Tactile-Based Insertion for Dense Box-Packing
Name
1909.05426.pdf
Description
Submitted version
Size
1.94 MB
Format
Adobe PDF
Checksum (MD5)
8f806f6e8ddd9d6655a62d9ae1985bd8
Author(s)
Dong, Siyuan
Rodriguez, Alberto
Date Issued
November 2019
Journal
IEEE Proceedings of the International Conference on Intelligent Robots and Systems
Publisher
IEEE
Citation
Dong, Siyuan and Alberto Rodriguez "Tactile-based insertion for dense box-packing." IEEE Proceedings of the International Conference on Intelligent Robots and Systems, Macau, China, (November 2019). International Conference on Intelligent Robots and Systems, 2019 © 2019 IEEE.
Version
Original manuscript
Abstract
We study the problem of using high-resolution tactile sensors to control the insertion of objects in a box-packing scenario. In this paper, we propose an insertion strategy that leverages tactile sensing to: 1) safely probe the box with the grasped object while monitoring incipient slip to maintain a stable grasp on the object. 2) estimate and correct for residual position uncertainties to insert the object into a designated gap without disturbing the environment. Our proposed methodology is based on two neural networks that estimate the error direction and error magnitude, from a stream of tactile imprints, acquired by two GelSlim fingers, during the insertion process. The system is trained on four objects with basic geometric shapes, which we show generalizes to four other common objects. Based on the estimated positional errors, a heuristic controller iteratively adjusts the position of the object and eventually inserts it successfully without requiring prior knowledge of the geometry of the object. The key insight is that dense tactile feedback contains useful information with respect to the contact interaction between the grasped object and its environment. We achieve high success rate and show that unknown objects can be inserted with an average of 6 attempts of the probe-correct loop. The method's ability to generalize to novel objects makes it a good fit for box packing in warehouse automation.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IROS40897.2019.8968204
