Neuro-fuzzy estimation of passive robotic joint safe velocity with embedded sensors of conductive silicone rubber. (May 2016)

• Record Type: Journal Article
• Authors: Al-Shammari, Eiman Tamah; Petković, Dalibor; Danesh, Amir Seyed; Shamshirband, Shahaboddin; Issa, Mirna; Zentner, Lena
• Is Part Of: Mechanical systems and signal processing. Volume 72/73(2016)
• Page Start: 486
• Page End: 498
• Publication Date: 2016-05
• Subjects: Passive joint -- Compliant joint -- Head injury safety -- Robot collision -- ANFIS network; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.11.031
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: Robotic operations need to be safe for unpredictable contacts. Joints with passive compliance with springs can be used for soft robotic contacts. However the joints cannot measure external collision forces. In this investigation was developed one passive compliant joint which have soft contacts with external objects and measurement capabilities. To ensure it, conductive silicone rubber was used as material for modeling of the compliant segments of the robotic joint. These compliant segments represent embedded sensors. The conductive silicone rubber is electrically conductive by deformations. The main task was to obtain elastic absorbers for the external collision forces. These absorbers can be used for measurement in the same time. In other words, the joint has an internal measurement system. Adaptive neuro fuzzy inference system (ANFIS) was used to estimate the safety level of the robotic joint by head injury criteria (HIC). Highlights: Safe physical human–robot interaction. Passive compliant robotic joint with internal embedded sensors. Safe robotic mechanisms with an internally measuring system. Control algorithm for estimation of the maximal joint safe velocity. Adaptive neuro fuzzy application.