Have a look to the photo album of the event.
– The idea we had in our lab #sirslab about using the cutaneous-only (no kinesthetic) haptic feedback in robot-assisted surgery, like the da Vinci system, was a great idea and it got the prestigious Intuitive Surgical Research Grant in 2015 (the only Italians) with a collaborative project with University of Pennsylvania (K.J. Kuchenbecker). Claudio Pacchierotti and I have been in California to present the results of the research based on our idea. We gave talks to surgeons and engineers of Intuitive Surgical in Santa Clara in the Silicon Vally and it was amazing. A lot of great conversations, ideas, and comments. We are coming back to Italy with more energy :-).
If you want to know more about the idea of cutaneous feedback in surgical robotics have a look to this paper
– L. Meli, C. Pacchierotti, D. Prattichizzo. Sensory subtraction in robot-assisted surgery: fingertip skin deformation feedback to ensure safety and improve transparency in bimanual haptic interaction. IEEE Transactions on Biomedical Engineering, 61(4):1318-1327, 2014
and to the paper where the idea has been implemented in the da Vinci System in
– C. Pacchierotti, D. Prattichizzo, K. J. Kuchenbecker. Cutaneous feedback of fingertip deformation and vibration for palpation in robotic surgery. IEEE Transactions on Biomedical Engineering. In Press, 2015
The human hand is highly versatile and easily adaptable to a variety of manipulation tasks, exposing flexible solutions to the needs of control. In daily life, humans beings are, apparently without effort, able to generate complex and elegant movements of the hand and fingers, such as typing on keyboards, playing a musical instrument, or writing.
In this paper we focus on the analysis of human hand movements during handwriting tasks, a subject which has been studied for many decades.
We present for the first time, at the best of our knowledge, a methodological approach based on the biomechanics of the human hand to compare two different input methods, i.e., the finger and the stylus, in digital handwriting tasks.
Performance of two input methods is evaluated and compared in terms of manipulability indexes in the task space, i.e., the ratio between a measure of performance (displacement, velocity, force in the task space) and a measure of effort in the input/joint space.
Beside the mathematical analysis based on a biomechanical model of the hand, two experiments are presented, in which subjects were asked to write on a touchscreen using either their index finger, or a stylus.
The results (both analytical and experimental) assess that writing with the finger is more suitable for performing large, but not very accurate motions, while writing with the stylus leads to a higher precision and more isotropic motion performance.
This post summarises our research on wearable extra fingers. We started to investigate how to enhance the capability of the human hand by means of wearable robots in 2011 . The goal was to integrate the human hand with an additional robotic finger as represented in Fig. 1. We firstly investigate the potentials of extra-finger in healthy subjects. Such devices could give humans the possibility to manipulate objects in a more efficient way, enhancing our hand grasping dexterity/ability. The first prototype has been presented in  together with several examples of the extra-finger applications. Together with the design issues related to portability and wearability of the devices, another critical aspect was integrating the motion of the extra–fingers with that of the human hand. In , we presented a mapping algorithm able to transfer to the extra–fingers a part or the whole motion of the human hand. A commercial dataglove was used to measure the hand configuration during a grasping task. A video is available here. Although this control approach guarantees a reliable tracking of the human hand, there was two main drawbacks to be solved. First, the user lacked a feedback of the robotic finger status and could only perceive the force
exerted by the device mediated by the grasped object. The second problem was related to the approaching phase of the grasp. In fact, the algorithm presented in  considers the motion of the whole hand to compute the motion of the extra finger, thus limiting the possibility of the user to make fine adjustments to adapt the finger shape to that of the grasped object. In  we addressed these issues by introducing a vibrotactile interface that can be worn as a ring. The human user receives information through the vibrotactile interface about the robotic finger status in terms of contact/no contact with the grasped object and in terms of force exerted by the device. Regarding the grasp approaching phase, we introduced a new control strategy that enables the finger to autonomously adapt to the shape of the grasped object.
The experience gained with healthy subjects was fundamental for the development of Robotic Sixth Finger for compensating hand function in chronic stroke patients. We proposed to use a robotic the Robotic Sixth Finger together with the paretic hand/arm, to constrain the motion of the object. The device can be worn on the user’s forearm by means of an elastic band. The systems acts like a two-finger gripper, where one finger is represented by the Robotic Sixth Finger, while the other by the patient’s paretic limb. The patient can regulate the finger flexion/extension through a wearable switch embedded in a ring worn on the healthy hand. Two possible predefined motions can be chosen to obtain either a precision or a power grasp. In addition to the switch, the proposed ring interface also embeds a vibrotactile motor able to provide the patient with information about the force exerted by the device. The preliminary results with patients are presented in  and a video is available here.
 O. A. Atassi, “Design of a robotic sixth finger for grasping enhancement,” Master’s thesis, Universita` degli Studi di Siena (advisor: Domenico Prattichizzo), December 2011.
 D. Prattichizzo, M. Malvezzi, I. Hussain, G. Salvietti. The Sixth-Finger: a Modular Extra-Finger to Enhance Human Hand Capabilities. In Proc. IEEE Int. Symp. in Robot and Human Interactive Communication, Pages 993-998, Edinburgh, United Kingdom, August 2014.
 D. Prattichizzo, G. Salvietti, F. Chinello, M. Malvezzi. An Object-based Mapping Algorithm to Control Wearable Robotic Extra-Fingers. In Proc. IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, Pages 1563-1568, Besançon, France, July, 2014.
 I. Hussain, L. Meli, C. Pacchierotti, G. Salvietti, D. Prattichizzo. Vibrotactile haptic fedback for intuitive control of robotic extra fingers. In Proc. IEEE World Haptics Conference (WHC), Chicago, IL, June, 2015.
 I. Hussain, G. Salvietti, L. Meli, C. Pacchierotti, D. Prattichizzo. Using the robotic sixth finger and vibrotactile feedback for grasp compensation in chronic stroke patients. In Proc. IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR), Singapore, Republic of Singapore, 2015. [Finalist for the Best Student Paper Award]
 D. Prattichizzo. The interplay between humans and robots in grasping. In Proc. International Symposium on Robotic Research, Sestri Levante, Italy, September, 2015
 I. Hussain, G. Salvietti, M. Malvezzi and D. Prattichizzo. Design guidelines for a wearable robotic extra-finger. In proc. IEEE Int. Forum on Research and Technology for Society and Industry, Turin, Italy September, 2015
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”, , 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 , and we exploit a path following control  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 , 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)
 M. Aggravi, S. Scheggi, and D. Prattichizzo – Evaluation of a predictive approach in steering the human locomotion via haptic feedback – IROS, 2015 [pdf]
 G. Arechavaleta, J.-P. Laumond, H. Hicheur, and A. Berthoz – On the nonholonomic nature of human locomotion – Autonomous Robots, 2008
 C. Canudas De Wit, G. Bastin, and B. Siciliano – Theory of robot control – Chapter 9 Nonlinear Feedback Control
 S. Scheggi, M. Aggravi, F. Morbidi, and D. Prattichizzo – Cooperative human-robot haptic navigation – ICRA, 2014, [pdf]
 S. Scheggi, F. Morbidi, and D. Prattichizzo. Human-robot formation control via visual and vibrotactile haptic feedback – IEEE Trans. on Haptics, 2014, [pdf]
 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]
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.
Despite its expected clinical benefits, current teleoperated surgical robots do not provide the surgeon with haptic feedback largely because grounded forces can destabilize the system’s closed-loop controller.
This article presents an alternative approach that enables the surgeon tofeel fingertip contact deformations and vibrations while guaranteeing the teleoperator’s stability.
We implemented our cutaneous feedback solution on an Intuitive Surgical da Vinci Standard robot by mounting a SynTouch BioTac tactile sensor to the distal end of a surgical instrument and a custom cutaneous display to the corresponding master controller. As the user probes the remote environment, the contact deformations, DC pressure, and AC pressure (vibrations) sensed by the BioTac are directly mapped to input commands for the cutaneous device’s motors using a model-free algorithm based on look-up tables. The cutaneous display continually moves, tilts, and vibrates a flat plate at the operator’s fingertip to optimally reproduce the tactile sensations experienced by the BioTac.
We tested the proposed approach by having eighteen subjects use the augmented da Vinci robot to palpate a heart model with no haptic feedback, only deformation feedback, and deformation plus vibration feedback. Fingertip deformation feedback significantly improved palpation performance by reducing the task completion time, the pressure exerted on the heart model, and the subject’s absolute error in detecting the orientation of the embedded plastic stick. Vibration feedback significantly improved palpation performance only for the seven subjects who dragged the BioTac across the model, rather than pressing straight into it.
C. Pacchierotti, D. Prattichizzo, K. J. Kuchenbecker. Cutaneous feedback of fingertip deformation and vibration for palpation in robotic surgery. IEEE Transactions on Biomedical Engineering. In Press, 2015.