Back
An Adaptive Haptic Aid Based on Pilot Performance
{This paper presents an Adaptive Haptic Aid (AHA) for shared control applications. The aim of this work is to design a haptic support system that adapts the amount of aid based on pilot performance. Model Reference Adaptive Control (MRAC) is used to adapt the parameters of the haptic feedback in order to achieve a desired level of performance. A simulation study is conducted to test the adaptive system with different pilots models. Eventually, a human-in-the-loop experiment is performed to validate the AHA adaptation system. Both the simulation and the experimental results show that the amount of provided help is related to the pilot skills. Specifically, the haptic force increases when the pilot shows a lack of performance. Experimental results also show the benefits produced by using the Adaptive Haptic Aid compared to no-aided systems.}
@inproceedings{item_3016790, title = {{An Adaptive Haptic Aid Based on Pilot Performance}}, booktitle = {{Modeling and Simulation Technologies: Papers Presented at the AIAA SciTech Forum and Exposition 2019}}, abstract = {{This paper presents an Adaptive Haptic Aid (AHA) for shared control applications. The aim of this work is to design a haptic support system that adapts the amount of aid based on pilot performance. Model Reference Adaptive Control (MRAC) is used to adapt the parameters of the haptic feedback in order to achieve a desired level of performance. A simulation study is conducted to test the adaptive system with different pilots models. Eventually, a human-in-the-loop experiment is performed to validate the AHA adaptation system. Both the simulation and the experimental results show that the amount of provided help is related to the pilot skills. Specifically, the haptic force increases when the pilot shows a lack of performance. Experimental results also show the benefits produced by using the Adaptive Haptic Aid compared to no-aided systems.}}, pages = {725--733}, publisher = {Curran}, address = {San Diego, CA, USA}, year = {2019}, slug = {item_3016790}, author = {Aranella, A and D\textquotesingleIntino, G and Olivari, M and Geluardi, S and B\"ulthoff, HH and Pollini, L} }