7 papers
ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving
Zhiyuan Zhang, Yanlun Peng, Jianing Zhang +7
Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can res…
KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation
Yuansen Huang, Jiayi Chen, Haoran Liu +6
Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly contact-based test-time refi…
ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation
Zhengcheng Yu, Changze Li, Haoran Liu +1
Autonomous parking demands precise low-speed maneuvering within narrow, cluttered, and highly constrained environments, where vehicles must navigate tight spaces while avoiding sta…
Elevator-LIO: Robust LiDAR-Inertial Odometry for Multi-Floor Navigation under Elevator-Induced Non-Inertial Motion
Yifan Zhang, Yudong Huang, Yuchong Zhang +4
This paper presents Elevator-LIO, a LiDAR-inertial odometry framework designed to achieve continuous robot localization during elevator travel, thereby supporting cross-floor robot…
Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations
Zhiyuan Zhang, Zhenghao Jin, Yanlun Peng +8
Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving have made important progress…
Embodied Navigation Foundation Model
Jiazhao Zhang, Anqi Li, Yunpeng Qi +14
Navigation is a fundamental capability in embodied AI, representing the intelligence required to perceive and interact within physical environments following language instructions.…