A lightweight,inexpensive robotic system for insect vision

Designing hardware for miniaturized robotics which mimics the capabilities of flying insects is of interest, because they share similar constraints (i.e. small size, low weight, and low energy consumption). Research in this area aims to enable robots with similarly efficient flight and cognitive abilities. Visual processing is important to flying insects' impressive flight capabilities, but currently, embodiment of insect-like visual systems is limited by the hardware systems available. Suitable hardware is either prohibitively expensive, difficult to reproduce, cannot accurately simulate insect vision characteristics, and/or is too heavy for small robotic platforms. These limitations hamper the development of platforms for embodiment which in turn hampers the progress on understanding of how biological systems fundamentally work. To address this gap, this paper proposes an inexpensive, lightweight robotic system for modelling insect vision. The system is mounted and tested on a robotic platform for mobile applications, and then the camera and insect vision models are evaluated. We analyse the potential of the system for use in embodiment of higher-level visual processes (i.e. motion detection) and also for development of navigation based on vision for robotics in general. Optic flow from sample camera data is calculated and compared to a perfect, simulated bee world showing an excellent resemblance.     

Animal colour vision--behavioural tests and physiological concepts

Over a century ago workers such as J. Lubbock and K. von Frisch developed behavioural criteria for establishing that non‐human animals see colour. Many animals in most phyla have since then been shown to have colour vision. Colour is used for specific behaviours, such as phototaxis and object recognition, while other behaviours such as motion detection are colour blind. Having established the existence of colour vision, research focussed on the question of how many spectral types of photoreceptors are involved. Recently, data on photoreceptor spectral sensitivities have been combined with behavioural experiments and physiological models to study systematically the next logical question: ‘what neural interactions underlie colour vision ?‘This review gives an overview of the methods used to study animal colour vision, and discusses how quantitative modelling can suggest how photoreceptor signals are combined and compared to allow for the discrimination of biologically relevant stimuli.     

Control theoretic interpretation of directional motion preferences in optic flow processing interneurons

In this article, we formalize the processing of optic flow in identified fly lobula plate tangential cells and develop a control theoretic framework that suggests how the signals of these cells may be combined and used to achieve reflex-like navigation behavior. We show that this feedback gain synthesis task can be cast as a combined static state estimation and linear feedback control problem. Our framework allows us to analyze and determine the relationship between optic flow measurements and actuator commands, which greatly simplifies the implementation of biologically inspired control architectures on terrestrial and aerial robotic platforms.     

Introduced species as evolutionary traps

Invasive species can alter environments in such a way that normal behavioural decision‐making rules of native species are no longer adaptive. The evolutionary trap concept provides a useful framework for predicting and managing the impact of harmful invasive species. We discuss how native species can respond to changes in their selective regime via evolution or learning. We also propose novel management strategies to promote the long‐term co‐existence of native and introduced species in cases where the eradication of the latter is either economically or biologically unrealistic.     

A bioinspired autonomous swimming robot as a tool for studying goal-directed locomotion

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.     

On the role of emotion in biological and robotic autonomy

This paper reviews some of the differences between notions of biological and robotic autonomy, and how these differences have been reflected in discussions of embodiment, grounding and other concepts in AI and autonomous robotics. Furthermore, the relations between homeostasis, emotion and embodied cognition are discussed as well as recent proposals to model their interplay in robots, which reflects a commitment to a multi-tiered affectively/emotionally embodied view of mind that takes organismic embodiment more serious than usually done in biologically inspired robotics.     

Independent Component Analysis in Spiking Neurons

Although models based on independent component analysis (ICA) have been successful in explaining various properties of sensory coding in the cortex, it remains unclear how networks of spiking neurons using realistic plasticity rules can realize such computation. Here, we propose a biologically plausible mechanism for ICA-like learning with spiking neurons. Our model combines spike-timing dependent plasticity and synaptic scaling with an intrinsic plasticity rule that regulates neuronal excitability to maximize information transmission. We show that a stochastically spiking neuron learns one independent component for inputs encoded either as rates or using spike-spike correlations. Furthermore, different independent components can be recovered, when the activity of different neurons is decorrelated by adaptive lateral inhibition.     

Regulatory constructivism: On the relation between evolutionary epistemology and Piaget's genetic epistemology

It is argued that fundamental to Piaget's life works is a biologically based naturalism in which the living world is a nested complex of self-regulating, self-organising (constructing) adaptive systems. A structuralist-rationalist overlay on this core position is distinguished and it is shown how it may be excised without significant loss of content or insight. A new and richer conception of the nature of Piaget's genetic epistemology emerges, one which enjoys rich interrelationships with evolutionary epistemology. These are explored and it is shown how a regulatory systems evolutionary epistemology may be embedded within genetic epistemology.     

Photoreceptor spectral sensitivities in terrestrial animals: adaptations for luminance and colour vision

This review outlines how eyes of terrestrial vertebrates and insects meet the competing requirements of coding both spatial and spectral information. There is no unique solution to this problem. Thus, mammals and honeybees use their long-wavelength receptors for both achromatic (luminance) and colour vision, whereas flies and birds probably use separate sets of photoreceptors for the two purposes. In particular, we look at spectral tuning and diversification among 'long-wavelength' receptors (sensitivity maxima at greater than 500 nm), which play a primary role in luminance vision. Data on spectral sensitivities and phylogeny of visual photopigments can be incorporated into theoretical models to suggest how eyes are adapted to coding natural stimuli. Models indicate, for example, that animal colour vision--involving five or fewer broadly tuned receptors--is well matched to most natural spectra. We can also predict that the particular objects of interest and signal-to-noise ratios will affect the optimal eye design. Nonetheless, it remains difficult to account for the adaptive significance of features such as co-expression of photopigments in single receptors, variation in spectral sensitivities of mammalian L-cone pigments and the diversification of long-wavelength receptors that has occurred in several terrestrial lineages.     

Numerical and Experimental Research on Modular Oscillating Fin

Fishes are famous for their ability to position themselves accurately even in turbulent flows. This ability is the result of the coordinated movement of fins which extend from the body. We have embarked on a research program designed to develop an agile and high efficient biologically inspired robotic fish based on the performance of hybrid mechanical fms. To accomplish this goal, a mechanical ray-like fin actuated by Shape Memory Alloy （SMA） is developed, which can realize both oscillatory locomotion and undulatory locomotion. We first give a brief introduction on the mechanical structure of our fin and then carry out theoretic analysis on force generation. Detailed information of these theoretical results is later revealed by Computational Huid Dynamic （CFD）, and is final validated by experiments. This robotic fin has potential application as a propulsor for future underwater vehicles in addition to being a valuable scientific instrument.     

Simulation of adaptive mechanisms in the vestibulo-ocular reflex

The vestibulo-ocular reflex (VOR), which stabilizes the eyes in space during head movements, can undergo adaptive modification to maintain retinal stability in response to natural or experimental challenges. A number of models and neural sites have been proposed to account for this adaptation but these do not fully explain how the nervous system can detect and correct errors in both gain and phase of the VOR. This paper presents a general error correction algorithm based on the multiplicative combination of three signals (retinal slip velocity, head position, head velocity) directly relevant to processing of the VOR. The algorithm is highly specific, requiring the combination of particular sets of signals to achieve compensation. It is robust, with essentially perfect compensation observed for all gain (0.25X–4.0X) and phase (-180°–+180°) errors tested. Output of the model closely resembles behavioral data from both gain and phase adaptation experiments in a variety of species. Imposing physiological constraints (no negative activation levels or changes in the sign of unit weights) does not alter the effectiveness of the algorithm. These results suggest that the mechanisms implemented in our model correspond to those implemented in the brain of the behaving organism. Predictions concerning the nature of the adaptive process are specific enough to permit experimental verification using electrophysiological techniques. In addition, the model provides a strategy for adaptive control of any first order mechanical system.     

Color signal information content and the eye of the beholder: a case study in the rhesus macaque

Animal coloration has provided many classical examples of both natural and sexual selection. Methods to study color signals range from human assessment to models of receiver vision, with objective measurements commonly involving spectrometry or digital photography. However, signal assessment by a receiver is not objective but linked to receiver perception. Here, we use standardized digital photographs of female rhesus macaque (Macaca mulatta) face and hindquarter regions, combined with estimates of the timing of the female fertile phase, to assess how color varies with respect to this timing. We compare objective color measures (camera sensor responses) with models of rhesus vision (retinal receptor stimulation and visual discriminability). Due to differences in spectral separation between camera sensors and rhesus receptors, camera measures overestimated color variation and underestimated luminance variation compared with rhesus macaques. Consequently, objective digital camera measurements can produce statistically significant relationships that are probably undetectable to rhesus macaques, and hence biologically irrelevant, while missing variation in the measure that may be relevant. Discrimination modeling provided results that were most meaningful (as they were directly related to receiver perception) and were easiest to relate to underlying physiology. Further, this gave new insight into the function of such signals, revealing perceptually salient signal luminance changes outside of the fertile phase that could potentially enhance paternity confusion. Our study demonstrates how, even for species with similar visual systems to humans, models of vision may provide more accurate and meaningful information on the form and function of visual signals than objective color measures do.     

Cache consensus: rapid object sorting by a robotic swarm

We present a new method which allows a swarm of robots to sort arbitrarily arranged objects into homogeneous clusters. In the ideal case, a distributed robotic sorting method should establish a single homogeneous cluster for each object type. This can be achieved with existing methods, but the rate of convergence is considered too slow for real-world application. Previous research on distributed robotic sorting is typified by randomised movement with a pick-up/deposit behaviour that is a probabilistic function of local object density. We investigate whether the ability of each robot to localise and return to remembered places can improve distributed sorting performance. In our method, each robot maintains a cache point for each object type. Upon collecting an object, it returns to add this object to the cluster surrounding the cache point. Similar to previous biologically inspired work on distributed sorting, no explicit communication between robots is implemented. However, the robots can still come to a consensus on the best cache for each object type by observing clusters and comparing their sizes with remembered cache sizes. We refer to this method as cache consensus. Our results indicate that incorporating this localisation capability enables a significant improvement in the rate of convergence. We present experimental results using a realistic simulation of our targeted robotic platform. A subset of these experiments is also validated on physical robots.     

A neural-network system for control of eye movements: basic mechanisms

This paper presents a neural-network-based system that can generate and control movements of the eyes. It was inspired by a number of experimental observations on the saccadic and gaze systems of monkeys and cats. Because of the generality of the approach undertaken, the system can be regarded as a demonstration of how parallel distributed processing principles, namely learning and attractor dynamics, can be integrated with experimental findings, as well as a biologically inspired controller for a dexterous robotic orientation device. The system is composed of three parts: a dynamic motor map, a push-pull circuitry, and a plant. The dynamics of the motor map is generated by a multi-layer network that was trained to compute a bidimensional temporal-spatial transformation. Simulation results indicate (1) that the system is able to reproduce some of the properties observed in the biological system at the neural and movement levels and (2) that the dynamics of the motor map remains stereotyped even when the motor map is subject to abnormal stimulation patterns. The latter result emphasizes the role of the topographic projection that connects the motor map to the push-pull circuitry in determining the features of the resulting movements.     

Biological and bionic hands: natural neural coding and artificial perception

The first decade and a half of the twenty-first century brought about two major innovations in neuroprosthetics: the development of anthropomorphic robotic limbs that replicate much of the function of a native human arm and the refinement of algorithms that decode intended movements from brain activity. However, skilled manipulation of objects requires somatosensory feedback, for which vision is a poor substitute. For upper-limb neuroprostheses to be clinically viable, they must therefore provide for the restoration of touch and proprioception. In this review, I discuss efforts to elicit meaningful tactile sensations through stimulation of neurons in somatosensory cortex. I focus on biomimetic approaches to sensory restoration, which leverage our current understanding about how information about grasped objects is encoded in the brain of intact individuals. I argue that not only can sensory neuroscience inform the development of sensory neuroprostheses, but also that the converse is true: stimulating the brain offers an exceptional opportunity to causally interrogate neural circuits and test hypotheses about natural neural coding.     

Seeing in stereo: The ecology and evolution of primate binocular vision and stereopsis

Primates are the most visually adapted order of mammals. There is a rich history within anthropology of proposed explanations for the adaptive significance of binocular vision, especially pertaining to primate origins and evolution. Depth perception and orbit morphology have been hypothesized to be functionally related to specialized locomotor or feeding behaviors. Many of these arguments continue to this day. An understanding of specific primate visual adaptations, including binocular vision, can shed light on these long‐term and heated debates.     

Dynamic Service Discovery for Mobile Computing: Intelligent Agents Meet Jini in the Aether

The emergence of ad-hoc pervasive connectivity for devices based on Bluetooth-like systems provides a new way to create applications for mobile systems. We seek to realize ubiquitous computing systems based on the cooperation of autonomous, dynamic and adaptive components (hardware as well as software) which are located in vicinity of one another. In this paper we present this vision. We also describe a prototype system we have developed that implements parts of this vision – in particular a system that combines agent oriented and service oriented approaches and provides dynamic service discovery. We point out why existing systems such as Jini are not suited for this task, and how our system improves on them.     

Automated triplexed hepatocyte-based viability and CYP1A and -3A induction assays

Cytochrome P450 (CYP) enzymes are key players in drug metabolism. Therefore, it is essential to understand how these enzymes can be affected by xenobiotics with regards to induction and toxicity to avoid potential drug-drug interactions. Typically, information has been gathered by combining data from multiple experiments, which is time-consuming and labor intensive, and interassay variability may lead to misinterpretation. Monitoring CYP induction and cytotoxicity by xenobiotics using an automated, multiplexed format can decrease workload and increase data confidence. Here the authors demonstrate the ability to monitor CYP1A and CYP3A4 induction, combined with a cytotoxicity measurement, from a single microplate well using cryopreserved human hepatocytes. The assay procedure was automated in a 384-well format, including cell manipulations, compound titration and transfer, and reagent dispensing, using simple robotic instrumentation. EC(50) and E(max) values were derived for multiple known CYP1A and -3A4 inducers. Induction and toxicological responses in the triplex system were validated based on literature values from conventional single-parameter assays. Validation and pharmacology data confirm that multiplexed cell-based CYP assays can simplify workload, save time and effort, and generate biologically relevant data.     

Ethanol is a better inducer of DNA guanine tetraplexes than potassium cations

Guanine tetraplexes are a biologically relevant alternative of the Watson and Crick duplex of DNA. It is thought that potassium or other cations present in the cavity between consecutive guanine tetrads are an integral part of the tetraplexes. Here we show using CD spectroscopy that ethanol induces the guanine tetraplexes like or even better than potassium cations. We present examples of ethanol stabilizing guanine tetraplexes even in cases when potassium cations fail to do so. Hence, besides the A-form or Z-form, ethanol stabilizes another conformation of DNA, i.e., the guanine tetraplexes. We discuss the mechanism of the stabilization. Use of ethanol will permit studies of guanine tetraplexes that cannot be induced by potassium cations or other tetraplex-promoting agents. This work demonstrates that a still broader spectrum of nucleotide sequences can fold into guanine tetraplexes than has previously been thought. Aqueous ethanol may better simulate conditions existing in vivo than the aqueous solutions.