Multi-objective path planning for space exploration robot based on chaos immune particle swarm optimization algorithm

Authors:
Wei Hao;Shiyin Qin
Affiliations:
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Year:
2011

Citing 5
Cited 0

Real-time robot path planning based on a modified pulse-coupled neural network model

IEEE Transactions on Neural Networks
The Research and Simulation on the Path Planning Based on the Improved Grid Model

AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 02
An efficient dynamic system for real-time robot-path planning

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robot Path Integration in Manufacturing Processes: Genetic Algorithm Versus Ant Colony Optimization

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Autonomous robot navigation using adaptive potential fields

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Multi-objective path planning for mobile robot in complex environments is a challenging issue in space exploration. In order to improve the efficiency and quality of the multi-objective path planning, a chaos immune particle swarm optimization (CIPSO) algorithm is proposed in this paper, which combines chaos and PSO with immune network theory so as to enhance the searching speed of path planning for mobile robot and insure the safety of space exploration. Simulation results show that the CIPSO has well performance for path planning and obstacle avoidance.