Path Planning Algorithms Benchmarking for Grapevines Pruning and Monitoring

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Sandro Augusto Magalhães (Autor) Outra; Filipe Neves Santos (Autor) FEUP; Rui Costa Martins (Autor) Outra; Luís F. Rocha (Autor) FEUP; José Brito (Autor) Outra

Ata de Conferência Internacional

Título: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Páginas: 295-306

19th EPIA Conference on Artificial Intelligence, EPIA 2019

3 September 2019 through 6 September 2019

Indexação

Scopus - 3 Citações

Outras Informações

ID Authenticus: P-00R-03A

DOI: 10.1007/978-3-030-30244-3_25

Abstract (EN): Labour shortage is a reality in agriculture. Farmers are asking for solutions to automate agronomic tasks, such as monitoring, pruning, spraying, and harvesting. The automation of these tasks requires, most of the time, the use of robotic arms to mimic human arms capabilities. The current robotic arm based solutions available, both in the market and in the scientific sphere, have several limitations, such as, low-speed manipulation, the path planning algorithms are not aware of the requirements of the agricultural tasks (robotic motion and manipulation synchronisation), and require active perception tuning to the end-target point. This work benchmarks algorithms from open manipulation planning library (OMPL) considering a cost-effective six-degree freedom manipulator in a simulated vineyard. The OMPL planners shown a very low performance under demanding pruning tasks. The best and most promising results are performed and obtained by BiTRRT. However, further work is needed to increase its performance and reduce planning time. This benchmark work helps the reader to understand the limitations of each algorithm and when to use them. © 2019, Springer Nature Switzerland AG.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12