Meta-Heuristic Optimization Techniques and Its Applications in Robotics

Abstract

Optimization techniques are search methods, where the goal is to find a solution to an optimization problem, such that a given quantity is optimized, possibly subject to a set of constraints. Modern optimization techniques start to demonstrate their power in dealing with hard optimization problems in robotics and automation such as manufacturing cells formation, robot motion planning, worker scheduling, cell assignment, vehicle routing problem, assembly line balancing, shortest sequence planning, sensor placement, unmanned-aerial vehicles (UAV) communication relaying and multirobot coordination to name just a few. By example, in particle, path planning it is a difficult task in robotics, as well as construct and control a robot. The main propose of path planning is find a specific route in order to reach the target destination.

A review of metaheuristics in robotics

“…Relying only on little heuristic information that is accumulated from previous generation from time to time, metaheuristic works on a candidate solution by evaluating how fit it is respective to the ultimate objective. As an example found in [20] the optimal set of robot behaviours is yet to be found in simulating a soccer goalie robot. Any possible combination of behaviour set can be tested in turn and a quality score is assigned to it.…”