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  • LAGO Policy: Latency-Aware Asynchronous Diffusion Policies with Goal . . .
    LAGO Policy improves inter-chunk consistency via latency-aware classifier-free guidance conditioning on future actions It further enables goal-directed collision-free trajectory planning by predicting a task-relevant interaction goal from demonstrations
  • Delay-Aware Diffusion Policy: Bridging the - arXiv. org
    In this paper, we introduce Delay-Aware Diffusion Policy (DA-DP), a novel framework that improves diffusion policy performance in dynamic environments by explicitly modeling inference delay
  • LAGO Policy: Latency-Aware Diffusion for Robotics
    This paper presents LAGO Policy, a framework that integrates latency-aware diffusion, goal-directed planning, and trajectory optimization for smooth, collision-free robot manipulation
  • LAGO Policy: Latency-Aware Asynchronous Diffusion Policies with Goal . . .
    Key Contributions LAGO Policy introduces a unified asynchronous action-generation framework that integrates trajectory optimization with diffusion policies for smooth and safe robotic manipulation It addresses inter-chunk discontinuities via latency-aware guidance and enables goal-directed collision-free planning by predicting interaction goals, leading to more reliable real-world execution
  • 论文速读--扩散模型+离线策略学习 - 知乎
    Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model, NIPS2023 提出一种利用conformal预测来衡量模型动力学不确定性的方法，文中宣称这一方法能够准确地估计不确定性 动机：不确定性至关重要，conformal预测比其他方法有更好的不确定性预测性能
  • LAGO Policy：融合规划的异步扩散策略 - 什么值得买
    03 实测效果与验证 研究团队在8项具有挑战性的真实世界操控任务中评估了LAGO Policy的表现。 这些任务涵盖精准抓取、姿态对齐、接触丰富控制及平滑执行等高要求场景，包括插笔、杯子转移、抓取放置、倾倒、毛巾折叠、悬挂胶带、盒子整理及螺丝分类。
  • [2512. 07697] Delay-Aware Diffusion Policy: Bridging the Observation . . .
    We introduce Delay-Aware Diffusion Policy (DA-DP), a framework for explicitly incorporating inference delays into policy learning DA-DP corrects zero-delay trajectories to their delay-compensated counterparts, and augments the policy with delay conditioning
  • Jiaqi Peng
    We present a sim-to-real navigation diffusion policy that can achieve cross-embodiment generalization in dynamic, cluttered and diverse real-world scenarios
  • ZhengYinan-AIR Diffusion-Planner - GitHub
    The official implementation of Diffusion Planner, which represents a pioneering effort in fully harnessing the power of diffusion models for high-performance motion planning, without overly relying on refinement
  • Diffusion Policy—基于扩散模型的机器人动作生成策略 - 知乎
    这篇关于Diffusion Policy的论文介绍和你以往看过的任何一篇论文介绍都不同，它不是生硬的学术介绍，也不是夸大的媒体PR，它是一篇可以让非学术背景的人看得懂的笔记。





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