Enhancing the Rate-Hardness of Haptic Interaction: Successive Force Augmentation Approach
| Autor: | Jee-Hwan Ryu, Bernhard Weber, Aghil Jafari, Dominik Janetzko, Chan-Il Lee, Harsimran Singh |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Stiffness physical human–robot interaction Collision rate-hardness Stability (probability) Haptics and haptic interface passivitycriterion Analyse und Regelung komplexer Robotersysteme Control and Systems Engineering medicine haptics and haptic interface passivity criterion rate-hardness physical human-robot interaction Electrical and Electronic Engineering medicine.symptom Bristol Robotics Laboratory Simulation ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | IEEE Transactions on Industrial Electronics. 67:809-819 |
| ISSN: | 1557-9948 0278-0046 |
| DOI: | 10.1109/tie.2019.2918500 |
| Popis: | © 1982-2012 IEEE. There have been numerous approaches that have been proposed to enlarge the impedance range of haptic interaction while maintaining stability. However, enhancing the rate-hardness of haptic interaction while maintaining stability is still a challenging issue. The actual perceived rate-hardness has been much lower than what the users expect to feel. In this paper, we propose the successive force augmentation (SFA) approach, which increases the impedance range by adding a feed-forward force offset to the state-dependent feedback force rendered using a low stiffness value. This allows the proposed approach to display stiffness of up to 10 N/mm with Phantom Premium 1.5. It was possible to further enhance the rate-hardness by using the original value of virtual environment stiffness for feedback force calculation during the transient response followed by normal SFA. Experimental evaluation for multi-DoF virtual environment exhibited a much higher displayed stiffness and rate-hardness compared to conventional approaches. Two user studies revealed that the increase of rate-hardness due to SFA allowed the participants to have a faster reaction time to an unexpected collision with a virtual wall and accurately discriminate between four virtual walls of different stiffness. |
| Databáze: | OpenAIRE |
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