High resolution pressure sensing using sub-pixel shifts on low resolution load-sensing tiles

Mihai Andries (1, 2) , François Charpillet (2) , Olivier Simonin (3, 4, 5)

1 UL - Université de Lorraine
2 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
3 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
4 Université de Lyon
5 CITI - CITI Centre of Innovation in Telecommunications and Integration of services

In ambient intelligence, pressure sensing can be used for detecting and recognizing objects based on their load profile. This paper presents a pressure scanning technique that improves weight-based object recognition, by adding information about the surface of the object in contact with the floor. The new high-resolution pressure scanning technique employs sub-pixel shifting to assemble a series of low-resolution scans into an aggregated high-resolution scan. The proposed scanning device is composed of 4 load-sensing tiles, on which the scanned object slides in regular movements. The result is a regular grid image of the object's contact surface, containing the weight of each section of the grid, as well as the corresponding centers of mass. A formal proof-of-concept is provided, together with experimental results obtained both on a noiseless simulated platform, and on a noisy physical platform.

Mots clés: Load sensing; Sensing floor

Domaines: Intelligence artificielle [cs.AI]; Robotique [cs.RO]

Mihai Andries, François Charpillet, Olivier Simonin. High resolution pressure sensing using sub-pixel shifts on low resolution load-sensing tiles. 2015 IEEE International Conference on Robotics and Automation (ICRA 2015), May 2015, Seattle, United States. ⟨hal-01136255⟩