A Fast Evolutionary Algorithm for Robot Path Planning

Robot path planning is a NP problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this paper, we devise an evolutionary algorithm to solve the robot path planning problems based on some new genetic operators.The problems in algorithm design mainly considered are how to select the evolutionary operators, how to avoid the solutions falling into the local optimal and how to enhance the efficiency of the evolution process and so on. The new algorithm has been carried on the operation to the test examples. The experiment results indicated that the new algorithm is efficiency for solving the robot path planning problems and the best path usually can be found.

[1]  Sanjiv Singh,et al.  An efficient on-line path planner for outdoor mobile robots , 2000, Robotics Auton. Syst..

[2]  Eyal Zussman,et al.  A planning approach for robot-assisted multiple-bent profile handling , 1994 .

[3]  Shigeru Aomura,et al.  Optimized bending sequences of sheet metal bending by robot , 2002 .

[4]  José Alí Moreno,et al.  Heuristic Algorithm for Robot Path Planning Based on Real Space Renormalization , 2000, IBERAMIA-SBIA.

[5]  Donald B. Gennery,et al.  Traversability Analysis and Path Planning for a Planetary Rover , 1999, Auton. Robots.

[6]  Zbigniew Michalewicz,et al.  Adaptive evolutionary planner/navigator for mobile robots , 1997, IEEE Trans. Evol. Comput..

[7]  Homayoun Seraji,et al.  Vision-based terrain characterization and traversability assessment , 2001, J. Field Robotics.

[8]  Satyandra K. Gupta.  SHEET METAL BENDING OPERATION PLANNING : USING VIRTUAL NODE GENERATION TO IMPROVE SEARCH EFFICIENCY , 1999 .

[9]  Jean-Claude Latombe,et al.  Numerical potential field techniques for robot path planning , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[10]  Tiejun Li,et al.  The Ant Algorithm for Solving Robot Path Planning Problem , 2005, Third International Conference on Information Technology and Applications (ICITA'05).

[11]  Hui Li,et al.  A fast evolutionary algorithm for combinatorial optimization problems , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[12]  Maria Joao Rendas,et al.  Definition of Exploratory Trajectories in Robotics Using Genetic Algorithms , 1997 .

[13]  Dirk Cattrysse,et al.  Methods for the sequencing of sheet metal bending operations , 1999 .

[14]  M. Inui,et al.  Fast bending sequence planning for progressive press-working , 1999, Proceedings of the 1999 IEEE International Symposium on Assembly and Task Planning (ISATP'99) (Cat. No.99TH8470).

[15]  Aranya Walairacht,et al.  Multi-component genetic algorithm for generating best bending sequence and tool selection in sheet metal parts , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[16]  Ulrich Nehmzow,et al.  Robot navigation in the real world: : Experiments with Manchester's FortyTwo in unmodified, large environments , 2000, Robotics Auton. Syst..

[17]  Zbigniew Michalewicz,et al.  Inver-over Operator for the TSP , 1998, PPSN.

[18]  G. Swaminathan.  Robot Motion Planning , 2006 .