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.
Highlights
Tactile sensors posses the potential of becoming an indispensable part of a modern day robotic system
Extensive experimentation was conducted in underwater and ground based environments for validating the BRICPPF based object recognition algorithms
We have proven that allowing the exploration to function independent of the current state of recognition works fine with robust object recognition being achieved in only a few exploration steps
Summary
Tactile sensors posses the potential of becoming an indispensable part of a modern day robotic system. While laser and vision sensors have proven their worth in most of the structured and even some unstructured ground based applications, their utility is inhibited by bad lighting conditions. Bad lighting conditions and water turbidity created either by dirt or by sediment stirred by the robot itself, limit the utility of laser and vision sensors. On the other hand are immune to ambient lighting conditions and water turbidity because of their intrinsic insensitivity to ambient light. They are essential for complementing the performance of vision sensors in ground based applications and are capable of performing an even larger role in underwater applications.
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