paper-with-me

홈 › Papers

Hybrid Feedback Control for Global and Optimal Safe Navigation

2024-02-26 · Ishak Cheniouni, Soulaimane Berkane, Abdelhamid Tayebi

We propose a hybrid feedback control strategy that safely steers a point-mass robot to a target location optimally from all initial conditions in the n-dimensional Euclidean space with a single spherical obstacle. The robot moves straight to the target when it has a clear line-of-sight to the target location. Otherwise, it engages in an optimal obstacle avoidance maneuver via the shortest path inside the cone enclosing the obstacle and having the robot's position as a vertex. The switching strategy that avoids the undesired equilibria, leading to global asymptotic stability (GAS) of the target location, relies on using two appropriately designed virtual destinations, ensuring control continuity and shortest path generation. Simulation results illustrating the effectiveness of the proposed approach are presented.

📄 PDF Abstract BibTeX arXiv:2402.17038

Code (0)

등록된 구현이 없습니다.

Tasks

Position

Similar Papers 제목 키워드 기반

Hybrid Feedback for Affine Nonlinear Systems with Application to Global Obstacle Avoidance (Extended Version)

2023-05-06 · Miaomiao Wang, Abdelhamid Tayebi

This paper explores the design of hybrid feedback for a class of affine nonlinear systems with topological constraints that prevent global asymptotic stability. A new hybrid control strategy is introduced, which differs …

N-dimensional Convex Obstacle Avoidance using Hybrid Feedback Control (Extended version)

2024-03-17 · Mayur Sawant, Ilia Polushin, Abdelhamid Tayebi arxiv

This paper addresses the autonomous robot navigation problem in a priori unknown n-dimensional environments containing disjoint convex obstacles of arbitrary shapes and sizes, with pairwise distances strictly greater tha…

Robot Navigation

Hybrid Feedback Sampling for Sample-Efficient Model Predictive Control

2026-08-19 · Chaoyi Pan, Zeji Yi, John Zhang, Zachary Manchester 외 arxiv

Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robotic systems. However, for high-dimensional and open-loop unstable dy…

Safety aware model-based reinforcement learning for optimal control of a class of output-feedback nonlinear systems

2021-10-01 · S M Nahid Mahmud, Moad Abudia, Scott A Nivison, Zachary I. Bell 외

The ability to learn and execute optimal control policies safely is critical to realization of complex autonomy, especially where task restarts are not available and/or the systems are safety-critical. Safety requirement…

Model-based Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)

Safe and Quasi-Optimal Autonomous Navigation in Sphere Worlds

2023-02-23 · Ishak Cheniouni, Abdelhamid Tayebi, Soulaimane Berkane

We propose a continuous feedback control strategy that steers a point-mass vehicle safely to a desired destination, in a quasi-optimal manner, from almost all initial conditions in an n-dimensional Euclidean space clutte…

Autonomous Navigation