Proton 2: Increasing the Sensitivity and Portability of a Visuo-haptic Surface Interaction Recorder

2017

Conference Paper

hi

The Portable Robotic Optical/Tactile ObservatioN PACKage (PROTONPACK, or Proton for short) is a new handheld visuo-haptic sensing system that records surface interactions. We previously demonstrated system calibration and a classification task using external motion tracking. This paper details improvements in surface classification performance and removal of the dependence on external motion tracking, necessary before embarking on our goal of gathering a vast surface interaction dataset. Two experiments were performed to refine data collection parameters. After adjusting the placement and filtering of the Proton's high-bandwidth accelerometers, we recorded interactions between two differently-sized steel tooling ball end-effectors (diameter 6.35 and 9.525 mm) and five surfaces. Using features based on normal force, tangential force, end-effector speed, and contact vibration, we trained multi-class SVMs to classify the surfaces using 50 ms chunks of data from each end-effector. Classification accuracies of 84.5% and 91.5% respectively were achieved on unseen test data, an improvement over prior results. In parallel, we pursued on-board motion tracking, using the Proton's camera and fiducial markers. Motion tracks from the external and onboard trackers agree within 2 mm and 0.01 rad RMS, and the accuracy decreases only slightly to 87.7% when using onboard tracking for the 9.525 mm end-effector. These experiments indicate that the Proton 2 is ready for portable data collection.

@inproceedings{Burka17-ICRA-Proton,
  title = {Proton 2: Increasing the Sensitivity and Portability of a Visuo-haptic Surface Interaction Recorder},
  author = {Burka, Alex and Rajvanshi, Abhinav and Allen, Sarah and Kuchenbecker, Katherine J.},
  booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {439--445},
  address = {Singapore},
  month = may,
  year = {2017},
  doi = {10.1109/ICRA.2017.7989057},
  month_numeric = {5}
}