Multi-source micro-friction identification for a class of cable-driven robots with passive backbone. (1st December 2016)

• Record Type: Journal Article
• Authors: Tjahjowidodo, Tegoeh; Zhu, Ke; Dailey, Wayne; Burdet, Etienne; Campolo, Domenico
• Is Part Of: Mechanical systems and signal processing. Volume 80(2016)
• Page Start: 152
• Page End: 165
• Publication Date: 2016-12-01
• Subjects: Transparent haptic interface -- Cable-driven robot with passive backbone -- Friction -- Hysteresis -- Coulomb -- LuGre; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.04.032
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: This paper analyses the dynamics of cable-driven robots with a passive backbone and develops techniques for their dynamic identification, which are tested on the H-Man, a planar cabled differential transmission robot for haptic interaction. The mechanism is optimized for human–robot interaction by accounting for the cost-benefit-ratio of the system, specifically by eliminating the necessity of an external force sensor to reduce the overall cost. As a consequence, this requires an effective dynamic model for accurate force feedback applications which include friction behavior in the system. We first consider the significance of friction in both the actuator and backbone spaces. Subsequently, we study the required complexity of the stiction model for the application. Different models representing different levels of complexity are investigated, ranging from the conventional approach of Coulomb to an advanced model which includes hysteresis. The results demonstrate each model's ability to capture the dynamic behavior of the system. In general, it is concluded that there is a trade-off between model accuracy and the model cost. Highlights: Dynamics of cable-driven robots for haptic interface is modeled. The significance of the frictional effect on the system is confirmed. We evaluate the required complexity of the friction model. The optimized models are validated experimentally with satisfactory results. Suitable models for haptic interface are identified.