5 March 2018 Tactile sensor of hardness recognition based on magnetic anomaly detection
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Proceedings Volume 10710, Young Scientists Forum 2017; 107102J (2018) https://doi.org/10.1117/12.2317715
Event: Young Scientists Forum 2017, 2017, Shanghai, China
Hardness, as one kind of tactile sensing, plays an important role in the field of intelligent robot application such as gripping, agricultural harvesting, prosthetic hand and so on. Recently, with the rapid development of magnetic field sensing technology with high performance, a number of magnetic sensors have been developed for intelligent application. The tunnel Magnetoresistance(TMR) based on magnetoresistance principal works as the sensitive element to detect the magnetic field and it has proven its excellent ability of weak magnetic detection. In the paper, a new method based on magnetic anomaly detection was proposed to detect the hardness in the tactile way. The sensor is composed of elastic body, ferrous probe, TMR element, permanent magnet. When the elastic body embedded with ferrous probe touches the object under the certain size of force, deformation of elastic body will produce. Correspondingly, the ferrous probe will be forced to displace and the background magnetic field will be distorted. The distorted magnetic field was detected by TMR elements and the output signal at different time can be sampled. The slope of magnetic signal with the sampling time is different for object with different hardness. The result indicated that the magnetic anomaly sensor can recognize the hardness rapidly within 150ms after the tactile moment. The hardness sensor based on magnetic anomaly detection principal proposed in the paper has the advantages of simple structure, low cost, rapid response and it has shown great application potential in the field of intelligent robot.
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Lingyun Xue, Lingyun Xue, Dongfang Zhang, Dongfang Zhang, Qingguang Chen, Qingguang Chen, Huanle Rao, Huanle Rao, Ping Xu, Ping Xu, } "Tactile sensor of hardness recognition based on magnetic anomaly detection", Proc. SPIE 10710, Young Scientists Forum 2017, 107102J (5 March 2018); doi: 10.1117/12.2317715; https://doi.org/10.1117/12.2317715

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