Review of Soft Computing Techniques used in Robotics Application

In this Review paper we discussed, how soft computing to the field of behavior based robotics. It discusses the role of fuzzy, neuro-fuzzy and genetic algorithm rule-based systems for behavior architectures and adaptation. It reviews a number of applications of soft computing techniques to autonomous robot navigation and control.

[1]  Frank Hoffmann,et al.  An OVerview on Soft Computing in Behavior Based Robotics , 2003, IFSA.

[2]  Alessandro Saffiotti Fuzzy logic in Autonomous Robot Navigation - a case study , 1997 .

[3]  Piero P. Bonissone,et al.  Hybrid soft computing systems: industrial and commercial applications , 1999, Proc. IEEE.

[4]  Edward Tunstel,et al.  Soft computing-based design and control for mobile robot path tracking , 1999, Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375).

[5]  Gerardo Beni,et al.  From Swarm Intelligence to Swarm Robotics , 2004, Swarm Robotics.

[6]  Frank Hoffmann Soft Computing Techniques for the Design of Mobile Robot Behaviors , 2000, Inf. Sci..

[7]  Miomir Vukobratović,et al.  Genetic Algorithms in Robotics , 2003 .

[8]  Diego Andina,et al.  Swarm intelligence and its applications in swarm robotics , 2007 .

[9]  Dongbing Gu,et al.  GA-based learning in behaviour based robotics , 2003, Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694).