Nonlinear model predictive control schemes for obstacle avoidance
| dc.creator | Marcelo A. Santos | |
| dc.creator | Antonio Ferramosca | |
| dc.creator | Guilherme Vianna Raffo | |
| dc.date.accessioned | 2025-05-27T14:10:57Z | |
| dc.date.accessioned | 2025-09-09T00:53:22Z | |
| dc.date.available | 2025-05-27T14:10:57Z | |
| dc.date.issued | 2023 | |
| dc.identifier.doi | 10.1007/s40313-023-01024-2 | |
| dc.identifier.issn | 21953880 | |
| dc.identifier.uri | https://hdl.handle.net/1843/82517 | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Minas Gerais | |
| dc.relation.ispartof | Journal of Control, Automation and Electrical Systems | |
| dc.rights | Acesso Restrito | |
| dc.subject | Aeronave não tripulada | |
| dc.subject.other | The technological development experienced in the last couple of decades has reshaped people’s daily routines from a personal and professional point of view. The list goes through all sorts of advanced robotics systems and autonomous vehicles including manufacturing robots, unmanned aerial vehicles (UAVs), self-driving cars, household and warehouse autonomous robots, underwater vehicles, among others. However, as this kind of systems becomes more common, new technical issues arise, bringing more light to challenges related to how to create safe and reliable intelligent motion systems to interact with human life and complex environments. Besides the specific tasks that each system is designed for, when it comes to autonomous navigation, problems such as path planning and dynamic control are paramount. As for the applications, systems able to navigate autonomously are being used for distinct tasks | |
| dc.title | Nonlinear model predictive control schemes for obstacle avoidance | |
| dc.type | Artigo de periódico | |
| local.citation.epage | 906 | |
| local.citation.issue | 5 | |
| local.citation.spage | 891 | |
| local.citation.volume | 34 | |
| local.description.resumo | This work proposes single-layer nonlinear model predictive control schemes to solve the autonomous navigation problem while providing obstacle avoidance feature in cluttered environments with previously unknown obstacles. Considering model predictive control frameworks for set-point stabilization and set-point tracking, the penalty method of nonlinear programming is taken into account to enforce avoidance constraints without losing stability and feasibility guarantees. The set-point tracking schemes are shown to be more suitable for motion systems due to their enlarged domain of attraction with respect to the regulation formulations, making it feasible for any changing targets. Further, for the set-point tracking problem, the proposed schemes avoid the use of terminal regions, which, for nonlinear systems, might be cumbersome to compute. Thus, simple design schemes based on a relaxed terminal equality constraint and on a weighted terminal cost are considered. Finally, two case studies considering a differential mobile robot and a quadrotor unmanned aerial vehicle are provided to evaluate the set-point tracking formulations. | |
| local.publisher.country | Brasil | |
| local.publisher.department | ENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA | |
| local.publisher.initials | UFMG | |
| local.url.externa | https://link.springer.com/article/10.1007/s40313-023-01024-2 |
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