Conference Paper

CrunchBot: A Mobile Whiskered Robot Platform.

DOI: 10.1007/978-3-642-23232-9_10 Conference: Towards Autonomous Robotic Systems - 12th Annual Conference, TAROS 2011, Sheffield, UK, August 31 - September 2, 2011. Proceedings
Source: DBLP

ABSTRACT CrunchBot is a robot platform for developing models of tactile perception and navigation. We present the architecture of CrunchBot,
and show why tactile navigation is difficult. We give novel real-time performance results from components of a tactile navigation
system and a description of how they may be integrated at a systems level. Components include floor surface classification,
radial distance estimation and navigation. We show how tactile-only navigation differs fundamentally from navigation tasks
using vision or laser sensors, in that the assumptions about the data preclude standard algorithms (such as extended Kalman
Filters) and require brute-force methods.

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    ABSTRACT: Tactile sensing can be an important source of information for robots, and texture discrimination in particular is useful in object recognition and terrain identification. Whisker based tactile sensing has recently been shown to be a promising approach for mobile robots, using simple sensors and many classification approaches. However these approaches have often been tested in limited environments, and have not been compared against one another in a controlled way. A wide range of whisker-object contact poses are possible on a mobile robot, and the effect such contact variability has on sensing has not been properly investigated. We present a novel, carefully controlled study of simple surface texture classifiers on a large set of varied pose conditions that mimic those encountered by mobile robots. Namely, single brief whisker contacts with textured surfaces at a range of surface orientations and contact speeds. Results show that different classifiers are appropriate for different settings, with spectral template and feature based approaches performing best in surface texture, and contact speed estimation, respectively. The results may be used to inform selection of classifiers in tasks such as tactile SLAM.
    Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on; 01/2012
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    ABSTRACT: The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem for a mobile robot, CrunchBot, where only sparse, local tactile information from whisker sensors is available. To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting as a mapping algorithm. The hierarchical models require reports of whisker distance to contact and of surface orientation at contact, and we demonstrate that this information can be retrieved by classifiers from strain data collected by CrunchBot’s physical whiskers. We then provide a demonstration in simulation of how this information can be used to build maps (but not yet full SLAM) in an zero-odometry-noise environment containing walls and table-like hierarchical objects.
    Robotics and Autonomous Systems 01/2012; · 1.16 Impact Factor
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    ABSTRACT: Introduction. The Efficient coding hypothesis [1, 2] proposes that biological sensory processing has evolved to maximize the information transmitted to the brain from the environment, and should therefore be tuned to the statistics of the world. Metabolic and wiring considerations impose additional sparsity on these representations, such that the activity of individual neurons are as decorrelated as possible [3]. Efficient coding has provided a framework for understanding early sensory processing in both vision and audition, for example in explaining the receptive field properties of simple and complex cells in primary visual cortex (V1) and the tuning properties of auditory nerve fibres [4].
    Proceedings of the Second international conference on Biomimetic and Biohybrid Systems; 07/2013

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