LCDP-Sim: Language-Conditioned Diffusion Policy
An end-to-end Vision-Language-Action (VLA) system utilizing Diffusion Policy to map RGB images and natural language instructions into robotic control signals.
An end-to-end Vision-Language-Action (VLA) system utilizing Diffusion Policy to map RGB images and natural language instructions into robotic control signals.
A comprehensive mapping and navigation system combining OpenStreetMap data with Gaode Maps API for accurate routing and location search capabilities.
A comprehensive neural style transfer toolkit with modular architecture, batch processing capabilities, and interactive web interface.
Published in IEEE Robotics and Automation Letters (RAL), 2025
This paper presents a novel approach for learning risk maps in autonomous driving scenarios under partial observability constraints, utilizing advanced spatiotemporal modeling and diffusion models.
Recommended citation: Hong, Y., Ding, W. et al. (2025). "Learning Risk Map for Autonomous Driving in Partially Observable Environments." IEEE Robotics and Automation Letters (RAL). (Under Review)
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