期刊
IEEE TRANSACTIONS ON HAPTICS
卷 10, 期 2, 页码 183-195出版社
IEEE COMPUTER SOC
DOI: 10.1109/TOH.2016.2615924
关键词
Morphological computation; active haptic perception; proprioception; robotic palpation; soft robotic probe
资金
- U.K. Engineering and Physical Sciences Research Council [EP/N03211X/1, EP/I028773/1, EP/ I028765/1]
- EPSRC [EP/N03211X/2, EP/I028773/1, EP/N03211X/1, EP/I028765/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/N03211X/1, EP/N03211X/2, EP/I028773/1, EP/I028765/1] Funding Source: researchfish
When humans are asked to palpate a soft tissue to locate a hard nodule, they regulate the stiffness, speed, and force of the finger during examination. If we understand the relationship between these behavioral variables and haptic information gain (transfer entropy) during manual probing, we can improve the efficacy of soft robotic probes for soft tissue palpation, such as in tumor localization in minimally invasive surgery. Here, we recorded the muscle co-contraction activity of the finger using EMGsensors to address the question as to whether joint stiffness control during manual palpation plays an important role in the haptic information gain. To address this question, we used a soft robotic probe with a controllable stiffness joint and a force sensor mounted at the base to represent the function of the tendon in a biological finger. Then, we trained a Markov chain using muscle co-contraction patterns of human subjects, and used it to control the stiffness of the soft robotic probe in the same soft tissue palpation task. The soft robotic experiments showed that haptic information gain about the depth of the hard nodule can be maximized by varying the internal stiffness of the soft probe.
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