12 citations · 28 across the 16 of their papers we have counts for
9 papers · 1 filter
Kinematify: Open-Vocabulary Synthesis of High-DoF Articulated Objects
Jiawei Wang, Dingyou Wang, Jiaming Hu +3
A deep understanding of kinematic structures and movable components is essential for enabling robots to manipulate objects and model their own articulated forms. Such understanding…
TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Jiawei Wang, Haowei Sun, Xintao Yan +3
Safe and scalable deployment of end-to-end (E2E) autonomous driving requires extensive and diverse data, particularly safety-critical events. Existing data are mostly generated fro…
Improving Traffic Signal Data Quality for the Waymo Open Motion Dataset
Xintao Yan, Erdao Liang, Jiawei Wang +2
Datasets pertaining to autonomous vehicles (AVs) hold significant promise for a range of research fields, including artificial intelligence (AI), autonomous driving, and transporta…
Mobile Manipulation Planning for Tabletop Rearrangement
Jiaming Hu, Jiawei Wang, Henrik I Christensen
Efficient tabletop rearrangement planning seeks to find high-quality solutions while minimizing total cost. However, the task is challenging due to object dependencies and limited…
GSFF-SLAM: 3D Semantic Gaussian Splatting SLAM via Feature Field
Zuxing Lu, Xin Yuan, Shaowen Yang +2
Semantic-aware 3D scene reconstruction is essential for autonomous robots to perform complex interactions. Semantic SLAM, an online approach, integrates pose tracking, geometric re…
cpRRTC: GPU-Parallel RRT-Connect for Constrained Motion Planning
Jiaming Hu, Jiawei Wang, Henrik Christensen
Motion planning is a fundamental problem in robotics that involves generating feasible trajectories for a robot to follow. Recent advances in parallel computing, particularly throu…
RADE: Learning Risk-Adjustable Driving Environment via Multi-Agent Conditional Diffusion
Jiawei Wang, Xintao Yan, Yao Mu +3
Generating safety-critical scenarios in high-fidelity simulations offers a promising and cost-effective approach for efficient testing of autonomous vehicles. Existing methods typi…
TeraSim: Uncovering Unknown Unsafe Events for Autonomous Vehicles through Generative Simulation
Haowei Sun, Xintao Yan, Zhijie Qiao +14
Traffic simulation is essential for autonomous vehicle (AV) development, enabling comprehensive safety evaluation across diverse driving conditions. However, traditional rule-based…
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events
Xiaojie Yang, Hangli Ge, Jiawei Wang +4
Large-scale human mobility exhibits spatial and temporal patterns that can assist policymakers in decision making. Although traditional prediction models attempt to capture these p…