Lian,et al.  Analysis of Formation Control and Communication Pattern in Multi-Robot Systems , 2006, 2006 SICE-ICASE International Joint Conference.

[10]  Alcherio Martinoli,et al.  A quantitative method for comparing trajectories of mobile robots using point distribution models , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Tao Liu,et al.  Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera , 2015, IEEE Transactions on Control Systems Technology.

[12]  Luca Maria Gambardella,et al.  SWARM-BOT: pattern formation in a swarm of self-assembling mobile robots , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[13]  Jee-Hwan Ryu,et al.  Teleoperation of multi-robot and multi-property systems , 2008, 2008 6th IEEE International Conference on Industrial Informatics.

[14]  Nicola Basilico,et al.  Multirobot Exploration of Communication-Restricted Environments: A Survey , 2017, IEEE Intelligent Systems.

[15]  Jee-Hwan Ryu,et al.  A user study of command strategies for mobile robot teleoperation , 2009, Intell. Serv. Robotics.