Zobrazeno 1 - 10
of 2 188
pro vyhledávání: '"Swevers"'
Publikováno v:
Volume 9, Issue 11, 2024
This paper introduces an efficient $\mathcal{O}(n)$ compute and memory complexity algorithm for globally optimal path planning on 2D Cartesian grids. Unlike existing marching methods that rely on approximate discretized solutions to the Eikonal equat
Externí odkaz:
http://arxiv.org/abs/2409.11545
The manipulation of deformable linear objects (DLOs) via model-based control requires an accurate and computationally efficient dynamics model. Yet, data-driven DLO dynamics models require large training data sets while their predictions often do not
Externí odkaz:
http://arxiv.org/abs/2407.03476
This paper proposes DriViDOC: a framework for Driving from Vision through Differentiable Optimal Control, and its application to learn autonomous driving controllers from human demonstrations. DriViDOC combines the automatic inference of relevant fea
Externí odkaz:
http://arxiv.org/abs/2403.15102
Autor:
Kiessling, David, Baumgärtner, Katrin, Frey, Jonathan, Decré, Wilm, Swevers, Jan, Diehl, Moritz
This paper examines the question of finding feasible points to discrete-time optimal control problems. The optimization problem of finding a feasible trajectory is transcribed to an unconstrained optimal control problem. An efficient algorithm, calle
Externí odkaz:
http://arxiv.org/abs/2403.10115
This paper introduces a novel, lightweight method to solve the visibility problem for 2D grids. The proposed method evaluates the existence of lines-of-sight from a source point to all other grid cells in a single pass with no preprocessing and indep
Externí odkaz:
http://arxiv.org/abs/2403.06494
Autor:
Zhang, Shuhao, Swevers, Jan
This paper proposes a two-stage approach to formulate the time-optimal point-to-point motion planning problem, involving a first stage with a fixed time grid and a second stage with a variable time grid. The proposed approach brings benefits through
Externí odkaz:
http://arxiv.org/abs/2403.03573
This paper presents a Nonlinear Model Predictive Control (NMPC) scheme targeted at motion planning for mechatronic motion systems, such as drones and mobile platforms. NMPC-based motion planning typically requires low computation times to be able to
Externí odkaz:
http://arxiv.org/abs/2402.06263
This paper proposes an almost feasible Sequential Linear Programming (afSLP) algorithm. In the first part, the practical limitations of previously proposed Feasible Sequential Linear Programming (FSLP) methods are discussed along with illustrative ex
Externí odkaz:
http://arxiv.org/abs/2401.13840
We present PV-OSIMr, an efficient algorithm for computing the Delassus matrix (also known as the inverse operational space inertia matrix) for a kinematic tree, with the lowest order computational complexity known in literature. PV-OSIMr is derived b
Externí odkaz:
http://arxiv.org/abs/2310.03676
Autor:
Rastgar, Fatemeh, Masnavi, Houman, Sharma, Basant, Aabloo, Alvo, Swevers, Jan, Singh, Arun Kumar
Efficient navigation in unknown and dynamic environments is crucial for expanding the application domain of mobile robots. The core challenge stems from the nonavailability of a feasible global path for guiding optimization-based local planners. As a
Externí odkaz:
http://arxiv.org/abs/2309.08235