Experimental Evaluation of a 2-DoF Haptic Shared Control System Based on Pilot Intent Estimation

This paper presents the experimental evaluation of a novel haptic shared control system. The proposed system was designed to help human operators to perform a maneuver that is not known in advance. A Pilot Intent Estimator (PIE) was implemented to estimate the unknown trajectory that a human pilot intends to follow. Then, a haptic feedback was designed to mimic the behavior of a skilled pilot that tracks the estimated trajectory. A human-in-the-loop experiment was performed to evaluate the developed shared control system in a 2 Degrees-of- Freedom (DoF) control task. Results showed the effectiveness of the PIE to estimate the correct pilot intended path. Furthermore, the developed haptic system helped participants to achieve better performance to follow the estimated trajectory, compared to manual control

The System Charactreistics and Performance of a Shaking Table

This work proposes an Adaptive Haptic Aid system that adapts the amount of provided aid based on actual pilot performance. This is achieved by parameterizing the haptic system and adjusting the parameters on-line to match a desired closed loop performance. The parameters of the haptic aid are adjusted using a technique known as Model Reference Adaptive Control (MRAC), which has been widely studied in past years and applied to automatic control of plants with unknown dynamics. Simulations and experimental tests with naive and expert pilots show that the proposed Adaptive Haptic Aid system represents a promising solution for haptic aid design

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