Probabilistic fuzzy controller based robotics path decision theory

This paper aims to comprise the new ideas for the efficient implementation to autonomous mobile robot navigation over the complex environment in presence of static obstacles.

The fuzzy decision via probability and its distribution is applied for the generating objective function subject to the robotics path and obstacle avoidance. The present objective function is formed to achieve high level of significance for the real-time obstacle avoidance and the efficiency.

The proposed controller makes a robot take its decision effectively in complex environment in a feasible time. In comparison with other AI approaches the proposed controller reflects that the proposed method outperforms in terms of optimal path and quality of solution. The experimental and simulation results are nearly same.

It has been tested in a complex crowded environment to find shorter path than existed approaches. For the validation, the experimental and simulation result using Matlab Software (R2008) has provided at the end of the paper.