Whiskered texture classification with uncertain contact pose geometry

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

Whisking with robots from rat vibrissae to biomimetic technology for active touch

This article summarizes some of the key features of the rat vibrissal system, including the actively controlled sweeping movements of the vibrissae known as whisking, and reviews the past and ongoing research aimed at replicating some of this functionality in biomimetic robots

The effect of whisker movement on radial distanceestimation: A case study in comparative robotics

Whisker movement has been shown to be under active control in certain specialistanimals such as rats and mice. Though this whisker movement is well characterized,the role and effect of this movement on subsequent sensing is poorly understood. Onemethod for investigating this phenomena is to generate artificial whisker deflections withrobotic hardware under different movement conditions. A limitation of this approachis that assumptions must be made in the design of any artificial whisker actuators,which will impose certain restrictions on the whisker-object interaction. In this paperwe present three robotic whisker platforms, each with different mechanical whiskerproperties and actuation mechanisms. A feature-based classifier is used to simultaneouslydiscriminate radial distance to contact and contact speed for the first time. We showthat whisker-object contact speed predictably affects deflection magnitudes, invariantof whisker material or whisker movement trajectory. We propose that rodent whiskercontrol allows the animal to improve sensing accuracy by regulating contact speed inducedtouch-to-touch variability

Whisker-object contact speed affects radial distance estimation

Whiskered mammals such as rats are experts in tactile perception. By actively palpating surfaces with their whiskers, rats and mice are capable of acute texture discrimination and shape perception. We present a novel system for investigating whisker-object contacts repeatably and reliably. Using an XY positioning robot and a biomimetic artificial whisker we can generate signals for different whisker-object contacts under a wide range of conditions. Our system is also capable of dynamically altering the velocity and direction of the contact based on sensory signals. This provides a means for investigating sensory motor interaction in the tactile domain. Here we implement active contact control, and investigate the effect that speed has on radial distance estimation when using different features for classification. In the case of a moving object contacting a whisker, magnitude of deflection can be ambiguous in distinguishing a nearby object moving slowly from a more distant object moving rapidly. This ambiguity can be resolved by finding robust features for contact speed, which then informs classification of radial distance. Our results are verified on a dataset from SCRATCHbot, a whiskered mobile robot. Building whiskered robots and modelling these tactile perception capabilities would allow exploration and navigation in environments where other sensory modalities are impaired, for example in dark, dusty or loud environments such as disaster areas. © 2010 IEEE

Optimal decision-making in mammals : insights from a robot study of rodent texture discrimination

Texture perception is studied here in a physical model of the rat whisker system consisting of a robot equipped with a biomimetic vibrissal sensor. Investigations of whisker motion in rodents have led to several explanations for texture discrimination, such as resonance or stick-slips. Meanwhile, electrophysiological studies of decision-making in monkeys have suggested a neural mechanism of evidence accumulation to threshold for competing percepts, described by a probabilistic model of Bayesian sequential analysis. For our robot whisker data, we find that variable reaction-time decision-making with sequential analysis performs better than the fixed response-time maximum-likelihood estimation. These probabilistic classifiers also use whatever available features of the whisker signals aid the discrimination, giving improved performance over a single-feature strategy, such as matching the peak power spectra of whisker vibrations. These results cast new light on how the various proposals for texture discrimination in rodents depend on the whisker contact mechanics and suggest the possibility of a common account of decision-making across mammalian species

Towards hierarchical blackboard mapping on a whiskered robot

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. © 2012 Elsevier B.V. All rights reserved

Tactile Discrimination Using Template Classifiers: Towards a Model of Feature Extraction in Mammalian Vibrissal Systems

Rats and other whiskered mammals are capable of making sophisticated sensory discriminations using tactile signals from their facial whiskers (vibrissae). As part of a programme of work to develop biomimetic technologies for vibrissal sensing, including whiskered robots, we are devising algorithms for the fast extraction of object parameters from whisker deflection data. Previous work has demonstrated that radial distance to contact can be estimated from forces measured at the base of the whisker shaft. We show that in the case of a moving object contacting a whisker, the measured force can be ambiguous in distinguishing a nearby object moving slowly from a more distant object moving rapidly. This ambiguity can be resolved by simultaneously extracting object position and speed from the whisker deflection time series – that is by attending to the dynamics of the whisker’s interaction with the object. We compare a simple classifier with an adaptive EM (Expectation Maximisation) classifier. Both systems are effective at simultaneously extracting the two parameters, the EM-classifier showing similar performance to a handpicked template classifier. We propose that adaptive classification algorithms can provide insights into the types of computations performed in the rat vibrissal system when the animal is faced with a discrimination task

CrunchBot : a mobile whiskered robot platform

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

Naive Bayes texture classification applied to whisker data from a moving robot

Many rodents use their whiskers to distinguish objects by surface texture. To examine possible mechanisms for this discrimination, data from an artificial whisker attached to a moving robot was used to test texture classification algorithms. This data was examined previously using a template-based classifier of the whisker vibration power spectrum [1]. Motivated by a proposal about the neural computations underlying sensory decision making [2], we classified the raw whisker signal using the related ‘naive Bayes’ method. The integration time window is important, with roughly 100ms of data required for good decisions and 500ms for the best decisions. For stereotyped motion, the classifier achieved hit rates of about 80% using a single (horizontal or vertical) stream of vibration data and 90% using both streams. Similar hit rates were achieved on natural data, apart from a single case in which the performance was only about 55%. Therefore this application of naive Bayes represents a biologically motivated algorithm that can perform well in a real-world robot task

A Biologically Inspired Controllable Stiffness Multimodal Whisker Follicle

This thesis takes a soft robotics approach to understand the computational role of a soft whisker follicle with mechanisms to control the stiffness of the whisker. In particular, the thesis explores the role of the controllable stiffness whisker follicle to selectively favour low frequency geometric features of an object or the high frequency texture features of the object.Tactile sensing is one of the most essential and complex sensory systems for most living beings. To acquire tactile information and explore the environment, animals use various biological mechanisms and transducing techniques. Whiskers, or vibrissae are a form of mammalian hair, found on almost all mammals other than homo sapiens. For many mammals, and especially rodents, these whiskers are essential as a means of tactile sensing.The mammalian whisker follicle contains multiple sensory receptors strategically organised to capture tactile sensory stimuli of different frequencies via the vibrissal system. Nocturnal mammals such as rats heavily depend on whisker based tactile perception to find their way through burrows and identify objects. There is diversity in the whiskers in terms of the physical structure and nervous innervation. The robotics community has developed many different whisker sensors inspired by this biological basis. They take diverse mechanical, electronic, and computational approaches to use whiskers to identify the geometry, mechanical properties, and objects' texture. Some work addresses specific object identification features and others address multiple features such as texture and shape etc. Therefore, it is vital to have a comprehensive discussion of the literature and to understand the merits of bio-inspired and pure-engineered approaches to whisker-based tactile perception.The most important contribution is the design and use of a novel soft whisker follicle comprising two different frequency-dependent data capturing modules to derive more profound insights into the biological basis of tactile perception in the mammalian whisker follicle. The new insights into the biological basis of tactile perception using whiskers provide new design guidelines to develop efficient robotic whiskers