Adaptive cancelation of self-generated sensory signals in a whisking robot

Sensory signals are often caused by one's own active movements. This raises a problem of discriminating between self-generated sensory signals and signals generated by the external world. Such discrimination is of general importance for robotic systems, where operational robustness is dependent on the correct interpretation of sensory signals. Here, we investigate this problem in the context of a whiskered robot. The whisker sensory signal comprises two components: one due to contact with an object (externally generated) and another due to active movement of the whisker (self-generated). We propose a solution to this discrimination problem based on adaptive noise cancelation, where the robot learns to predict the sensory consequences of its own movements using an adaptive filter. The filter inputs (copy of motor commands) are transformed by Laguerre functions instead of the often-used tapped-delay line, which reduces model order and, therefore, computational complexity. Results from a contact-detection task demonstrate that false positives are significantly reduced using the proposed scheme

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 robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics

Chapter 10 The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics Tony J. Prescott, Ben Mitchinson, Nathan F. Lepora, Stuart P. Wilson, Sean R. Anderson, John Porrill, Paul Dean, Charles ..

An internal model architecture for novelty detection: Implications for cerebellar and collicular roles in sensory processing

The cerebellum is thought to implement internal models for sensory prediction, but details of the underlying circuitry are currently obscure. We therefore investigated a specific example of internal-model based sensory prediction, namely detection of whisker contacts during whisking. Inputs from the vibrissae in rats can be affected by signals generated by whisker movement, a phenomenon also observable in whisking robots. Robot novelty-detection can be improved by adaptive noise-cancellation, in which an adaptive filter learns a forward model of the whisker plant that allows the sensory effects of whisking to be predicted and thus subtracted from the noisy sensory input. However, the forward model only uses information from an efference copy of the whisking commands. Here we show that the addition of sensory information from the whiskers allows the adaptive filter to learn a more complex internal model that performs more robustly than the forward model, particularly when the whisking-induced interference has a periodic structure. We then propose a neural equivalent of the circuitry required for adaptive novelty-detection in the robot, in which the role of the adaptive filter is carried out by the cerebellum, with the comparison of its output (an estimate of the self-induced interference) and the original vibrissal signal occurring in the superior colliculus, a structure noted for its central role in novelty detection. This proposal makes a specific prediction concerning the whisker-related functions of a region in cerebellar cortical zone A2 that in rats receives climbing fibre input from the superior colliculus (via the inferior olive). This region has not been observed in non-whisking animals such as cats and primates, and its functional role in vibrissal processing has hitherto remained mysterious. Further investigation of this system may throw light on how cerebellar-based internal models could be used in broader sensory, motor and cognitive contexts. © 2012 Anderson et al

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

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