4 papers
AugVLA-3D: Depth-Driven Feature Augmentation for Vision-Language-Action Models
Zhifeng Rao, Wenlong Chen, Lei Xie +4
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic perception and control, yet most existing approaches primarily rely on VLM trained using 2…
Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition
Wule Mao, Zhouheng Li, Yunhao Luo +3
Achieving safe, efficient, and kinematically feasible planning in dynamic environments remains a significant challenge, as planners must simultaneously handle moving obstacles, sen…
Enhancing Physical Consistency in Lightweight World Models
Dingrui Wang, Zhexiao Sun, Zhouheng Li +8
A major challenge in deploying world models is the trade-off between size and performance. Large world models can capture rich physical dynamics but require massive computing resou…
A Learning-based Planning and Control Framework for Inertia Drift Vehicles
Bei Zhou, Zhouheng Li, Lei Xie +2
Inertia drift is a transitional maneuver between two sustained drift stages in opposite directions, which provides valuable insights for navigating consecutive sharp corners for au…