OCEAN: An Openspace Collision-free Trajectory Planner for Autonomous Parking Based on ADMM
D Wang, Y Lu, W Liu, H Zuo, J Xin, X Long… - arXiv preprint arXiv …, 2024 - arxiv.org
In this paper, we propose an Openspace Collision-freE trAjectory plaNner (OCEAN) for
autonomous parking. OCEAN is an optimization-based trajectory planner accelerated by …
autonomous parking. OCEAN is an optimization-based trajectory planner accelerated by …
Lane-Keeping Control of Autonomous Vehicles Through a Soft-Constrained Iterative LQR
DH Lee - arXiv preprint arXiv:2311.16900, 2023 - arxiv.org
The accurate prediction of smooth steering inputs is crucial for autonomous vehicle
applications because control actions with jitter might cause the vehicle system to become …
applications because control actions with jitter might cause the vehicle system to become …
Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving
Y Zhang, J Boedecker, C Li, G Zhou - arXiv preprint arXiv:2301.13313, 2023 - arxiv.org
Model Predictive Control (MPC) is attracting tremendous attention in the autonomous driving
task as a powerful control technique. The success of an MPC controller strongly depends on …
task as a powerful control technique. The success of an MPC controller strongly depends on …
Real Time Motion Planning Using Constrained Iterative Linear Quadratic Regulator for On-Road Self-Driving
C You - arXiv preprint arXiv:2202.08400, 2022 - arxiv.org
Collision avoidance is one of the most challenging tasks people need to consider for
developing the self-driving technology. In this paper we propose a new spatiotemporal …
developing the self-driving technology. In this paper we propose a new spatiotemporal …
[PDF][PDF] Real-time Trajectory Generation via Dynamic Movement Primitives for Autonomous Racing
We employ sequences of high-order motion primitives for efficient online trajectory planning,
enabling competitive racecar control even when the car deviates from an offline …
enabling competitive racecar control even when the car deviates from an offline …
GrAVITree: Graph-based Approximate Value Function In a Tree
PH Washington, D Fridovich-Keil… - 2023 American …, 2023 - ieeexplore.ieee.org
In this paper, we introduce GrAVITree, a tree-and sampling-based algorithm to compute a
near-optimal value function and corresponding feedback policy for indefinite time-horizon …
near-optimal value function and corresponding feedback policy for indefinite time-horizon …
A Survey of Vehicle Dynamics Models for Autonomous Driving
L Jin, S Zhao, N Xu - 2024 - sae.org
Autonomous driving technology is more and more important nowadays, it has been
changing the living style of our society. As for autonomous driving planning and control …
changing the living style of our society. As for autonomous driving planning and control …
i2LQR: Iterative LQR for Iterative Tasks in Dynamic Environments
This work introduces a novel control strategy called Iterative Linear Quadratic Regulator for
Iterative Tasks (i2LQR), which aims to improve closed-loop performance with local trajectory …
Iterative Tasks (i2LQR), which aims to improve closed-loop performance with local trajectory …
Control of a lower limb exoskeleton using Learning from Demonstration and an iterative Linear Quadratic Regulator Controller: A simulation study
Lower limb exoskeletons have complex dynamics that mimic human motion. They need to
be able to replicate lower limb motion such as walking. The trajectory of the exoskeleton …
be able to replicate lower limb motion such as walking. The trajectory of the exoskeleton …
Safe and Trustworthy Decision Making through Reinforcement Learning
J Li - 2024 - escholarship.org
The advent of advanced computational technologies and artificial intelligence has ushered
in a new era of complex systems and applications, notably in the realms of autonomous …
in a new era of complex systems and applications, notably in the realms of autonomous …