机器人靠全身触觉定位抓取物体,无需视觉。
No Need to Look! Locating and Grasping Objects by a Robot Arm Covered with Sensitive Skin
- 用全身敏感皮肤接触环境,分两阶段搜物抓物。
- 真实机器人单物成功率85.7%,比末端触觉快6倍。
- 适合光照差、遮挡多的农业采摘等场景。
机器人通常依赖视觉定位抓取物体,触觉反馈仅作辅助。本文探索在完全无视觉输入下,仅靠触觉完成搜索与抓取的极端情况。核心创新在于利用覆盖整个机械臂表面的敏感皮肤进行接触感知。搜索分为两个阶段:(1) 以机械臂整体表面进行粗略工作区探索;(2) 使用末端配备力/力矩传感器进行精确定位。我们在仿真和真实机器人上系统评估该方法,证明可成功定位、抓取并放入篮子多种物体。真实机器人单物体整体成功率85.7%,失败主要发生在特定物体抓取环节。使用全身接触的方法比仅依赖末端触觉的基线方法快六倍。我们还实现了桌面上多个物体的定位与抓取。该方法不局限于特定平台,适用于任何具备全身接触感知能力的机器人系统。本研究对光照不佳、有尘烟或遮挡的场景(如作物在叶丛中采摘)具有重要应用前景。
原文摘要 · Abstract (English)
Locating and grasping of objects by robots is typically performed using visual sensors. Haptic feedback from contacts with the environment is only secondary if present at all. In this work, we explored an extreme case of searching for and grasping objects in complete absence of visual input, relying on haptic feedback only. The main novelty lies in the use of contacts over the complete surface of a robot manipulator covered with sensitive skin. The search is divided into two phases: (1) coarse workspace exploration with the complete robot surface, followed by (2) precise localization using the end-effector equipped with a force/torque sensor. We systematically evaluated this method in simulation and on the real robot, demonstrating that diverse objects can be located, grasped, and put in a basket. The overall success rate on the real robot for one object was 85.7% with failures mainly while grasping specific objects. The method using whole-body contacts is six times faster compared to a baseline that uses haptic feedback only on the end-effector. We also show locating and grasping multiple objects on the table. This method is not restricted to our specific setup and can be deployed on any platform with the ability of sensing contacts over the entire body surface. This work holds promise for diverse applications in areas with challenging visual perception (due to lighting, dust, smoke, occlusion) such as in agriculture when fruits or vegetables need to be located inside foliage and picked.
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