Safety of Dynamical Systems with Multiple Non-Convex Unsafe Sets Using Control Barrier Functions
원문 초록
This paper presents an approach to deal with safety of dynamical systems in presence of multiple non-convex unsafe sets. While optimal control and model predictive control strategies can be employed in these scenarios, they suffer from high computational complexity in case of general nonlinear systems. Leveraging control barrier functions, on the other hand, results in computationally efficient control algorithms. Nevertheless, when safety guarantees have to be enforced alongside stability objectives, undesired asymptotically stable equilibrium points have been shown to arise. We propose a computationally efficient optimization-based approach which allows us to ensure safety of dynamical systems without introducing undesired equilibria even in presence of multiple non-convex unsafe sets. The developed control algorithm is showcased in simulation and in a real robot navigation application.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Integration of a Graph-Based Path Planner and Mixed-Integer MPC for Robot Navigation in Cluttered Environments
Robust Output-Feedback MPC for Nonlinear Systems with Applications to Robotic Exploration
Differentiable Nonlinear Model Predictive Control
Evaluating the Impact of Model Accuracy for Optimizing Battery Energy Storage Systems
Adversarial Attacks and Detection in Visual Place Recognition for Safer Robot Navigation
Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.