用触觉+物理推理实现机器人盲操作，高效精准完成精细装配任务
Contact SLAM: An Active Tactile Exploration Policy Based on Physical Reasoning Utilized in Robotic Fine Blind Manipulation Tasks
- 基于物理推理设计触觉感知的主动探索策略
- 在插座装配和推块任务中实现高精度操作
- 适合视觉受限场景下的精细操控应用
接触丰富的操作对机器人执行难度大，尤其在视觉被遮挡时，机器人无法通过视觉获取实时环境状态，称为“盲操作”。本文提出一种新型物理驱动的触觉认知方法——“Contact SLAM”，仅依靠触觉传感和场景先验知识，实现环境状态估计与操作。为提升探索效率，设计了主动探索策略，逐步降低操作场景中的不确定性。实验结果表明，该方法在多个接触丰富任务中表现有效且准确，包括高难度精细的插座装配任务和推块任务。
原文摘要 · Abstract (English)
Contact-rich manipulation is difficult for robots to execute and requires accurate perception of the environment. In some scenarios, vision is occluded. The robot can then no longer obtain real-time scene state information through visual feedback. This is called ``blind manipulation". In this manuscript, a novel physically-driven contact cognition method, called ``Contact SLAM", is proposed. It estimates the state of the environment and achieves manipulation using only tactile sensing and prior knowledge of the scene. To maximize exploration efficiency, this manuscript also designs an active exploration policy. The policy gradually reduces uncertainties in the manipulation scene. The experimental results demonstrated the effectiveness and accuracy of the proposed method in several contact-rich tasks, including the difficult and delicate socket assembly task and block-pushing task.
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