Adapting to sensing and actuation variations in multi-robot coverage
Carregando...
Data
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Federal de Minas Gerais
Descrição
Tipo
Artigo de periódico
Título alternativo
Primeiro orientador
Membros da banca
Resumo
This article considers the problem of multi-robot coverage control, where a group of robots has to spread out over an environment to provide coverage. We propose a new approach for a group of robots carrying out this collaborative task that will adapt online to performance variations among the robots. Two types of performance variations are considered: variations in sensing performance (e.g. differences in sensor types, calibration, or noise), and variations in actuation (e.g. differences in terrain, vehicle types, or lossy motors). The robots have no prior knowledge of the relative strengths of their performance compared to the others in the team. We present an algorithm that learns the relative performance variations among the robots online, in a distributed fashion, and automatically compensates by assigning the weak robots a smaller portion of the environment and the strong robots a larger portion. Using a Lyapunov-type proof, we show that the robots converge to a locally optimal coverage configuration. The algorithm is also demonstrated in both MATLAB simulations and experiments with Pololu m3pi ground robots.
Abstract
Assunto
Robôs - Sistemas de controle, Robótica
Palavras-chave
method of using adaptive weightings to adjust for individual variations in performance within multi-robot coverage control, modify the Voronoi boundaries between neighboring robots, which adjusts a robot’s cell size relative to its neighbors, method incorporates performance error into the decentralized algorithm while maintaining stability and performance
Citação
Departamento
Curso
Endereço externo
https://journals.sagepub.com/doi/full/10.1177/0278364916688103