Abstract
Optimal path planning is an important feature of autonomous mobile robot guidance and control during outdoor missions. Offline path planning of any manoeuvres in cluttered environments depends on pre-mission knowledge about topographical features of the landscape between the robot's start position and goal position. A topographical landscape consists of regions with different traversal costs, and it is not necessarily binary in nature. For certain extraterrestrial or cross-country missions, where a lack of vehicular resources has to be handled, there is a strong need to calculate an optimal path according to a given optimization criterion. The paper presents a genetic approach to the problem. Evolutionary computation is used to carry out path optimization.
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