E-puck motion control using multi-objective particle swarm optimization
Keywords:Motion control, Orientation control, Multi-Objective Particle Swarm Optimization (MPSO) algorithm, Virtual robot experimentation platform software, Infra-Red sensors
AbstractThis article describes the velocity-based motion and orientation control method for differential-driven two-wheeled E-puck Robot (DDER) using Multi-Objective Particle Swarm Optimization (MPSO) algorithm in the Virtual Robot Experimentation Platform (V-REP) software environment. The wheel velocities data and Infra-Red (IR) sensors reading make the multi-objective fitness functions for MPSO. We use front, left, and right IR sensors reading and right wheel velocity data to design the first fitness function for MPSO. Similarly, the front, left, and right IR sensors reading, and left wheel velocity data have been taken for making the second fitness function for MPSO. The multi-objective fitness functions of MPSO minimize the motion and orientation of the DDER during navigation. Due to the minimization of motion and orientation, the DDER covers less distance to reach the goal and also takes less time. The Two-Dimensional (2D) and Three-Dimensional (3D) navigation results of the DDER among the scattered obstacles have been presented in the V-REP software environment. Also, the comparative analysis with previously developed Invasive Weed Optimization (IWO) algorithm has been performed to show the effectiveness and efficiency of the proposed MPSO algorithm.
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