A Soft Humanoid Hand with In-Finger Visual Perception
| Autor: | Julia Starke, Felix Hundhausen, Tamim Asfour |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Visual perception business.industry Computer science GRASP 02 engineering and technology Convolutional neural network Visual processing Computer Science - Robotics 020901 industrial engineering & automation Parallel processing (DSP implementation) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Robotics (cs.RO) Humanoid robot |
| Zdroj: | IROS |
| DOI: | 10.1109/iros45743.2020.9341080 |
| Popis: | We present a novel underactued humanoid five finger soft hand, the KIT \softhand, which is equipped with cameras in the fingertips and integrates a high performance embedded system for visual processing and control. We describe the actuation mechanism of the hand and the tendon-driven soft finger design with internally routed high-bandwidth flat-flex cables. For efficient on-board parallel processing of visual data from the cameras in each fingertip, we present a hybrid embedded architecture consisting of a field programmable logic array (FPGA) and a microcontroller that allows the realization of visual object segmentation based on convolutional neural networks. We evaluate the hand design by conducting durability experiments with one finger and quantify the grasp performance in terms of grasping force, speed and grasp success. The results show that the hand exhibits a grasp force of 31.8 N and a mechanical durability of the finger of more than 15.000 closing cycles. Finally, we evaluate the accuracy of visual object segmentation during the different phases of the grasping process using five different objects. Hereby, an accuracy above 90 % can be achieved. 7 pages |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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