Biologically inspired control of physically simulated bipeds

Summary The basic rhythmicity underlying animal locomotion is created by dedicated neural structures called central pattern generators (CPGs). We describe the implementation of such structures in simulation and their successful use for the control of bipedal walking. Artificial evolution (in the form of genetic algorithms) is used as the optimisation procedure. Two CPG types are illustrated, the more advanced of which being based on recent theoretical findings on the nature of neural architectures required to drive animal locomotion. It is shown that CPGs in conjunction with simple reflex responses as well as an appropriate mechanical implementation of the biped are capable of producing stable walking patterns on planar surfaces. This finding corroborates circumstantial experimental evidence that limited bipedal locomotion is possible without the employment of higher level control centres.     

Biologically inspired kinematic synergies enable linear balance control of a humanoid robot

Despite many efforts, balance control of humanoid robots in the presence of unforeseen external or internal forces has remained an unsolved problem. The difficulty of this problem is a consequence of the high dimensionality of the action space of a humanoid robot, due to its large number of degrees of freedom (joints), and of non-linearities in its kinematic chains. Biped biological organisms face similar difficulties, but have nevertheless solved this problem. Experimental data reveal that many biological organisms reduce the high dimensionality of their action space by generating movements through linear superposition of a rather small number of stereotypical combinations of simultaneous movements of many joints, to which we refer as kinematic synergies in this paper. We show that by constructing two suitable non-linear kinematic synergies for the lower part of the body of a humanoid robot, balance control can in fact be reduced to a linear control problem, at least in the case of relatively slow movements. We demonstrate for a variety of tasks that the humanoid robot HOAP-2 acquires through this approach the capability to balance dynamically against unforeseen disturbances that may arise from external forces or from manipulating unknown loads.     

Biologically inspired redistribution of a swarm of robots among multiple sites

We present a biologically inspired approach to the dynamic assignment and reassignment of a homogeneous swarm of robots to multiple locations, which is relevant to applications like search and rescue, environmental monitoring, and task allocation. Our work is inspired by experimental studies of ant house hunting and empirical models that predict the behavior of the colony that is faced with a choice between multiple candidate nests. We design quorum based stochastic control policies that enable the team of agents to distribute themselves among multiple candidate sites in a specified ratio, and compare our results to the linear stochastic policies described in (Halasz et al., in Proceedings of the International Conference on Intelligent Robots and Systems (IROS’07), pp. 2320–2325, 2007). We show how our quorum model consistently performs better than the linear models while minimizing computational requirements and now it can be implemented without the use of inter-agent wireless communication.     

Biologically inspired phylogenetic models strongly outperform the no common mechanism model

But Tuffley and Steel (1997) introduced a model called No Common Mechanism (NCM), in which characters may-but are not required to-vary their relative rates independently, both within and between branches. Because the independent variation is taken only as a possibility, not as a requirement, NCM would apply to almost any situation, and so may be accepted as realistic. This is useful because Tuffley and Steel also showed that maximum likelihood under NCM selects the same trees as does parsimony. With the realistic NCM in the background, then, most parsimonious trees have greatest power to explain available observations. -Farris (2008).     

Biologically inspired strategy for programmed assembly of viral building blocks with controlled dimensions

Facile fabrication of building blocks with precisely controlled dimensions is imperative in the development of functional devices and materials. We demonstrate the assembly of nanoscale viral building blocks of controlled lengths using a biologically motivated strategy. To achieve this we exploit the simple self-assembly mechanism of Tobacco mosaic virus (TMV), whose length is solely governed by the length of its genomic mRNA. We synthesize viral mRNA of desired lengths using simple molecular biology techniques, and in vitro assemble the mRNA with viral coat proteins to yield viral building blocks of controlled lengths. The results indicate that the assembly of the viral building blocks is consistent and reproducible, and can be readily extended to assemble building blocks with genetically modified coat proteins (TMV1cys). Additionally, we confirm the potential utility of the TMV1cys viral building blocks with controlled dimensions via covalent and quantitative conjugation of fluorescent markers. We envision that our biologically inspired assembly strategy to design and construct viral building blocks of controlled dimensions could be employed to fabricate well-controlled nanoarchitectures and hybrid nanomaterials for a wide variety of applications including nanoelectronics and nanocatalysis.     

Saccade control in a simulated robot camera-head system: neural net architectures for efficient learning of inverse kinematics

The high speed of saccades means that they cannot be guided by visual feedback, so that any saccadic control system must know in advance the correct output signals to fixate a particular retinal position. To investigate neural-net architectures for learning this inverse-kinematics problem we simulated a 4 deg-of-freedom robot camera-head system, in which the head could pan and tilt and the cameras pan and verge. The main findings were: (1) Linear nets, multilayer perceptrons (MLPs) trained by backpropagation, and cerebellar model arithmetic computers (CMACs) all learnt rapidly to 5–10% accuracy when given perfect error feedback. (2) For additional accuracy (down to 2%) two-layer nets learnt much faster than a single MLP or CMAC: the best combination tried was to have a CMAC learn the errors of a trained linear net. (3) Imperfect error signals were provided by a crude controller whose output was simply proportional to retinal input in the relevant axis, thereby providing a mechanism for (a) controlling the camera-head system when the feedforward neural net controller was wrong or inoperative, and (b) converting sensory error signals into motor error signals as required in supervised learning. It proved possible to train neural-net controllers using these imperfect error signals over a range of learning rates and crude-controller gains. These results suggest that appropriate neural-net architectures can provide practical, accurate and robust adaptive control for saccadic movements. In addition, the arrangement of a crude controller teaching a sophisticated one may be similar to that used by the primate saccadic system, with brainstem circuitry teaching the cerebellum.     

Biologically inspired sensing: infrared spectroscopic analysis of cell responses to an inhalation health hazard

This work describes the development of a biologically based sensing technique to quantify chemical agents that pose inhalation health hazards. The approach utilizes cultured epithelial cells (A549 human type II pneumocytes) of the lung, exposed to potential toxins and monitored through the noninvasive means of infrared spectroscopy to quantify changes to cell physiology and function. Cell response to Streptolysin O, a cholesterol-binding cytolysin, is investigated here. Infrared spectra display changes in cell physiology indicative of membrane damage, altered proteins, and some nucleic acid damage. Methods to improve cell adhesion through modification of support surface properties are detailed. This spectroscopic approach not only provides a robust means to detect potential toxins but also provides information on modes of damage and mechanisms of cellular response.     

An adaptive gaze stabilization controller inspired by the vestibulo-ocular reflex

The vestibulo-ocular reflex stabilizes vision in many vertebrates. It integrates inertial and visual information to drive the eyes in the opposite direction to head movement and thereby stabilizes the image on the retina. Its adaptive nature guarantees stable vision even when the biological system undergoes dynamic changes (due to disease, growth or fatigue etc), a characteristic especially desirable in autonomous robotic systems. Based on novel, biologically plausible neurological models, we have developed a robotic testbed to qualitatively evaluate the performance of these algorithms. We show how the adaptive controller can adapt to a time varying plant and elaborate how this biologically inspired control architecture can be employed in general engineering applications where sensory feedback is very noisy and/or delayed.     

Oculomotor evidence for top-down control following the initial saccade

The goal of the current study was to investigate how salience-driven and goal-driven processes unfold during visual search over multiple eye movements. Eye movements were recorded while observers searched for a target, which was located on (Experiment 1) or defined as (Experiment 2) a specific orientation singleton. This singleton could either be the most, medium, or least salient element in the display. Results were analyzed as a function of response time separately for initial and second eye movements. Irrespective of the search task, initial saccades elicited shortly after the onset of the search display were primarily salience-driven whereas initial saccades elicited after approximately 250 ms were completely unaffected by salience. Initial saccades were increasingly guided in line with task requirements with increasing response times. Second saccades were completely unaffected by salience and were consistently goal-driven, irrespective of response time. These results suggest that stimulus-salience affects the visual system only briefly after a visual image enters the brain and has no effect thereafter.     

Fully decentralized control of a soft-bodied robot inspired by true slime mold

Animals exhibit astoundingly adaptive and supple locomotion under real world constraints. In order to endow robots with similar capabilities, we must implement many degrees of freedom, equivalent to animals, into the robots’ bodies. For taming many degrees of freedom, the concept of autonomous decentralized control plays a pivotal role. However a systematic way of designing such autonomous decentralized control system is still missing. Aiming at understanding the principles that underlie animals’ locomotion, we have focused on a true slime mold, a primitive living organism, and extracted a design scheme for autonomous decentralized control system. In order to validate this design scheme, this article presents a soft-bodied amoeboid robot inspired by the true slime mold. Significant features of this robot are twofold: (1) the robot has a truly soft and deformable body stemming from real-time tunable springs and protoplasm, the former is used for an outer skin of the body and the latter is to satisfy the law of conservation of mass; and (2) fully decentralized control using coupled oscillators with completely local sensory feedback mechanism is realized by exploiting the long-distance physical interaction between the body parts stemming from the law of conservation of protoplasmic mass. Simulation results show that this robot exhibits highly supple and adaptive locomotion without relying on any hierarchical structure. The results obtained are expected to shed new light on design methodology for autonomous decentralized control system.     

Biologically based insecticides for the control of immature Australian mosquitoes: a review

Abstract  Our review outlines changes in insecticide usage for mosquito control against Australian mosquitoes, with a focus on biologically based insecticides. The most widely used microbial insecticide is Bacillus thuringiensis var. israelensis de Barjac ( Bti ) and it is regularly used in estuaries and freshwater. In comparison, the use of Bacillus sphaericus (Neide) is limited to freshwater. The only insect growth regulator registered for mosquito control in Australia is s -methoprene, and it is used in both estuaries and freshwater. Although biologically based insecticides have been used for more than 10 years, there remains knowledge gaps surrounding the use of specific formulations in specific habitats: for example, VectoBac WG ( Bti ) and VectoBac G ( Bti ) in containers containing freshwater, or Altosid pellets ( s -methoprene) in ground-pool freshwater habitats. Where broad-scale mosquito control programs have been implemented in Australia, a reduction in the incidence of mosquito-borne disease, mainly Ross River virus, has been recorded. Therefore, the future application of these products is supported. The use of insecticides should be integrated with public education, biological control, physical habitat modification and coupled with spatial risk assessment.     

Biologically constrained action selection improves cognitive control in a model of the Stroop task

The Stroop task is a paradigmatic psychological task for investigating stimulus conflict and the effect this has on response selection. The model of Cohen et al. (Cohen et al. 1990 Psychol. Rev. 97, 332-361) has hitherto provided the best account of performance in the Stroop task, but there remains certain key data that it fails to match. We show that this failure is due to the mechanism used to perform final response selection-one based on the diffusion model of choice behaviour (Ratcliff 1978 Psychol. Rev. 85, 59-108). We adapt the model to use a selection mechanism which is based on the putative human locus of final response selection, the basal ganglia/thalamo-cortical complex (Redgrave et al. 1999 Neuroscience 89, 1009-1023). This improves the match to the core human data and, additionally, makes it possible for the model to accommodate, in a principled way, additional mechanisms of cognitive control that enable better fits to the data. This work prompts a critique of the diffusion model as a mechanism of response selection, and the features that any response mechanism must possess to provide adaptive action selection. We conclude that the consideration of biologically constrained solutions to the action selection problem is vital to the understanding and improvement of cognitive models of response selection.     

On-line adaptive control of a fed-batch fermentation of Saccharomyces cerevisiae

The feasibility of applying an adaptive control technique to a fermentation process is investigated. The nonlinear, time-variant parameters of a fermentation process were estimated on-line as a series of linearized describing matrices. The matrices were used to update a suboptimal feedback law which controlled the process in real time over the linear region. Experiments were performed on a small-scale fully instrumented fermenter with the online, real-time adaptive control package. Results are presented for both single- and multivariable control, and indicate successful control of yeast cell growth.     

Parabolic flight reveals independent binocular control of otolith-induced eye torsion

To examine otolith-governed ocular torsion in hyper- and hypogravity, eight subjects, including two astronauts, underwent parabolic flight while seated upright with head fixed. A mask fitted with two video cameras provided synchronized images of both eyes at a rate of 25/sec during 15 parabolas, the individual parabolas separated by a few minutes of level 1 G flight. Three main findings emerged: 1) After the first parabola, most subjects showed differential torsional offset of the two eyes in the 1 G portions between parabolas, compared to the conjugate baseline position of the eyes prior to the first parabola. 2) Changes in binocular torsion in the 0 G and 1.8 G portions of parabolic flight revealed in most subjects systematic reversal of direction. The reversal was consistent within, but not across subjects. 3) Disconjugacy defined as the moment-to-moment difference in the movements of the two eyes, and evaluated without the contribution of the differential offset, found two subjects with relatively high disconjugacy scores, and the remaining six with low scores. On the basis of prior studies (9, 20), we would predict the first two would be subject to SMS, the remainder not. The two astronauts, who did not have SMS on their space missions, fell into the low scoring group. We propose that the disconjugacies may be due to intrinsic asymmetries in the otolith receptors on the two sides of the head, which appear to be independently linked to the extraocular muscles of the two eyes, a phenomenon masked in normal 1 G states by adaptation. The apparently independent control of the two sides cannot be detected by the simpler and more common monocular studies.     

Some new directions in control theory inspired by systems biology

This paper, addressed primarily to engineers and mathematicians with an interest in control theory, argues that entirely new theoretical problems arise naturally when addressing questions in the field of systems biology. Examples from the author's recent work are used to illustrate this point.     

The role of binocular information in the 'on-line' control of prehension

Binocular visual information may be involved in the selection of appropriate motor programs before a reach is executed or it may be involved during the movement-execution phase in order to monitor and guide the hand to the target object. Here we introduced binocular information after 0%, 25%, 50% or 75% of the movement-execution phase and determined its effects on the kinematic indices of prehensile movements made to objects of different sizes placed at different distances. Kinematic indices linked to the transport component, such as peak velocity and time-to-peak velocity, were unaffected by the presence of binocular cues whereas later occurring indices, such as peak grip aperture and time in the slow phase, were significantly affected. Although the magnitude of the peak grip was affected by the presence of binocular cues, the time at which it occurred did not change. This pattern of results suggest that the visuo-motor control of prehensile movements utilises both feedforward and feedback strategies and that binocular cues are particularly important for the fine manual adjustments typical of the latter.     

Evaluation of calibration-free concentration analysis provided by Biacore™ systems

Surface Plasmon Resonance biosensors measure the interaction between a molecule in solution and its interaction partner attached to a sensor surface. Under certain conditions, the observed binding rate can be used directly to obtain the concentration of the molecule in solution, without the use of any standard. This type of assay is referred to as Calibration Free Concentration Analysis, CFCA. By examining experimental conditions, including immobilization levels and temperature, for a range of analytes, and by using global analysis of several sample dilutions, conditions that gave the most robust results were identified. These conditions provided the concentration values that were on average ∼15% lower than those obtained using other methods. The accuracy of the concentration determined may be related to how the analyte is distributed in the dextran matrix and to its distance from the gold surface, and may thereby depend on the conversion of the SPR signal to mass. A good precision of CFCA, ∼8% (n = 21), was demonstrated when this method was used to efficiently guide purification procedures of Interferon α-2a. In this paper, the theory behind CFCA and the future developments, as well as the application of CFCA for absolute and relative concentration measurements (including the assessment of the potency of a biotherapeutic medicine) are discussed, and new evaluation tools that broaden the range of applications, are introduced.     

Maximizing productivity of a continuous fermenter using nonlinear adaptive optimizing control

The control of a continuously operated fermenter at its maximum productivity level gives rise to a difficult control problem as the location of the optimum operating point changes due to the disturbances. In addition, the fermenter exhibits a change in the sign of the steady state gain near the optimum operating point. This study is aimed at developing an on-line optimizing control scheme that can track the changing location of the steady state optimum so as to maximize the fermenter productivity. A nonlinear Laguerre model, whose parameters are estimated on-line, is used for tracking the optimum operating point. The control at the optimum point is achieved using an adaptive nonlinear MPC strategy that uses the nonlinear Laguerre model for prediction. The efficiency of the proposed algorithm is demonstrated by simulating the control of a continuous fermenter that exhibits shift in the location of the optimum operating point in response to the changes in the maximum specific growth rate. The proposed on-line optimizing control strategy is shown to result in a considerable improvement in the closed loop performance even in the presence of measurement noise.