| Texto completo | |
| Autor(es): |
Vangasse, Arthur da C.
;
Raffo, Guilherme V.
;
Pimenta, Luciano C. A.
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2023 LATIN AMERICAN ROBOTICS SYMPOSIUM, LARS, 2023 BRAZILIAN SYMPOSIUM ON ROBOTICS, SBR, AND 2023 WORKSHOP ON ROBOTICS IN EDUCATION, WRE; v. N/A, p. 6-pg., 2023-01-01. |
| Resumo | |
Multi-agent time-varying path following problems still offer a wide variety of open challenges, in which efficient collision avoidance is of great importance in this context. This work proposes a solution based on artificial vector fields that generate velocity references for single agents in path-following tasks. A distributed Model Predictive Control (MPC) scheme accountable for double integrator dynamic models and collision avoidance features enables the group of robots to follow the dynamic field in a safe manner. Control Barrier Functions (CBF) are utilized to include collision avoidance in the MPC problem. Simulation scenarios corroborate the method's efficiency and highlight the improvements in contrast with previous works. (AU) | |
| Processo FAPESP: | 14/50851-0 - INCT 2014: Instituto Nacional de Ciência e Tecnologia para Sistemas Autônomos Cooperativos Aplicados em Segurança e Meio Ambiente |
| Beneficiário: | Marco Henrique Terra |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |