Fuzzy critic for robotic motion planning by genetic algorithm in hierarchical intelligent control
Takanori Shibata, Toshio Fukuda, Kazuo Tanie · 2005
In this paper, a new strategy for motion planning in robotics is proposed. When robots performs some tasks, they work along with the motion plans. The plane should be effective. The proposed strategy applies a genetic algorithm (GA) to optimize the plans. To evaluate the planned motion, the strategy applies fuzzy logic as 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. Depending on the goals of the tasks, human operators can easily transfer 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.