This paper describes the development of a new biorobotic platform inspired by the lamprey. Design, fabrication and implemented control are all based on biomechanical and neuroscientific findings on this eel-like fish. The lamprey model has been extensively studied and characterized in recent years because it possesses all basic functions and control mechanisms of higher vertebrates, while at the same time having fewer neurons and simplified neural structures. The untethered robot has a flexible body driven by compliant actuators with proprioceptive feedback. It also has binocular vision for vision-based navigation. The platform has been successfully and extensively experimentally tested in aquatic environments, has high energy efficiency and is ready to be used as investigation tool for high level motor tasks.

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

New bilayered composite systems with tunable and temperature-dependent formation of periodical wrinkles on the surface are the object of this report. The samples were prepared by spin-coating deposition of a thin film of the conducting polymer poly(ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) on the surface of standard monodomain liquid crystal elastomer (LCE) films. Several bilayered materials were prepared by changing the thickness of PEDOT:PSS nanofilms. Basic characterization showed very good stability and adhesion between the two components also after performing multiple heat cycles around nematic-to-isotropic transition temperature of the LCE. Interestingly, formation of uniaxially aligned microwrinkles was observed, with most of the wrinkles aligned along perpendicular direction with respect to the nematic director, due to reversible elongation/compression of the LCE during thermal cycles

The bioinspired approach has been key in combining the disciplines of robotics with neuroscience in an effective and promising fashion. Indeed, certain aspects in the field of neuroscience, such as goal-directed locomotion and behaviour selection, can be validated through robotic artefacts. In particular, swimming is a functionally important behaviour where neuromuscular structures, neural control architecture and operation can be replicated artificially following models from biology and neuroscience. In this article, we present a biomimetic system inspired by the lamprey, an early vertebrate that locomotes using anguilliform swimming. The artefact possesses extra- and proprioceptive sensory receptors, muscle-like actuation, distributed embedded control and a vision system. Experiments on optimised swimming and on goal-directed locomotion are reported, as well as the assessment of the performance of the system, which shows high energy efficiency and adaptive behaviour. While the focus is on providing a robotic platform for testing biological models, the reported system can also be of major relevance for the development of engineering system applications.

ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Control September 2014Abstract. Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input-output data (voltagedisplacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input (NARX) structure. Frequency response analysis of the DEA dynamics was performed using generalised frequency response functions (GFRFs), providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics.

Effective tactile sensing for artificial platforms remains an open issue in robotics. This study investigates the performance of a soft biologically-inspired artificial fingertip in active exploration tasks. The fingertip sensor replicates the mechanisms within human skin and offers a robust solution that can be used both for tactile sensing and gripping/manipulating objects. The softness of the optical sensor's contact surface also allows safer interactions with objects. High-level tactile features such as edges are extrapolated from the sensor's output and the information is used to generate a tactile image. The work presented in this paper aims to investigate and evaluate this artificial fingertip for 2D shape reconstruction. The sensor was mounted on a robot arm to allow autonomous exploration of different objects. The sensor and a number of human participants were then tested for their abilities to track the raised perimeters of different planar objects and compared. By observing the technique and accuracy of the human subjects, simple but effective parameters were determined in order to evaluate the artificial system's performance. The results prove the capability of the sensor in such active exploration tasks, with a comparable performance to the human subjects despite it using tactile data alone whereas the human participants were also able to use proprioceptive cues.

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In this work a new bi-layered composite actuator based on a polysiloxane-based monodomain nematic Liquid Crystal Elastomer (LCE) and on a conductive PEDOT:PSS thin layer is proposed. The basic idea is to integrate electroconductive properties in the LCE and to validate the feasibility of direct actuation of the LCE by Joule heating of the conductive (and compliant) PEDOT:PSS layer. The fabrication of the actuator is achieved by depositing a thin conductive polymer layer by drop casting a PEDOT:PSS waterborne solution after having increased the LCE surface wettability with an air plasma treatment. The excellent stability of PEDOT:PSS and its mechanical properties, better matched with LCE ones compared to metals or inorganic nanoparticles used in other approaches, allowed to develop an all-organic reliable actuating composite based on thermoresponsive properties of LCE. Thermal actuation via direct Joule heating of the composite has been verified and prototypes of LCE/PEDOT:PSS bending actuators have been preliminary tested