Robust shape estimation with false-positive contact detection

We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contact-based detection method tends to induce a degree of uncertainty with false-positive contact data because the sensors ma...

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Bibliographic Details
Published in:arXiv.org 2021-04
Main Authors: Shibata, Kazuki, Miyano, Tatsuya, Jimbo, Tomohiko, Matsubara, Takamitsu
Format: Article
Language:English
Subjects:
Accelerometers
Algorithms
Gaussian process
Robustness
Sensors
Tactile sensors (robotics)
Telephone directories
Touch
Online Access:Get full text
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Summary:We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contact-based detection method tends to induce a degree of uncertainty with false-positive contact data because the sensors may react not only to actual contact but also to the unstable behavior of the robot. Therefore, it is crucial to consider a robust shape estimation method capable of handling such false-positive contact data. To realize this, we introduce the concept of heteroscedasticity into the contact data and propose a robust shape estimation algorithm based on Gaussian process implicit surfaces (GPIS). We confirmed that our algorithm not only reduces shape estimation errors caused by false-positive contact data but also distinguishes false-positive contact data more clearly than the GPIS through simulations and actual experiments using a quadcopter.
ISSN:2331-8422
DOI:10.48550/arxiv.2104.10318