Hybrid Insect-Inspired Multi-Robot Coverage in Complex Environments

Abstract

Abstract. Coordination is one of the most challenging research issues in distributed multi-robot systems (MRS), aiming to improve performance, energy consumption, robustness and reliability of a robotic system in accomplishing complex tasks. Social insect-inspired coordination techniques achieve these goals by applying simple but effective heuristics from which elegant solutions emerge. In our previous research, we demonstrated the effectiveness of a hybrid ant-and-bee inspired approach, HybaCo, designed to provide coordinated multi-robot solutions to area coverage problems in simple environments. In this paper, we extend this work and illustrate the effectiveness of our hybrid ant-and-bee inspired approach (HybaCo) in complex environments with static obstacles. We evaluate both the ant-inspired (StiCo) and bee-inspired (BeePCo) approaches separately, and then compare them according to a number of performance criteria using a high-level simulator. Experimental results indicate that HybaCo improves the area coverage uniformly in complex environments as well as simple environments.

A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms

“…The BCO is another swarm intelligence based on a bioinspired machine learning algorithm similar to ACO and PSO. Caliskanelli et al [248] introduced a pheromone signaling algorithm based on BCO [249] for multi-robot coverage as well as a hybrid BCO-ACO pheromone signaling technique to solve the loss of communication network problems in multiple robots [250]. Firefly algorithm (FA) is a nature-inspired optimization algorithm [251] that has been widely used in coverage and exploration of the unknown area, especially mine disarming tasks [252,253].…”

Development of an Attention Mechanism for Task-Adaptive Heterogeneous Robot Teaming

“…Similarly, in the realm of traffic management, including the regulation of traffic flows and the scheduling of public transport systems [4][5][6], deploying a multitude of specialized robots to form a cohesive team proves to be more cost effective than relying on a single robot endowed with multiple capabilities for the entire operation. Additionally, when addressing tasks that require comprehensive area coverage and the navigation of complex search missions [7][8][9], HMRS demonstrates its capacity to mitigate task intricacies by distributing responsibilities among the team members.…”