10 papers
Latent Diffusion Policy: Shaping Latent Spaces for Diffusion-Based Robotic Manipulation
Zhexuan Zhou, Yichen Lai, Jinhao Zhang +3
Diffusion-based visuomotor policies operating directly in raw action spaces conflate scene comprehension with trajectory generation within a single denoising process. The resulting…
Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning
Yude Li, Zhexuan Zhou, Huizhe Li +6
Decentralized cooperative pursuit in cluttered environments is challenging for autonomous aerial swarms, especially under partial and noisy perception. Existing methods often rely…
LAP: Fast LAtent Diffusion Planner for Autonomous Driving
Jinhao Zhang, Wenlong Xia, Zhexuan Zhou +3
Diffusion models have demonstrated strong capabilities for modeling human-like driving behaviors in autonomous driving, but their iterative sampling process induces substantial lat…
Hyper-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control
Jinhao Zhang, Zhexuan Zhou, Huizhe Li +5
Diffusion-based visuomotor policies perform well in robotic manipulation, yet current methods still inherit image-generation-style decoders and multi-step sampling. We revisit this…
Information Filtering via Variational Regularization for Robot Manipulation
Jinhao Zhang, Wenlong Xia, Yaojia Wang +6
Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However, most existing methods employ an…
Agile in the Face of Delay: Asynchronous End-to-End Learning for Real-World Aerial Navigation
Yude Li, Zhexuan Zhou, Huizhe Li +2
Robust autonomous navigation for Autonomous Aerial Vehicles (AAVs) in complex environments is a critical capability. However, modern end-to-end navigation faces a key challenge: th…