Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Gerdts, Matthias"'
Autor:
Wang, Qiannan, Gerdts, Matthias
This paper proposes a path planning algorithm for autonomous vehicles, evaluating collision severity with respect to both static and dynamic obstacles. A collision severity map is generated from ratings, quantifying the severity of collisions. A two-
Externí odkaz:
http://arxiv.org/abs/2408.16076
Models involving hybrid systems are versatile in their application, but difficult to handle and optimize efficiently due to their combinatorial nature. This work presents a method to cope with hybrid optimal control problems which, in contrast to dec
Externí odkaz:
http://arxiv.org/abs/2403.06842
Collision Avoidance using Iterative Dynamic and Nonlinear Programming with Adaptive Grid Refinements
Publikováno v:
2024 European Control Conference (ECC), Stockholm, Sweden, 2024, pp. 52-57
Nonlinear optimal control problems for trajectory planning with obstacle avoidance present several challenges. While general-purpose optimizers and dynamic programming methods struggle when adopted separately, their combination enabled by a penalty a
Externí odkaz:
http://arxiv.org/abs/2311.03148
Modern vertical take-off and landing vehicles (VTOLs) could significantly affect the future of mobility. The broad range of their application fields encompasses urban air mobility, transportation and logistics as well as reconnaissance and observatio
Externí odkaz:
http://arxiv.org/abs/2303.03351
Autor:
Wang, Qiannan, Gerdts, Matthias
In this paper, a risk map-based path planning algorithm is introduced for autonomous vehicles. Multivariate B-splines are implemented to generate a risk map, which measures the risk of colliding with different objects. In the following step, a two-le
Externí odkaz:
http://arxiv.org/abs/2203.03681
Akademický článek
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We consider the problem of computing safety regions, modeled as nonconvex backward reachable sets, for a nonlinear car collision avoidance model with time-dependent obstacles. The Hamilton-Jacobi-Bellman framework is used. A new formulation of level
Externí odkaz:
http://arxiv.org/abs/1911.12222
Autor:
Gerdts, Matthias
The paper discusses multistep nonlinear model-predictive control (NMPC) schemes for the tracking of a car model along a given reference track. In particular we will compare the numerical performance and robustness of classic single step NMPC, multist
Externí odkaz:
http://arxiv.org/abs/1809.00577
Autor:
Gerdts, Matthias, Martens, Björn
The paper addresses the problem of providing suitable reference trajectories in motion planning problems for autonomous vehicles. Among the various approaches to compute a reference trajectory, our aim is to find those trajectories which optimize a g
Externí odkaz:
http://arxiv.org/abs/1801.07612