IEEE Transactions on Haptics, 13(1):144-151, January 2020, Katherine J. Kuchenbecker and Claudio Pacchierotti contributed equally to this publication. (article)
Fingertip haptic feedback offers advantages in many applications, including robotic teleoperation, gaming, and training. However, ﬁngertip size and shape vary signiﬁcantly across humans, making it difﬁcult to design ﬁngertip interfaces and rendering techniques suitable for everyone. This article starts with an existing data-driven haptic rendering algorithm that ignores ﬁngertip size, and it then develops two software-based approaches to personalize this algorithm for ﬁngertips of different sizes using either additional data or geometry. We evaluate our algorithms in the rendering of pre-recorded tactile sensations onto rubber casts of six different ﬁngertips as well as onto the real ﬁngertips of 13 human participants. Results on the casts show that both approaches signiﬁcantly improve performance, reducing force error magnitudes by an average of 78% with respect to the standard non-personalized rendering technique. Congruent results were obtained for real ﬁngertips, with subjects rating each of the two personalized rendering techniques signiﬁcantly better than the standard non-personalized method.
IEEE Transactions on Haptics, 12(3):295-306, June 2019 (article)
Existing ﬁngertip haptic devices can deliver different subsets of tactile cues in a compact package, but we have not yet seen a wearable six-degree-of-freedom (6-DOF) display. This paper presents the Fuppeteer (short for Fingertip Puppeteer), a device that is capable of controlling the position and orientation of a ﬂat platform, such that any combination of normal and shear force can be delivered at any location on any human ﬁngertip. We build on our previous work of designing a parallel continuum manipulator for ﬁngertip haptics by presenting a motorized version in which six ﬂexible Nitinol wires are actuated via independent roller mechanisms and proportional-derivative controllers. We evaluate the settling time and end-effector vibrations observed during system responses to step inputs. After creating a six-dimensional lookup table and adjusting simulated inputs using measured Jacobians, we show that the device can make contact with all parts of the ﬁngertip with a mean error of 1.42 mm. Finally, we present results from a human-subject study. A total of 24 users discerned 9 evenly distributed contact locations with an average accuracy of 80.5%. Translational and rotational shear cues were identiﬁed reasonably well near the center of the ﬁngertip and more poorly around the edges.
IEEE Robotics and Automation Letters, 3(3):2214-2221, July 2018, Presented at ICRA 2018 (article)
Small size and low weight are critical requirements for wearable and portable haptic interfaces, making it essential to work toward the optimization of their sensing and actuation systems. This paper presents a new approach for task-driven design optimization of fingertip cutaneous haptic devices. Given one (or more) target tactile interactions to render and a cutaneous device to optimize, we evaluate the minimum number and best configuration of the device’s actuators to minimize the estimated haptic rendering error. First, we calculate the motion needed for the original cutaneous device to render the considered target interaction. Then, we run a principal component analysis (PCA) to search for possible couplings between the original motor inputs, looking also for the best way to reconfigure them. If some couplings exist, we can re-design our cutaneous device with fewer motors, optimally configured to render the target tactile sensation. The proposed approach is quite general and can be applied to different tactile sensors and cutaneous devices. We validated it using a BioTac tactile sensor and custom plate-based 3-DoF and 6-DoF fingertip cutaneous devices, considering six representative target tactile interactions. The algorithm was able to find couplings between each device’s motor inputs, proving it to be a viable approach to optimize the design of wearable and portable cutaneous devices. Finally, we present two examples of optimized designs for our 3-DoF fingertip cutaneous device.
In Proceedings of the IEEE World Haptics Conference (WHC), pages: 599-604, Munich, Germany, June 2017, Finalist for best poster paper (inproceedings)
Despite rapid advancements in the field of fingertip haptics, rendering tactile cues with six degrees of freedom (6 DOF) remains an elusive challenge. In this paper, we investigate the potential of displaying fingertip haptic sensations with a 6-DOF parallel continuum manipulator (PCM) that mounts to the user's index finger and moves a contact platform around the fingertip. Compared to traditional mechanisms composed of rigid links and discrete joints, PCMs have the potential to be strong, dexterous, and compact, but they are also more complicated to design. We define the design space of 6-DOF parallel continuum manipulators and outline a process for refining such a device for fingertip haptic applications. Following extensive simulation, we obtain 12 designs that meet our specifications, construct a manually actuated prototype of one such design, and evaluate the simulation's ability to accurately predict the prototype's motion. Finally, we demonstrate the range of deliverable fingertip tactile cues, including a normal force into the finger and shear forces tangent to the finger at three extreme points on the boundary of the fingertip.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems