Robotic Motion Planning by Genetic Algorithm with Fuzzy Critic

摘要

This paper proposes a new strategy for motion planning in robotics. When robots performs some tasks, they work along with motion plans. The plans should be effective for the robots. The proposed strategy applies a Genetic Algorithm (GA) to optimize the motion planning. To evaluate the planned motion, the strategy also applies fuzzy logic to a fitness function. The fitness function is referred to as Fuzzy Critic. The Fuzzy Critic evaluates populations in the GA with respect to multiple factors, while traditional fitness functions do with respect to only one factor. Depending on the goals of the tasks, human operators can easily determine inference rules in the Fuzzy Critic because of the fuzzy logic. In this paper, the strategy determines a path for a mobile robot which moves from a starting point to a goal point while avoiding obstacles in a work space and picking up loads on the way. Simulations illustrate the effectiveness of the proposed strategy.