EIDA：面向真实到仿真到真实机器人导航的执行接口动力学自适应
EIDA: Execution-Interface Dynamics Adaptation for Real-to-Sim-to-Real Robot Navigation
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中文总结 AI 辅助
EIDA通过拟合执行接口动力学，在轻量级仿真中更新几何与速度反馈，显著提升真实到仿真到真实导航迁移的成功率与准确性。
中文摘要 AI 辅助
当速度指令产生的运动与反馈不同于策略训练期间建模的运动与反馈时，仿真到机器人的迁移可能会失败。我们提出了执行接口动力学自适应（EIDA），该方法在不重建执行器动力学的情况下，从目标平台执行数据中拟合这些响应。一个机体坐标系位姿增量模型用于更新仿真器几何结构，而另一个独立模型则预测策略所观测到的速度反馈；策略输入中包含一段较短的速度反馈历史。拟合后的模型被用于一个轻量级GPU并行仿真器中。在完整的Jackal和Go2验证集上，与仿真器预定义的运动模型相比，拟合模型降低了位置和偏航角的预测误差。在另一个基于物理的仿真器中评估的100个基准导航环境中，EIDA在有无全局引导的情况下均取得了最高的成功率和导航得分。反馈消融实验进一步支持了匹配策略面向速度估计的必要性。在物理Unitree Go2上，EIDA在全部20次静态场景试验中均无碰撞地到达目标，而基线仅为20次中的4次。这些结果表明，执行接口自适应可以在不进行详细执行器仿真的情况下改善导航迁移。
英文摘要
Simulation-to-robot transfer can fail when velocity commands produce motion and feedback that differ from those modeled during policy training. We present execution-interface dynamics adaptation (EIDA), which fits these responses from target-platform execution data without reconstructing actuator dynamics. A model of body-frame pose increments updates simulator geometry, while a separate model predicts the velocity feedback observed by the policy; a short history of velocity feedback is included in the policy input. The fitted models are used within a lightweight GPU-parallel simulator. On the full Jackal and Go2 validation sets, the fitted models reduced position and yaw prediction errors relative to the simulator's predefined motion model. Across 100 benchmark navigation environments evaluated in a separate physics-based simulator, EIDA achieved the highest success rate and navigation score among the compared learned policies, both with and without global guidance. Feedback ablations further supported the need to match policy-facing velocity estimates. On a physical Unitree Go2, EIDA reached the goal without collision in all 20 static-scene trials, compared with 4 of 20 for the baseline. These results show that execution-interface adaptation can improve navigation transfer without detailed actuator simulation.
发表机构
- Eastern Institute of Technology（东方理工大学）
- National University of Singapore（新加坡国立大学）
- The Hong Kong Polytechnic University（香港理工大学）
- University of Science and Technology of China（中国科学技术大学）
机构由 AI 辅助整理，请以论文原文为准。
