Development of a new minimum avoidance system for a behavior-based mobile robot

A new fuzzy logic algorithm is developed for mobile robot navigation in local environments. A Pioneer robot perceives its environment through an array of eight sonar sensors and self positioning-localization sensors. While the fuzzy logic body of the algorithm performs the main tasks of obstacle avoidance and target seeking, an actual-virtual target switching strategy resolves the problem of limit cycles in any type of dead-ends encountered on the way to the target. This is an advantage beyond pure fuzzy logic approach and common virtual target techniques. In this work, multiple traps may have any shape or arrangement from barriers forming simple corners and U-shape dead-ends to loops, maze, snail shape, and other complicated shapes. Robot trajectories are demonstrated by simulation work and compared with results from other related methods to prove the robustness of this method.

[1]  Hichem Maaref,et al.  Sensor-based navigation of a mobile robot in an indoor environment , 2002, Robotics Auton. Syst..

[2]  Meng Wang,et al.  Fuzzy logic-based real-time robot navigation in unknown environment with dead ends , 2008, Robotics Auton. Syst..

[3]  Jean J. Saade,et al.  An efficient data-driven fuzzy approach to the motion planning problem of a mobile robot , 2003, Fuzzy Sets Syst..

[4]  Simon X. Yang,et al.  A fuzzy logic approach to reactive navigation of behavior-based mobile robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[5]  Tucker R. Balch,et al.  Avoiding the past: a simple but effective strategy for reactive navigation , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[6]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[7]  Robin R. Murphy,et al.  Introduction to AI Robotics , 2000 .

[8]  A. Kelarev Graph algebras and automata , 2003 .

[9]  Kostas J. Kyriakopoulos,et al.  Backstepping for nonsmooth systems , 2003, Autom..

[10]  K. Madhava Krishna,et al.  Perception and remembrance of the environment during real-time navigation of a mobile robot , 2001, Robotics Auton. Syst..

[11]  Emmanuel G. Collins,et al.  The virtual wall approach to limit cycle avoidance for unmanned ground vehicles , 2008, Robotics Auton. Syst..

[12]  Weiliang Xu,et al.  Sensor-based fuzzy reactive navigation of a mobile robot through local target switching , 1999, IEEE Trans. Syst. Man Cybern. Part C.

[13]  Mauro Massari,et al.  Autonomous Navigation System for Planetary Exploration Rover based on Artificial Potential Fields , 2004 .

[14]  Bakir Lacevic,et al.  A 3-level autonomous mobile robot navigation system designed by using reasoning/search approaches , 2006, Robotics Auton. Syst..

[15]  Jacky Baltes,et al.  Fuzzy Potential Energy for a Map Approach to Robot navigation , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[16]  George K. I. Mann,et al.  Mobile robot navigation using motor schema and fuzzy context dependent behavior modulation , 2008, Appl. Soft Comput..

[17]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[18]  Emmanuel G. Collins,et al.  Robot navigation in very cluttered environments by preference-based fuzzy behaviors , 2008, Robotics Auton. Syst..

[19]  Xiaoyu Yang,et al.  A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[20]  Meng Wang,et al.  Fuzzy logic based robot path planning in unknown environment , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[21]  Dilip Kumar Pratihar,et al.  Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches , 2006, Fuzzy Sets Syst..

[22]  Eric Monacelli,et al.  A fuzzy-based reactive controller for a non-holonomic mobile robot , 2004, Robotics Auton. Syst..

[23]  Yoram Koren,et al.  Potential field methods and their inherent limitations for mobile robot navigation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.