ANALYSIS AND IMPLEMENTATION OF MULTI-ROBOT EXPLORATION TECHNIQUES

Abstract

Robots need autonomous navigation and map exploration in order to go autonomously across and record previously uncharted territory. These tasks need quick decision-making, careful avoidance of obstacles, and effective path planning. In the first approach, homogeneous robots use their limited communication skills to autonomously choose their jobs and trajectories in a cooperative navigation environment. Robots minimise repeated exploration by using artificial pheromones to indicate explored places through communication and stigmergy, which are two ways of conveying information. Motion control of the robots is handled via fuzzy controllers. Through a variety of simulated situations, the efficacy of the proposed online path planner is assessed, revealing notable gains in task execution and navigation. The second approach presents a swarm-based control algorithm that is suggested for preserving a formation that guarantees close-quarters communication while venturing into uncharted territory. The program uses a frontier search technique to find attractive exploration regions and basic swarm rules to preserve formation, both of which are inspired by natural systems. Important metrics like swarm formation statistics and coverage performance show that our approach outperforms both conventional swarming techniques and current map coverage strategies in terms of efficacy.The third approach suggests using a sweeping algorithm to minimize overlapping regions and maximize coverage. This approach takes into account two scenarios: a communication-free situation and a communication-filled one with robots. The effectiveness of this strategy is demonstrated by extensive simulations with the Webots multi-robot simulator, where variables like the size of the area, the number of robots, and obstacles are varied. All strategies give strong foundations for multi-robot systems to effectively navigate, explore, and cover new terrain, and they each contribute significantly to the field of autonomous robotic exploration.