1 citations · 4 across the 21 of their papers we have counts for
7 papers · 1 filter
OmniScene: Attention-Augmented Multimodal 4D Scene Understanding for Autonomous Driving
Pei Liu, Hongliang Lu, Haichao Liu +5
Human vision is capable of transforming two-dimensional observations into an egocentric three-dimensional scene understanding, which underpins the ability to translate complex scen…
An Intention-driven Lane Change Framework Considering Heterogeneous Dynamic Cooperation in Mixed-traffic Environment
Xiaoyun Qiu, Haichao Liu, Yue Pan +2
In mixed-traffic environments, autonomous vehicles (AVs) must interact with heterogeneous human-driven vehicles (HVs) whose intentions and driving styles vary across individuals an…
VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Haichao Liu, Haoren Guo, Pei Liu +4
Scene understanding and risk-aware attentions are crucial for human drivers to make safe and effective driving decisions. To imitate this cognitive ability in urban autonomous driv…
RoboDexVLM: Visual Language Model-Enabled Task Planning and Motion Control for Dexterous Robot Manipulation
Haichao Liu, Sikai Guo, Pengfei Mai +3
This paper introduces RoboDexVLM, an innovative framework for robot task planning and grasp detection tailored for a collaborative manipulator equipped with a dexterous hand. Previ…
VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion
Pei Liu, Haipeng Liu, Haichao Liu +3
Human drivers adeptly navigate complex scenarios by utilizing rich attentional semantics, but the current autonomous systems struggle to replicate this ability, as they often lose…
CoDriveVLM: VLM-Enhanced Urban Cooperative Dispatching and Motion Planning for Future Autonomous Mobility on Demand Systems
Haichao Liu, Ruoyu Yao, Wenru Liu +3
The increasing demand for flexible and efficient urban transportation solutions has spotlighted the limitations of traditional Demand Responsive Transport (DRT) systems, particular…
UDMC: Unified Decision-Making and Control Framework for Urban Autonomous Driving with Motion Prediction of Traffic Participants
Haichao Liu, Kai Chen, Yulin Li +3
Current autonomous driving systems often struggle to balance decision-making and motion control while ensuring safety and traffic rule compliance, especially in complex urban envir…