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Task-Driven PCA-Based Design Optimization of Wearable Cutaneous Devices




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.

Author(s): Claudio Pacchierotti and Eric M. Young and Katherine J. Kuchenbecker
Journal: IEEE Robotics and Automation Letters
Volume: 3
Number (issue): 3
Pages: 2214--2221
Year: 2018
Month: July

Department(s): Haptic Intelligence
Bibtex Type: Article (article)

DOI: 10.1109/LRA.2018.2810953
Note: Presented at ICRA 2018
State: Published
URL: https://ieeexplore.ieee.org/document/8304773


  title = {Task-Driven {PCA}-Based Design Optimization of Wearable Cutaneous Devices},
  author = {Pacchierotti, Claudio and Young, Eric M. and Kuchenbecker, Katherine J.},
  journal = {IEEE Robotics and Automation Letters},
  volume = {3},
  number = {3},
  pages = {2214--2221},
  month = jul,
  year = {2018},
  note = {Presented at ICRA 2018},
  url = {https://ieeexplore.ieee.org/document/8304773},
  month_numeric = {7}