Online Robust MPC based Emergency Maneuvering System for Autonomous Vehicles
원문 초록
Nonlinear Robust Model Predictive Control (RMPC) provides a very promising solution to the problem of automatic emergency maneuvering, which is capable of handling multiple possibly conflicting objectives of robustness and performance. Even though RMPC gives a suboptimal solution, the key challenge in real-time implementation is that it is computationally very demanding. In this paper a real-time capable robust tube MPC based framework for steering control during emergency obstacle avoidance maneuver is presented. The novelty of this framework lies in the robust integration of path planning and path following tasks of autonomous vehicles. A simulation study showcases the robust performance improvements due to the proposed strategy over a non-robust MPC in different extreme maneuvering scenarios.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Optimized adaptive MPC for lateral control of autonomous vehicles
Coordinated Control of Autonomous Vehicles for Traffic Density Reduction at a Signalized Junction: An MPC Approach
Opportunistic Collaborative Planning with Large Vision Model Guided Control and Joint Query-Service Optimization
Robust Tube-based Control Strategy for Vision-guided Autonomous Vehicles
Autonomous driving using GA-optimized neural network based adaptive LPV-MPC controller
Differentiable Nonlinear Model Predictive Control
토론
이 논문과 연결된 포럼 글이 아직 없습니다.