Video2DoorTraversal：通过模拟门孪生体实现推门穿越
Video2DoorTraversal: Push Door Traversal via Simulated Door Twins
- Shanghai Jiao Tong University（上海交通大学）
- NeoWa Robotics（NeoWa机器人公司）
- Shandong University（山东大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出Video2DoorTraversal框架，通过DoorTwin重构门孪生体，训练ArticuACT策略，实现轮腿式移动机械手开门穿越，在真实门与未见门上分别达到96.57%和80.95%的成功率。
AI中文摘要：
开门与穿越是一项长周期的移动操作任务，需要精准的把手交互以及协调的基座-机械臂控制。本文提出Video2DoorTraversal，一种用于轮腿式移动机械手的单视频实-仿-实迁移框架。给定一段真实门的RGB视频，DoorTwin可重构出实例对齐、可关节化、适配仿真的门孪生体，具备真实的几何与外观。仿真闭环智能体将恢复的关节结构转化为参数化技能程序，并迭代优化失败的 rollout 以生成物理可执行的演示。这些演示用于训练ArticuACT，一种双深度策略，其以机器人中心相机为条件、交互感知监督来预测协调的基座、机械臂与夹爪指令。所有感知与策略推理均在板上运行，系统在5扇真实门上实现96.57%的平均成功率，在结构相似的未见门上实现80.95%的零样本成功率，且完成接近、开门、穿越全序列平均耗时约13秒。项目页面：this https URL。
英文摘要：
Door opening and traversal is a long-horizon loco-manipulation task that requires precise handle interaction and coordinated base-arm control. We present Video2DoorTraversal, a single-video real-to-sim-to-real framework for wheel-legged mobile manipulators. Given one RGB video of a real door, DoorTwin reconstructs an instance-aligned, articulated, and simulation-ready door twin with realistic geometry and appearance. A simulation-in-the-loop agent converts the recovered articulation into a parameterized skill program and iteratively refines failed rollouts to generate physically executable demonstrations. These demonstrations are used to train ArticuACT, a dual-depth policy that predicts coordinated base, arm, and gripper commands using robot-centric camera conditioning and interaction-aware supervision. With all perception and policy inference running onboard, the system achieves a 96.57% average success rate across five real doors and an 80.95% zero-shot success rate on structurally similar unseen doors, while completing the full approach, opening, and traversal sequence in approximately 13s on average. Project Page: https://video2doortraversal.github.io/.
