Sensors 2014, 14(2), 3227-3266; doi:10.3390/s140203227
Article

Object Recognition and Localization: The Role of Tactile Sensors

1,* email and 1,2email
Received: 23 December 2013; in revised form: 31 January 2014 / Accepted: 8 February 2014 / Published: 18 February 2014
(This article belongs to the Special Issue Tactile Sensors and Sensing Systems)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.
Keywords: haptic object recognition; tactile sensor; database matching; object exploration; biological exploration; particle filter; edge following; tactile images; recognition by parts; underwater recognition
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MDPI and ACS Style

Aggarwal, A.; Kirchner, F. Object Recognition and Localization: The Role of Tactile Sensors. Sensors 2014, 14, 3227-3266.

AMA Style

Aggarwal A, Kirchner F. Object Recognition and Localization: The Role of Tactile Sensors. Sensors. 2014; 14(2):3227-3266.

Chicago/Turabian Style

Aggarwal, Achint; Kirchner, Frank. 2014. "Object Recognition and Localization: The Role of Tactile Sensors." Sensors 14, no. 2: 3227-3266.

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