Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Schildbach, Georg"'
Autor:
Conrad, Mirko, Schildbach, Georg
Automated and autonomous driving has made a significant technological leap over the past decade. In this process, the complexity of algorithms used for vehicle control has grown significantly. Model Predictive Control (MPC) is a prominent example, wh
Externí odkaz:
http://arxiv.org/abs/2407.21569
Autor:
Kaiser, Tanja Katharina, Begemann, Marian Johannes, Plattenteich, Tavia, Schilling, Lars, Schildbach, Georg, Hamann, Heiko
Developing reusable software for mobile robots is still challenging. Even more so for swarm robots, despite the desired simplicity of the robot controllers. Prototyping and experimenting are difficult due to the multi-robot setting and often require
Externí odkaz:
http://arxiv.org/abs/2405.02438
Reference tracking and obstacle avoidance rank among the foremost challenging aspects of autonomous driving. This paper proposes control designs for solving reference tracking problems in autonomous driving tasks while considering static obstacles. W
Externí odkaz:
http://arxiv.org/abs/2405.02030
This work develops a first Model Predictive Control for European Space Agencies 3-dof free-floating platform. The challenges of the platform are the on/off thrusters, which cannot be actuated continuously and which are subject to certain timing const
Externí odkaz:
http://arxiv.org/abs/2312.10788
This paper addresses the problem of traffic prediction and control of autonomous vehicles on highways. A modified Interacting Multiple Model Kalman filter algorithm is applied to predict the motion behavior of the traffic participants by considering
Externí odkaz:
http://arxiv.org/abs/2310.07526
In this work, we provide deterministic error bounds for the actual state evolution of nonlinear systems embedded with the linear parametric variable (LPV) formulation and steered by model predictive control (MPC). The main novelty concerns the explic
Externí odkaz:
http://arxiv.org/abs/2310.01049
In this study, we are concerned with autonomous driving missions when a static obstacle blocks a given reference trajectory. To provide a realistic control design, we employ a model predictive control (MPC) utilizing nonlinear state-space dynamic mod
Externí odkaz:
http://arxiv.org/abs/2307.06031
This paper proposes a control architecture for autonomous lane keeping by a vehicle. In this paper, the vehicle dynamics consist of two parts: lateral and longitudinal dynamics. Therefore, the control architecture comprises two subsequent controllers
Externí odkaz:
http://arxiv.org/abs/2210.02971
This paper proposes a Robust Safe Control Architecture (RSCA) for safe-decision making. The system to be controlled is a vehicle in the presence of bounded disturbances. The RSCA consists of two parts: a Supervisor MPC and a Controller MPC. Both the
Externí odkaz:
http://arxiv.org/abs/2206.09735
We propose a deep reinforcement learning approach for solving a mapless navigation problem in warehouse scenarios. In our approach, an automation guided vehicle is equipped with LiDAR and frontal RGB sensors and learns to perform a targeted navigatio
Externí odkaz:
http://arxiv.org/abs/2202.11512