Cooperative exploration strategy for micro-aerial vehicles fleet

Abstract

In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots data exchange. The novelty comes from the exchange of the frontiers points instead of maps, which allows to reduce computation and data amount within the network. The proposed system has been implemented and tested under ROS using the Gazebo simulator. The results demonstrate that the proposed navigation strategy efficiently spreads robots over the environment for a faster exploration.

Aplicaciones practicas de los sistemas multi-UAV y enjambres aéreos

“…En un entorno de interiores, en (Mahdoui et al, 2017) se plantea un algoritmo de exploración con un grupo de microdrones. Dicho algoritmo es distribuido, y considera que cada dron está equipado con una cámara RGB-D mediante la cual van generando un mapa.…”

Information Distribution in Multi-Robot Systems: Utility-Based Evaluation Model

“…Cieslewski et al [3] address the problem of decentralized data distribution for the simultaneous localization and mapping problem and tackle it by reducing the amount of exchanged data. Mahdoui et al [4] present a decentralized solution to an exploration problem and reduce communication load by operating on meta information instead of the primary data. Such solutions are very specific and focus on one particular type of information for a particular mission; it is not clear how to generalize such an approach to other information types or how it would perform in other applications.…”

Communicating Multi-UAV System for Cooperative SLAM-based Exploration

“…Important computation requirements are used for this later approach. Taking into account the advantage of solution optimality from centralized approach, and the advantage of mission reliability and adaptability from decentralized approach; a leader -based approach has been proposed in our previous work [22]. The fleet is subdivided into subgroups -called clusters -such that one robot in each subgroup is responsible for targets assignment.…”

“…is the minimum distance from UAV i 's pose to the candidate target j. The proposed utility function is inspired from [17] and it has been presented in our previous work [22]. In the case of a single UAV, the utility function tends to choose the closest target with the maximum of information gain.…”