Parallel learning-based steering control for autonomous driving
Steering control for autonomous vehicles at high speeds is challenging due to the highly
nonlinear vehicle dynamics. The traditional model-based controllers usually degrade …
nonlinear vehicle dynamics. The traditional model-based controllers usually degrade …
Mobility vla: Multimodal instruction navigation with long-context vlms and topological graphs
An elusive goal in navigation research is to build an intelligent agent that can understand
multimodal instructions including natural language and image, and perform useful …
multimodal instructions including natural language and image, and perform useful …
{NeuOS}: A {Latency-Predictable}{Multi-Dimensional} Optimization Framework for {DNN-driven} Autonomous Systems
Deep neural networks (DNNs) used in computed vision have become widespread
techniques commonly used in autonomous embedded systems for applications such as …
techniques commonly used in autonomous embedded systems for applications such as …
Distributed consensus tracking control based on state and disturbance observations for mixed-order multi-agent mechanical systems
Y Wang, Y Liu, X Li, Y Liang - Journal of the Franklin Institute, 2023 - Elsevier
In this paper, we study the cooperative consensus control problem of mixed-order (also
called hybrid-order) multi-agent mechanical systems (MMSs) under the condition of …
called hybrid-order) multi-agent mechanical systems (MMSs) under the condition of …
Dyna-PPO reinforcement learning with Gaussian process for the continuous action decision-making in autonomous driving
G Wu, W Fang, J Wang, P Ge, J Cao, Y **, P Gou - Applied Intelligence, 2023 - Springer
Recent years have witnessed rapid development of autonomous driving. Model-based and
model-free reinforcement learning are two popular learning methods for autonomous …
model-free reinforcement learning are two popular learning methods for autonomous …
Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances
L Guo, P Guo, L Guan, H Ma - Measurement Science and …, 2024 - iopscience.iop.org
Parameter fluctuations, unmodeled dynamics, speed variation, steering actuator faults, and
other multi-channel uncertain disturbances are the key challenges faced by the path tracking …
other multi-channel uncertain disturbances are the key challenges faced by the path tracking …
Guided policy search model-based reinforcement learning for urban autonomous driving
In this paper, we continue our prior work on using imitation learning (IL) and model free
reinforcement learning (RL) to learn driving policies for autonomous driving in urban …
reinforcement learning (RL) to learn driving policies for autonomous driving in urban …
Cocoi: contact-aware online context inference for generalizable non-planar pushing
General contact-rich manipulation problems are long-standing challenges in robotics due to
the difficulty of understanding complicated contact physics. Deep reinforcement learning …
the difficulty of understanding complicated contact physics. Deep reinforcement learning …
Grounded relational inference: Domain knowledge driven explainable autonomous driving
Explainability is essential for autonomous vehicles and other robotics systems interacting
with humans and other objects during operation. Humans need to understand and anticipate …
with humans and other objects during operation. Humans need to understand and anticipate …
Tolerance-guided policy learning for adaptable and transferrable delicate industrial insertion
B Niu, C Wang, C Liu - Conference on Robot Learning, 2021 - proceedings.mlr.press
Policy learning for delicate industrial insertion tasks (eg, PC board assembly) is challenging.
This paper considers two major problems: how to learn a diversified policy (instead of just …
This paper considers two major problems: how to learn a diversified policy (instead of just …