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

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

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

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

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

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 SLAM with a biomimetic whiskered robot

Future robots may need to navigate where visual sensors fail. Touch sensors provide an alternative modality, largely unexplored in the context of robotic map building. We present the first results in grid based simultaneous localisation and mapping (SLAM) with biomimetic whisker sensors, and show how multi-whisker features coupled with priors about straight edges in the world can boost its performance. Our results are from a simple, small environment but are intended as a first baseline to measure future algorithms against

Perception of tactile vibrations and a putative neuronal code

We devised a delayed comparison task, appropriate for human and rats, in which subjects discriminate between pairs of vibration delivered either to their whiskers, in rats, or fingertips, in humans, with a delay inserted between the two stimuli. Stimuli were composed of a random time series of velocity values (\u201cnoise\u201d) taken from a Gaussian distribution with 0 mean and standard deviation referred to as \u3c31 for the first stimulus and \u3c32 for the second stimulus. The subject must select a response depending on the two vibrations\u2019 relative standard deviations, \u3c31>\u3c32 or \u3c31<\u3c32. In the standard condition, the base and comparison stimuli both had duration of 400 ms and they were separated by a 800 ms pause. In this condition, humans had better performance than did rats on average, yet the best rats were better than the worst humans. To learn how signals are integrated over time, we varied the duration of the second stimulus. In rats, the performance was progressively improved when the comparison stimulus duration increased from 200 to 400 and then to 600 ms. In humans, the effect of comparison stimulus duration was different: an increase in duration did not improve their performance but biased their choice. Stimuli of longer duration were perceived as having a larger value of \u3c3. We employed a novel psychophysical reverse correlation method to find out which kinematic features of the stochastic stimulus influenced the choices of the subjects. This analysis revealed that rats rely principally on features related to velocity and speed values normalized by stimulus duration \u2013 that is, the rate of velocity and speed features per unit time. In contrast, while human subjects used velocity- and speed-related features, they tended to be influenced by the summated values of those features over time. The summation strategy in humans versus the rate strategy in rats accounts for both (i) the lack of improvement in humans for greater stimulus durations and (ii) the bias by which they judged longer stimuli as having a greater value of \u3c3. Next, we focused on the capacity of rats to accomplish a task of parametric working memory, a capacity until now not found in rodents. For delays between the base and comparison stimuli of up to 6-10 seconds, humans and rats showed similar performance. However when the difference in \u3c3 was small, the rats\u2019 performance began to decay over long inter-stimulus delays more markedly than did the humans\u2019 performance. The next chapter reports the analyses of the activity of barrel cortex neurons during the vibration comparison task. 35% of sampled neuron clusters showed a significant change in firing rate as \u3c3 varied, and the change was positive in every case \u2013 the slope of firing rate versus \u3c3 was positive. We used methods related to signal detection theory to estimate the behavioral performance that could be supported by single neuron clusters and found that the resulting \u201cneurometric\u201d curve was much less steep performance than the psychometric curve (the performance of the whole rat). This led to the notion that stimuli are encoded by larger populations. A general linear model (GLM) that combined multiple simultaneously recorded 2 clusters performed much better than single clusters and began to approach animal performance. We conclude that a potential code for the stimulus is the variation in firing rate according to \u3c3, distributed across large populations.In conclusion, this thesis characterizes the perceptual capacities of humans and rats in a novel working memory task. Both humans and rats can extract the statistical structure of a \u201cnoisy\u201d tactile vibration, but seem to integrate signals by different operations. A major finding is that rats are endowed with a capacity to hold stimulus parameters in working memory with a proficiency that, until now, could be ascribed only to primates. The statistical properties of the stimulus appear to be encoded by a distributed population

Biomechanical Texture Coding and Transmission of Texture Information in Rat Whiskers

Classically, texture discrimination has been thought to be based on ‘global’ codes, i.e. frequency (signal analysis based on Fourier analysis) or intensity (signal analysis based on averaging), which both rely on integration of the vibrotactile signal across time and/or space. Recently, a novel ‘local’ coding scheme based on the waveform of frictional movements, discrete short- lasting kinematic events (i.e. stick-slip movements called slips) has been formulated. In the first part of my study I performed biomechanical measurements of relative movements of a rat vibrissa across sandpapers of different roughness. My major finding is that the classic global codes convey some information about texture identity but are consistently outperformed by the slip-based local code. Moreover, the slip code also surpasses the global ones in coding for active scanning parameters. This is remarkable as it suggests that the slip code would explicitly allow the whisking rat to optimize perception by selecting goal-specific scanning strategies. I therefore provide evidence that short stick-slip events may contribute to the perceptual mechanism by which rodent vibrissa code surface roughness. In the second part, I studied the biomechanics of how such events are transmitted from tip to follicle where mechano-transduction occurs. For this purpose, ultra-fast videography recording of the entire beam of a plucked rat whisker rubbing across sandpaper was employed. I found that slip events are conveyed almost instantly from tip to follicle while amplifying moments by a factor of about 1000. From these results, I argue that the mechanics of the whisker serve as a passive amplification device that faithfully represents stick-slip events to the neuronal receptors. Using measures of correlation, I moreover found that amongst the kinematic 8 variables, acceleration portrays dynamic variables (forces) best. The time series of acceleration at the base of the whisker provided a fair proxy to the time series of forces (dynamical variables) acting on the whisker base. Acceleration measurements (easily done via videography) may therefore provide an access to at least the relative amplitude of forces. This may be important for future work in behaving animals, where dynamical variables are notoriously difficult to measure