Autonomous multi-robot navigation and mapping for swarm applications

Abstract

Swarm exploration is a significant area of robotics research that has practical applications in search and rescue, environmental monitoring, and surveillance. It presents a challenge since a group of robots must cooperate and explore an unknown or partially known environment efficiently. To address this challenge, a recent project proposed a novel approach to swarm exploration. The approach involved equipping a group of robots with LIDAR sensors and using exploration algorithms and Extended Kalman filter to guide their movements while communicating with each other to share information. The system also employed mapping and map merging algorithms to conduct swarm exploration. The approach employed was effective in the efficient exploration of the surroundings and rapid accumulation of a substantial amount of data. The exploration technique showcased in the project involved the utilization of only 2 robots to serve as a representation of a swarm of robots. However, the system can accommodate additional robots to form a massive swarm system provided that the computational capacity can handle it. The system holds promise for mapping and monitoring the environment.