The use of Obstacle Motion Tracking for Car-like Mobile Robots Collision Avoidance in Dynamic Urban Environments

4 ETHZ, IRIS, ASL - Tannenstrasse, 3 - CH 8092 - Zurich, Switzerland. Abstract: One of the most challenging tasks for mobile robots is to track mobile obstacles that surround them. This task is especially difficult in outdoor environments where a great variety of obstacles may induce the robot to take erroneous decisions. The mobile robot needs as much information as possible concerning the obstacle positions and speeds (direction and magnitude) in order to plan evasive maneuvers that avoid collisions. Unfortunately, obstacles close to robot's sensors frequently cause blind zones behind them where other obstacles could be hidden. In this situation, the robot may lose vital information about these obstructed obstacles that could avoid future collisions. In order to overcome this problem an obstacle tracking module based only on 2D laser scan data was developed. Its main parts consist of obstacle detection, obstacle classification, and obstacle tracking. Different methods were evaluated for extracting data from the laser data. Geometrical feature extraction itself, i.e. lines and corners, was not found sufficient. Therefore, a motion detection module using scan matching was developed. The research was mostly conducted using a MatLab simulator that reproduces a simple 2D urban-like environment with parked and moving cars, buses, trucks, and people, buildings, streets, and trees. Aiming to adjust and validate the algorithms, some samplings of real data were carried out. The tests proved the applicability of the algorithms in real urban environments and in a near future they will be used in obstacle avoidance procedures onboard a real car-like robot.

[1]  Xiong Chen,et al.  Path planning approach based on probabilistic roadmap for sensor based car-like robot in unknown environments , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[2]  John Stein,et al.  An optimal tracking filter for processing sensor data of imprecisely determined origin in surveillance systems , 1971, CDC 1971.

[3]  Charles E. Thorpe,et al.  Simultaneous localization and mapping with detection and tracking of moving objects , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[4]  Satoshi Kagami,et al.  Continuous Curvature Trajectory Generation with Obstacle Avoidance for Car-Like Robots , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[5]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.

[6]  M. Yamamoto,et al.  Garage parking planning and control of car-like robot using a real time optimization method , 2005, (ISATP 2005). The 6th IEEE International Symposium on Assembly and Task Planning: From Nano to Macro Assembly and Manufacturing, 2005..

[7]  Ronald Sea.  An efficient suboptimal decision procedure for associating sensor data with stored tracks in real-time surveillance systems , 1971, CDC 1971.

[8]  K. Shadan,et al.  Available online: , 2012 .

[9]  Wolfram Burgard,et al.  Tracking multiple moving targets with a mobile robot using particle filters and statistical data association , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[10]  Hung-Ching Lu,et al.  The implementation of fuzzy-based path planning for car-like mobile robot , 2005, 2005 International Conference on MEMS,NANO and Smart Systems.

[11]  T. Martinez-Marfn.  Learning Optimal Motion Planning for Car-like Vehicles , 2005 .

[12]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[13]  Marina Oliver.  SPARC , 2001, Definitions.

[14]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[15]  Christian Laugier,et al.  An autonomous car-like robot navigating safely among pedestrians , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[16]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[17]  Robert W. Sittler,et al.  An Optimal Data Association Problem in Surveillance Theory , 1964, IEEE Transactions on Military Electronics.

[18]  Q.J. Duan,et al.  An immunity algorithm for path planning of the autonomous mobile robot , 2004, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[19]  Robert A. MacLachlan,et al.  Tracking Moving Objects From a Moving Vehicle Using a Laser Scanner , 2006 .

[20]  Roland Siegwart,et al.  Motion Planning for Car-Like Vehicles in Dynamic Urban Scenarios , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  B. Vazquez-Gonzalez,et al.  Complexity and path planning for a car-like robot , 2005, 2005 2nd International Conference on Electrical and Electronics Engineering.

[22]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[23]  Wolfram Burgard,et al.  Learning motion patterns of persons for mobile service robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[24]  Wolfram Burgard,et al.  Using EM to learn motion behaviors of persons with mobile robots , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[25]  R. Siegwart,et al.  Autonomous Driving in Structured and Unstructured Environments , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[26]  Chan-Hong Chao,et al.  Omni-directional vision-based parallel-parking control design for car-like mobile robot , 2005, IEEE International Conference on Mechatronics, 2005. ICM '05..

[27]  Jan-Olof Eklundh,et al.  Detecting and tracking moving objects from a mobile platform using a laser range scanner , 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).

[28]  Roland Siegwart,et al.  Introduction to Autonomous Mobile Robots , 2004 .

[29]  Li Zhang,et al.  Geometric feature based 2 1/2 D map building and planning with laser, sonar and tactile sensors , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[30]  Kudret Demirli,et al.  Autonomous parallel parking of a car-like mobile robot by a neuro-fuzzy behavior-based controller , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[31]  Tomás Martínez-Marín.  Learning Optimal Motion Planning for Car-like Vehicles , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[32]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[33]  Peter Liu,et al.  Fuzzy gain scheduling for parallel parking a car-like robot , 2005, IEEE Transactions on Control Systems Technology.

[34]  L. Trassoudaine,et al.  EKF and particle filter track-to-track fusion: a quantitative comparison from radar/lidar obstacle tracks , 2005, 2005 7th International Conference on Information Fusion.

[35]  Erwin Prassler,et al.  Statistical recognition of motion patterns , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[36]  Björn Jensen.  Motion tracking for human-robot interaction , 2004 .

[37]  T D Gillespie,et al.  Fundamentals of Vehicle Dynamics , 1992 .

[38]  Chang Boon Low,et al.  Robust path following of car-like WMR in the presence of skidding effects , 2005, IEEE International Conference on Mechatronics, 2005. ICM '05..