Mobile Robot Path Planning in a 2-Dimentional Mesh

Authors: Doraid Dalalah

Abstract:

A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Keywords: Mobile robot, Path Planning, Mesh, Potential field.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075250

References:

[1] Ashiru I. and Czarnecki C. "Optimal Motion Planning for Mobile Robots Using Genetic Algorithms," IEEE International Automation and Control Conference, pp. 297-300, 1995
[2] Brink Ten, C. and Popovic D. "A Collision-Space Approach to Trajectory Planning of Coordinated Robots," 1995 IFAC World Congress, San Francisco, Vol. A, pp. 205-209.
[3] Bugmann G., Taylor G., and Michael, J. "Route Finding by Neural Nets, Application of Modern Heuristic Methods," University of Plymouth PL4 8AA, United Kingdom, pp 1-11, 1994.
[4] Chen C. and Hwang. K. "Practical Path Planning Among Movable Obstacles," 1991 IEEE International Conference on Robotics and Automation, pp. 444-449.
[5] Christoph M., McNeil S., and Thorpe C. "Side Collision Warning Systems for Transit Buses," IV 2000- IEEE Intelligent Vehicle Symposium.
[6] Clifford, A. and Gregory, M. "A Real-Time Robot Arm Collision Avoidance System", IEEE Transactions on Robotics and Automation, Vol. 8, No. 2, pp 149-160, 1992.
[7] Devin B. and Mason M. 2000. "External Trajectories for Bounded Velocity Differential Drive Robots," (ICRA '00) IEEE International Conference on Robotics and Automation.
[8] Glasuis R. Komoda A., and Geilen S. "Neural Network Dynamics for Path Planning and Obstacle Avoidance," Department of the medical physics and biophysics, University of Nejimegen, The Netherlands, pp 1-14, 1994.
[9] Gordon A., John P.H. and Rossmiller K. "Predicting Trajectories Using Recurrent Neural Networks," ANNIE'91 Artificial Neural Networks in Engineering conference, pp 365-370.
[10] Mark. M. and Erdmann M. "Manipulation of Pose Distributions," 2000 Tech Report, Computer Science Department, Carnegie Mellon University, CMU-CS-00-111.
[11] Matthew M., Pai D., Rus D., Taylor L.R., and Erdmann M. "A Mobile Manipulator," (ICRA '99) IEEE International Conference on Robotics and Automation.
[12] Nagata S. Sekiguchi M. and Asakawa K. "Mobile Robot Control by a Structured Hierarchical Neural Network," IEEE Contr. Syst. Mag. pp 69-76, 1990.
[13] Peterson K. "Path Planning in Analogue Valued Obstacle Array Using Hierarchical Dynamic Programming and Neural Networks," ANNIE'91 Artificial Neural networks in Engineering Conference, pp 789-794.
[14] Roach W. and Michael N. "Coordinating the Motions of Robot Arm in a Common Workspace," IEEE Journal, Vol. RA-3, No. 5, pp 30-37, 1987.
[15] Simon D. "Neural Networks-based Robot Trajectory Generation," TRW Systems Integration Group, San Bernardino, CA 92402, pp 540-545, 1993.
[16] Simmons R., Fernandez J., Goodwin R., Koenig S., and O'Sullivan J. "Xavier: An Autonomous Mobile Robot on the Web," IEEE Robotics and Automation Magazine, 1999.
[17] Popa, A. S. Popa, M. Silea, I. "Mobile robot navigation with obstacle avoidance capability," 2008-IEEE 13th Power Electronics and Motion Control Conference, pp 1225-1232.
[18] Núñez P., Vázquez-Martín R., J. C. del Toro, A. Bandera, F. Sandoval. Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation. Robotics and Autonomous Systems archive, Vol. 56(3), pp247-264, 2008.