Nature-Inspired Optimization Algorithms for Path Planning and Fuzzy Tracking Control of Mobile Robots

Abstract

This paper proposes two applications of nature-inspired optimization algorithms (NIOAs) to solve a path planning problem and the optimal tuning of Proportional-Integral (PI)-fuzzy controllers as tracking controllers for nonholonomic wheeled mobile robots in static environments. Two optimization problems are solved by NIOAs and included first in an off-line path planning approach that generates the reference trajectory and next a cost-effective PI-fuzzy tracking controller tuning approach. The NIOAs applied to solve both optimization problems are Particle Swarm Optimization, Gravitational Search Algorithm, Charged System Search Algorithm, Grey Wolf Optimizer and Whale Optimization Algorithm.