Soft Tactile Fingertip to Estimate Orientation and the Contact State of Thin Rectangular Objects
| Autor: | Muhammad Hisyam Rosle, Keung Or, Ryo Kojima, Zhongkui Wang, Shinichi Hirai |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization business.industry Computer science Mechanical Engineering 010401 analytical chemistry Biomedical Engineering Base (geometry) Process (computing) 02 engineering and technology Object (computer science) 01 natural sciences 0104 chemical sciences Computer Science Applications Human-Computer Interaction 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Orientation (geometry) Computer vision Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | IEEE Robotics and Automation Letters. 5:159-166 |
| ISSN: | 2377-3774 |
| Popis: | A soft tactile fingertip was developed to provide the contact feedback on characteristics of an object for performing automatic assembly of electronic parts, such as a thin circuit board. However, designing a tactile fingertip with simple design and minimal number of sensors that can estimate orientation and the contact state of an object is a challenging task. This letter presents the simple-structured soft fingertip sensitive to external forces. The fingertip can estimate the grasping force and orientation of a thin rectangular object, and the contact state between the object and the environment based on magnetic flux density (MFD) changes. Two Hall-effect sensors were fixed in parallel at the hard base, and four cylindrical magnets were embedded in the soft body of the fingertip. All parts except the magnets were 3D-printed to simplify the fabrication process. We applied a machine learning approach to define the relationship between the MFD of sensor outputs and object's characteristics. In addition, finite element simulations were performed to evaluate the designed structure. Experimental results verified that the proposed fingertip can estimate the orientation and gripping force of thin rectangular objects. Furthermore, it can successfully classify contact states of the grasped object based on the sensor outputs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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