Study on Path Planning Method for Mobile Robot Based on Fruit Fly Optimization Algorithm

Abstract

A path planning method based on fruit fly optimization algorithm was proposed. An optimization algorithm by the foraging process of fruit fly was presented, and the mathematical model of fitness function was established. The algorithm steps employing the LabVIEW platform were achieved. The experiments of path planning were carried out. The experimental results show that the optimization algorithm can achieve the path planning and avoidance of mobile robot, and thus to verify the feasibility.

Optimal Path Planning for an Autonomous Mobile Robot Using Dragonfly Algorithm

“…In recent years, many researchers have implemented many nature / bio-inspired metaheuristic optimization methods for solving mobile robot navigation problems. Nature/bio-inspired algorithms such as Genetic Algorithm (GA) [1,2], Ant Colony Optimization (ACO) [3], Cuckoo Search (CS) [4], Invasive Weed Optimization (IWO) [5], Particle Swarm Optimization (PSO) [6], Bacteria Forging Algorithm (BFA) [7], Bats Algorithm [8], Simulated Annealing (SA) [9], Grey Wolf Optimizer [10], Bees Colony [11], Cockroach Swarm Algorithm [12], Frog Leaping Algorithm [13], Firefly Algorithm [14], Fruit Fly Algorithm [15] and many other algorithms have been implemented for solving navigational strategies in autonomous mobile robots. Few vision based solutions have also been proposed to solve the path planning problems [16][17][18].…”