Contact

Francesco Bufalo

Address: Spemannstr. 38
72076 Tübingen
Room number: 105
Phone: +49 7071 601 602
Fax: +49 7071 601 616
E-Mail: francesco.bufalo

 

Picture of Bufalo, Francesco

Francesco Bufalo

Position: PhD Student  Unit: Bülthoff

I recently graduated in Robotics and Automation Engineering from the University of Pisa. Now I am working as a PhD student with Human perception, cognition and action group (Heinrich H. Bülthoff). My research is focused on Force-Stiffness Haptic Feedback for learning helicopter maneuvers.

A study on Force-Stiffness Haptic Feedback for learning helicopter maneuvers

 

Introduction

Haptic systems have been recently used as support systems to the human operator for learning specific control tasks [1], [2]. In these works, participants were trained with a constant haptic feedback, removed in a following evaluation session. Results showed benefits from the haptic training, but a degradation of performance was noticed once the haptic aid was switched off. A possible solution to significantly reduce the degradation of performance would be to gradually decrease the amount of aid given to the human operator. This can be achieved with a variable Force-Stiffness Haptic Feedback, based on amount of help given to the participant and authority of the participant to oppose the provided help.

In difficult control tasks like performing helicopter maneuvers, haptic feedbacks can stimulate the learning process by showing possible right control strategies to the human operator.

 

Goals

The goal of this project is to design and test a new variable Force-Stiffness Haptic Feedback for learning helicopter maneuvers. Starting from a first test with the novel training in 1 DoF, I will then progressively extend the novel training to all the helicopter controls.

 

Methods

The new variable Force-Stiffness Haptic Feedback is based on two design parameters: amount of help given to the human operator, designed to provide similar control actions to those provided by an expert pilot, and authority of the participant to oppose the provided help. These two parameters are represented, respectively, by the desired deflection of the control device and the stiffness of the control device. The new training is tested in human-in-the-loop experiments, using fixed and motion simulators. In the experiments, participants perform a first training phase with haptics and a following evaluation phase without external aids.

 

Initial results

The new training have been already designed and tested for learning a disturbance rejection task in 1 DoF (roll axis). In a human-in-the-loop experiment, participants were split into three groups: variable haptic aid (VHA), constant haptic aid (CHA) and no haptic aid (NoHA). The VHA and CHA groups performed a first training phase with variable and constant haptic feedback respectively, followed by an evaluation phase without external aids. The NoHA group performed the entire experiment without external aids. Results showed overall better performance of the VHA group than the CHA and NoHA groups. In the evaluation phase, the participants of the VHA group were able to quickly recover performance similar to those obtained in the last trials of the training. Moreover, small variability of performance was obtained between participants of this group.

 

Initial conclusion

The experiment showed greater benefits from the new variable haptic training. The good results encourage new tests in experiments with more DoF, to gradually extend the training to more complex control tasks like helicopter maneuvers.

 

References

[1]  G. D’Intino, M. Olivari, S. Geluardi, J. Venrooij, M. Innocenti, H. H.Bülthoff, and L. Pollini (2016) Evaluation of haptic support system for training purposes in a tracking task, 2016 IEEE International Conference on Systems, Man and Cybernetics 002 169–002 174.

 

[2]  G. D’Intino, M. Olivari, S. Geluardi, J. Venrooij, L. Pollini and H. H.Bülthoff (2017) Experimental evaluation of haptic support system for learning a 2-dof tracking task, AIAA Modeling and Simulation Technologies conference.

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Conference papers (1):

Bufalo F, Olivari M, Geluardi S, Gerboni CA, Pollini L and Bülthoff HH (October-2017) Variable Force-Stiffness Haptic Feedback for Learning a Disturbance Rejection Task, IEEE International Conference on Systems, Man, and Cybernetics (SMC 2017), 1517-1522.

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Last updated: Monday, 22.05.2017