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arXiv · 2210.00051

Force/Torque Sensing for Soft Grippers using an External Camera

Jeremy A. Collins·Patrick Grady·Charles C. Kemp
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Abstract

Robotic manipulation can benefit from wrist-mounted force/torque (F/T) sensors, but conventional F/T sensors can be expensive, difficult to install, and damaged by high loads. We present Visual Force/Torque Sensing (VFTS), a method that visually estimates the 6-axis F/T measurement that would be reported by a conventional F/T sensor. In contrast to approaches that sense loads using internal cameras placed behind soft exterior surfaces, our approach uses an external camera with a fisheye lens that observes a soft gripper. VFTS includes a deep learning model that takes a single RGB image as input and outputs a 6-axis F/T estimate. We trained the model with sensor data collected while teleoperating a robot (Stretch RE1 from Hello Robot Inc.) to perform manipulation tasks. VFTS outperformed F/T estimates based on motor currents, generalized to a novel home environment, and supported three autonomous tasks relevant to healthcare: grasping a blanket, pulling a blanket over a manikin, and cleaning a manikin's limbs. VFTS also performed well with a manually operated pneumatic gripper. Overall, our results suggest that an external camera observing a soft gripper can perform useful visual force/torque sensing for a variety of manipulation tasks.

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Jeremy A. Collins, Patrick Grady, Charles C. Kemp. 2022-09-30. Force/Torque Sensing for Soft Grippers using an External Camera. https://arxiv.org/abs/2210.00051

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