Human Guidance with Wearable Haptics: the research so far in our SIRSLab

This post summarises our contributions to the research on human guidance with wearable devices. One of our recent work “Evaluation of a predictive approach in steering the human locomotion via haptic feedback”, [1], has been recently accepted for publication in the proceedings of 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015). In this work, we consider the human as an unicycle robot, following the work by Arechavaleta [2], and we exploit a path following control [3] for generating appropriate haptic (vibrotactile) cues to be applied on the user. The task here is to follow some ideal lines, with no knowledge of them. This is just one examples of the application of the wearable haptics – in this case, with vibrotactile feedack – for human guidance.

This paper is an evolution of one of our previous works [4], in which we were guiding the human considering her/him inside a mixed human-robot formation, where the role of leader and follower was, in some sense, blended. Here, vibrotactile cues were used to tune the position of the human user, so that she/he was maintaining a rigid formation w.r.t. to the robot, while it was moving toward a target.

We exploited also the idea of considering the human as leader of a mixed human-robot team [5, 6]. In these cases, the haptic feedback was used to notify the user about violations of formation constraints, so that she/he could modify her/his pace and maintain the formation.

Most of our results have received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement n. 601165 of the project “WEARHAP – WEARable HAPtics for humans and robots” and under grant agreement n. 288917 of the project “DALi – Devices for Assisted Living”, and from the European Union’s Horizon 2020 research and innovation programme – Societal Challenge 1 (DG CONNECT/H) under grant agreement n. 643644 of the project “ACANTO: A CyberphysicAl social NeTwOrk using robot friends”.

Publications/Videos/pdf also available on our website (sirslab.dii.unisi.it)

[1] M. Aggravi, S. Scheggi, and D. Prattichizzo – Evaluation of a predictive approach in steering the human locomotion via haptic feedback – IROS, 2015

[2] G. Arechavaleta, J.-P. Laumond, H. Hicheur, and A. Berthoz – On the nonholonomic nature of human locomotion – Autonomous Robots, 2008

[3] C. Canuda De Wit, G. Bastin, and B. Siciliano – Theory of robot control

[4] S. Scheggi, M. Aggravi, F. Morbidi, and D. Prattichizzo – Cooperative human-robot haptic navigation – ICRA, 2014, [pdf]

[5] S. Scheggi, F. Morbidi, and D. Prattichizzo. Human-robot formation control via visual and vibrotactile haptic feedback – IEEE Trans. on Haptics, 2014, [pdf]

[6] S. Scheggi, F. Chinello, D. Prattichizzo. Vibrotactile haptic feedback for human-robot interaction in leader-follower tasks. In Proc. ACM Int. Conf. on PErvasive Technologies Related to Assistive Environments, PETRA ’12, Pages 1-4, 2012, [pdf]

New paper accepted for publication in the Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015)

In this paper, we present a haptic guidance policy to steer the user along predefined paths and we evaluate a predictive approach to compensate actuation delays that humans have when they are guided along a given trajectory via sensory stimuli.

The proposed navigation policy exploits the nonholonomic nature of human locomotion in goal directed paths, which leads to a very simple guidance mechanism. The proposed method has been evaluated in a real scenario where seven human subjects were asked to walk along a set of predefined paths via vibrotactile cues. Their poses as well as the related distances from the path have been recorded using an accurate optical tracking system.

Results revealed that an average error of 0.24 m is achieved by using the proposed haptic policy, and that the predictive approach does not bring significant improvements to the path following problem for what concerns the distance error. On the contrary, the predictive approach achieved a definitely lower activation time of the haptic interfaces.

M. Aggravi, S. Scheggi, D. Prattichizzo. Evaluation of a predictive approach in steering the human locomotion via haptic feedback. In Proc. IEEE/RSJ International Conference Intelligent Robots and Systems. In Press, 2015.