Scaling up a Boltzmann machine model of hippocampus with visual features for mobile robots

Previous papers [4], [5] have described a detailed mapping between biological hippocampal navigation and a temporal restricted Boltzmann machine [20] with unitary coherent particle filtering. These models have focused on the biological structures and used simplified microworlds in implemented examples. As a first step in scaling the model up towards practical bio-inspired robotic navigation, we present new results with the model applied to real world visual data, though still limited by a discretized configuration space. To extract useful features from visual input we apply the SURF transform followed by a new lamellae-based winner-take-all Dentate Gyrus. This new visual processing stream allows the navigation system to function without the need for a simplifying data assumption of the previous models, and brings the hippocampal model closer to being a practical robotic navigation system

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

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

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

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

Naive Bayes novelty detection for a moving robot with whiskers

Novelty detection would be a useful ability for any autonomous robot that seeks to categorize a new environment or notice unexpected changes in its present one. A biomimetic robot (SCRATCHbot) inspired by the rat whisker system was here used to examine the performance of a novelty detection algorithm based on a 'naive' implementation of Bayes rule. Naive Bayes algorithms are known to be both efficient and effective, and also have links with proposed neural mechanisms for decision making. To examine novelty detection, the robot first used its whiskers to sense an empty floor, after which it was tested with a textured strip placed in its path. Given only its experience of the familiar situation, the robot was able to distinguish the novel event and localize it in time. Performance increased with the number of whiskers, indicating benefits from integrating over multiple streams of information. Considering the generality of the algorithm, we suggest that such novelty detection could have widespread applicability as a trigger to react to important features in the robot's environment. © 2010 IEEE

Enough is not enough: Medical students’ knowledge of early warning signs of childhood cancer

Background. The reported incidence of childhood cancer in upper-middle-income South Africa (SA) is much lower than in high-income countries, partly due to under-diagnosis and under-reporting. Documented survival rates are disturbingly low, prompting an analysis of potential factors that may be responsible.Objectives. To determine final-year medical students’ level of knowledge of early warning signs of childhood cancer and whether a correlation existed between test scores and participants’ age, gender and previous exposure to a person with cancer.Methods. A two-part questionnaire based on the Saint Siluan mnemonic, testing both recall and recognition of early warning signs of childhood cancer, was administered. The Mann-Whitney-Wilcoxon test was used to assess differences in continuous and count variables between demographic data, experience and responses, and Fisher’s exact test and Spearman’s rank correlation coefficient were used to determine correlations between demographic data, previous contact with persons with cancer and test scores. A novel equality ratio was calculated to compare the recall and recognition sections and allowed analysis of recall v. recognition.Results. The 84 participants recalled a median of six signs each (interquartile range 4 - 7) and correctly recognised a median of 70% in the recognition section, considered a pass mark. There was no correlation between participants’ age, gender, previous contact with a person with cancer and recognition scores. Students with previous exposure to a person with cancer had higher scores in the recall section, but this did not achieve statistical significance. Students were able to recognise more signs of haematological malignancies than central nervous system (CNS) malignancies.Conclusion. The study demonstrated a marked inconsistency between recall and recognition of signs of childhood cancer, with signs of CNS malignancies being least recognised. However, the majority of students could recognise enough early warning signs to meet the university pass standard. Although this study demonstrated acceptable recognition of early warning signs of childhood cancer at one university, we suggest that long-term recall in medical practitioners is poor, as reflected in the low age-standardised ratios of childhood cancer in SA. We recommend increased ongoing exposure to paediatric oncology in medical school and improved awareness programmes to increase early referrals

Marked colour divergence in gliding membranes of a tropical lizard mirror population differences in the colour of falling leaves

Populations of the Bornean gliding lizard, Draco cornutus, differ markedly in the colour of their gliding membranes. They also differ in local vegetation type (mangrove forest versus lowland rainforest) and consequently, the colour of falling leaves (red and brown/black in mangrove versus green, brown and black in rainforest). We show that the gliding membranes of these lizards closely match the colours of freshly fallen leaves in the local habitat as they appear to the visual system of birds (their probable predators). Furthermore, gliding membranes more closely resembled colours of local fallen leaves than standing foliage or fallen leaves in the other population’s habitat. This suggests that the two populations have diverged in gliding membrane coloration to match the colours of their local falling leaves, and that mimicking falling leaves is an adaptation that functions to reduce predation by birds

Towards practice-based studies of HRM: an actor-network and communities of practice informed approach

HRM may have become co-terminus with the new managerialism in the rhetorical orthodoxies of the HRM textbooks and other platforms for its professional claims. However, we have detailed case-study data showing that HR practices can be much more complicated, nuanced and indeed resistive toward management within organizational settings. Our study is based on ethnographic research, informed by actor-network theory and community of practice theory conducted by one of the authors over an 18-month period. Using actor-network theory in a descriptive and critical way, we analyse practices of managerial resistance, enrolment and counter-enrolment through which an unofficial network of managers used a formal HRM practice to successfully counteract the official strategy of the firm, which was to close parts of a production site. As a consequence, this network of middle managers effectively changed top management strategy and did so through official HRM practices, coupled with other actor-network building processes, arguably for the ultimate benefit of the organization, though against the initial views of the top management. The research reported here, may be characterized as a situated study of HRM-in-practice and we draw conclusions which problematize the concept of HRM in contemporary management literature