کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
390316 | 661241 | 2008 | 11 صفحه PDF | دانلود رایگان |
The paper develops a hybrid intelligent approach to path planning for high mobility robots operating in rough environments. Path planning consists of characterization of the environment using a fuzzy logic framework, and a two-stage genetic algorithm planner. A global planner determines the path that optimizes a combination of terrain roughness and path curvature. A local planner uses sensory information, and in case of detection of previously unknown and unaccounted for obstacles, performs an on-line replanning to get around the newly discovered obstacle. Fuzzy adaptation of the genetic operators is achieved by adjusting the probabilities of the operators based on a diversity measure of the paths population and traversability measure of the paths. Path planning for an articulated rover in a rugged Mars terrain is presented to demonstrate the effectiveness of the proposed path planner.
Journal: Fuzzy Sets and Systems - Volume 159, Issue 21, 1 November 2008, Pages 2927-2937