A Dynamic Inertial Weight Strategy in Micro PSO for Swarm Robots

Abstract

A relatively new area of research and development is Swarm Robotics. It is a part of the swarm intelligence field. In the proposed paper, we shall use swarm robotics in the field of defense and security, particularly for the problem of counter-improvised explosive device (IED) operations. The biggest problem in this regard is to physically detect the IEDs. We propose the use of a swarm of autonomous robots which shall be moving through the search space to collectively detect IEDs in a relatively lesser span of time with greater reliability. Since the robots are autonomous, there will not be any human contact involved, thus distancing humans from any potential IEDs or hazardous environments. The robot hardware shall be robust and able to traverse different kinds of terrains or even water bodies. A major problem of decision making for autonomous robots is localization of the robots towards the origin. Localization deals with finding its Cartesian coordinates and direction in the given coordinate system. For effective autonomous navigation of a robot, finding the position of the robot is essential at every point of time. Particle swarm optimization (PSO) is a useful method for population based global search. The proposed algorithm is an extension of micro-particle swarm optimization (µPSO) for Simultaneous Localization and Mapping. The effectiveness of this method is estimated by comparing its results with the traditional PSO and µPSO.