Simultaneous Localization and Mapping with Cost Effective Sensors

摘要

This paper explores the fascinating field of swarm robotics, where multiple robots collaborate to achieve tasks in a decentralized and distributed manner. The focus here is on the exploratory behavior of swarm robotics, including aggregation, dispersion, and collective movement. The system is represented as an occupancy grid problem and heuristic-based algorithms are used as optimized solutions. The decentralized approach within those methods makes them easier to idealize with current swarm robotic applications. Furthermore, these algorithms can be seam-lessly integrated with other current frontier-based exploration techniques to enhance robot cooperation. All these proposed methods have been tested in different simulation environments, which mimic real world scenarios.