A Straight Moving Path Planner for Mobile Robots in Static Environments Using Cellular Automata

Planning a collision free path for a robot in an environment with lots of obstacles is one of the most important issues in robotics. Path planning using robots draws the most attention when the planning environment is dangerous or inaccessible for human. In this paper a cellular automata based algorithm called SMPP (Straight Moving Path Planner) is presented for robot path planning problem. The advantage of this approach is that it prefers straight moves rather than zigzag steps. It is shown that how SMPP can help us finding a reasonable optimum path from the start point of the robot to the goal position in presence of obstacles. The proposed algorithm is then compared to the previous works done on the basis of cellular automata and the results are presented to validate the approach.

[1]  Shirong Liu,et al.  Path Planning Based on Ant Colony Algorithm and Distributed Local Navigation for Multi-Robot Systems , 2006, 2006 International Conference on Mechatronics and Automation.

[2]  Yangsheng Xu,et al.  PSO-Based Time-Optimal Trajectory Planning for Space Robot with Dynamic Constraints , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.

[3]  Q. P. Ha,et al.  INITIALIZATION OF ROBOTIC FORMATIONS USING DISCRETE PARTICLE SWARM OPTIMIZATION , 2007 .

[4]  Sepideh Adabi,et al.  A Cellular Automata Based Algorithm for Path Planning in Multi-Agent Systems with A Common Goal , 2008 .

[5]  Hamid Haj Seyyed Javadi,et al.  Using Particle Swarm Optimization for Robot Path Planning in Dynamic Environments with Moving Obstacles and Target , 2009, 2009 Third UKSim European Symposium on Computer Modeling and Simulation.

[6]  C. Lucas,et al.  A New Architecture to Execute CAs-Based Path-Planning Algorithm in Mobile Robots , 2006, 2006 IEEE International Conference on Mechatronics.

[7]  Qing Li,et al.  Optimum Path Planning for Mobile Robots Based on a Hybrid Genetic Algorithm , 2006, 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06).

[8]  Qidan Zhu,et al.  Robot Path Planning Based on Artificial Potential Field Approach with Simulated Annealing , 2006, Sixth International Conference on Intelligent Systems Design and Applications.

[9]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[10]  F.M. Marchese.  A reactive planner for mobile robots with generic shapes and kinematics on variable terrains , 2005, ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005..

[11]  M. Castro,et al.  An Algorithm for Robot Path Planning with Cellular Automata , 2000, ACRI.