Joseph Ayers

Biomimetic approaches to the control of underwater walking machines.

We have developed a biomimetic robot based on the American lobster. The robot is designed to achieve the performance advantages of the animal model by adopting biomechanical features and neurobiological control principles. Three types of controllers are described. The first is a state machine based on the connectivity and dynamics of the lobster central pattern generator (CPG). The state machine controls myomorphic actuators based on shape memory alloys (SMAs) and responds to environmental perturbation through sensors that employ a labelled-line code. The controller supports a library of action patterns and exteroceptive reflexes to mediate tactile navigation, obstacle negotiation and adaptation to surge. We are extending this controller to neuronal network-based models. A second type of leg CPG is based on synaptic networks of electronic neurons and has been adapted to control the SMA actuated leg. A brain is being developed using layered reflexes based on discrete time map-based neurons.

Locomotion: Control by Positive-Feedback Optokinetic Responses

Several species of arthropods perform forward locomotory movements when restrained in place and exposed to a pattern of stripes moving backward at normal locomotory velocities. Locomotory effort varies directly with stripe velocity. In nature such locomotory reactions would increase the visual stimulus that elicits them; hence, the reactions represent a new class of optokinetic responses employing positive visual feedback. Stabilizing mechanisms include response decrement during constant stripe velocities.

Low power real time electronic neuron VLSI design using subthreshold technique

We discuss a VLSI electronic neuron circuit that implements the Hindmarsh and Rose neuron model. Magnitude and time scaling techniques are employed for a 2 V power supply operation. A subthreshold operation technique and a single MOS resistor are used to minimize area and power consumption. Output bursts of the electronic neuron can be modulated dynamically by varying the input voltage level. The circuit is designed using a 0.25 /spl mu/m CMOS standard process, and the total power dissipation is 163.4 /spl mu/watt.

Observations on the electric organ discharge of two skate species (Chondrichthyes: Rajidae) and its relationship to behaviour

SynopsisThe electric organ discharge (EOD) of the little skate,Raja erinacea and winter skate,R. ocellata was recorded both from isolated individuals and from small groups using methods that allowed for the identification of individuals producing EODs. Pulse duration, train lengh, frequency, and pulse patterns are characterized and correlated with behaviour. The two species,R. erinacea andR. ocellata, were found to have characteristically different EOD pulse durations of 70 ms and 217 ms respectively. Isolated skates rarely discharged whereas groups of skates were found to discharge regularly. The EOD was evoked by tactile prodding, physical contact with other skates and electrical stimulation. Skates also discharged reflexively in response to an artificially induced head-positive DC stimulus, sine wave and monopolar square pulses. During approach and contact, skates responded to each other with interacting EOD displays. EOD interaction and pulse duration differences between other species suggest a possible intra-specific communication function of the EOD inRaja.

Oscillations and oscillatory behavior in small neural circuits

In order to determine the dynamical properties of central pattern generators (CPGs), we have examined the lobster stomatogastric ganglion using the tools of nonlinear dynamics. The lobster pyloric and gastric mill central pattern generators can be analyzed at both the cellular and network levels because they are small, i.e., contain only 25 neurons between them and each neuron and synapse are repeatedly identifiable from animal to animal. We discuss how the biophysical properties of each neuron and synapse in the two circuits act cooperatively to generate two different patterns of sequential activity, how these patterns are altered by neuromodulators and perturbed by noise and sensory inputs. Finally, we show how simplified Hindmarsh–Rose models can be made into analog electronic neurons that mimic the lobster neurons and in addition be incorporated into artificial CPGs with robotic applications.

Bio-mechanisms of swimming and flying

Chapter 1: An Engineering Perspective on Swimming Bacteria: High-Speed Flagellar Motor, Intelligent Flagellar Filaments, and Skillful Swimming in Viscous Environments, Y. Magariyama, S. Kudo, T. Goto, and Y. Takano.- Chapter 2: Euglena Motion Control by Local Illumination, A. Itoh.- Chapter 3: Thrust-Force Characteristics of Enlarged Propulsion Mechanisms Modeled on Eukaryotic Flagellar Movement and Ciliary Movement in Fluid, S. Kobayashi, K. Furihata, T. Mashima, and H. Morikawa.- Chapter 4: Resonance Model of the Indirect Flight Mechanism, H. Miyake.- Chapter 5: On Flow Separation Control by Means of Flapping Wings, K.D. Jones, M. Nakashima, C.J. Bradshaw, J. Papadopoulos, and M.F. Platzer.- Chapter 6: Outboard Propulsor with an Oscillating Horizontal Fin, H. Morikawa, A. Hiraki, S. Kobayashi, and Y. Muguruma.- Chapter 7: Three-Dimensional Maneuverability of the Dolphin Robot (Roll Control and Loop-the-Loop Motion), M. Nakashima, Y. Takahashi, T. Tsubaki, and K. Ono.- Chapter 8: Fundamental Study of a Fishllike Body with Two Undulating Side-Fins, Y. Toda, T. Suzuki, S. Uto, and N. Tanaka.- Chapter 9: Biology-Inspired Precision Maneuvering of Underwater Vehicles, N. Kato, H. Liu, and H. Morikawa .- Chapter 10: Optimal Measurement Strategies for Environmental Mapping and Localization of a Biomimetic Autonomous Underwater Vehicle, J. Guo, F.-C. Chiu, S.-W. Cheng, and P.-C. Shi.- Chapter 11: Experimental and Analytical Study of the Schooling Motion of Fish Based on Two Observed Individual Motions: Approaching Motion and Parallel Orienting Motion, Y. Inada, K. Kawachi, and H. Liu.- Chapter 12: Neural Basis of Odor-Source Searching Behavior in Insect Microbrain Systems Evaluated with a Mobile Robot, R. Kanzaki, S. Nagasawa, and I. Shimoyama.- Chapter 13: Architectures for Adaptive Behavior in Biomimetic Underwater Robots, J. Ayers.- Chapter 14: Efficiency of Biological and Artificial Gills, K. Nagase, F. Kohori, and K. Sakai.- Subject Index.

Controlling Biomimetic Underwater Robots With Electronic Nervous Systems

We are developing biomimetic robots based on neurobiological model systems, the lobster and the lamprey. Existing implementations of these robots are based on finite state machine based controllers that instantiate a set of finite state machines based on the organizational units of the animal model nervous systems. These state machines include leg or body axis central pattern generators (CPGs) that generate leg movements or undulations, postural pattern generators that control compensatory appendages and/or adaptive sensors and sensory integration networks that process sensor information. The use of neuron models instead of finite state systems allows one to replicate in great detail the real behavior of the neurobiological system (a network) and, thanks to spiking nature of the models, provides a link between the control functions and the experimental measurements from the animal. The key feature of these models is that because they are based on capturing of nonlinear dynamical behavior of neurons rather than neuronal conductance models, they are simpler, can operate in real time and are thus suitable for robotic control applications.

Functional Anatomy and Behavior

As emphasized in the Introduction, the choice of the model system is crucial to success in understanding mechanisms underlying motor pattern generation. Serious consideration must be given to the ease with which the nervous system selected is amenable to study by cellular techniques. For this reason, most of the results presented in this book deal primarily with the stomatogastric nervous system and are not devoted to a detailed consideration of the motor functions of the crustacean foregut, per se. However, these results cannot be appreciated without a minimal knowledge of the anatomy of the neuromuscular systems in the foregut and cannot be put into a biological perspective if they do not explain the motor behavior. The goal of this first chapter is: (1) to describe the basic structure of the foregut and the anatomical organization of the muscles and neurons involved in its operation, and (2) to examine the possible range of motor behavior expressed by each region of the foregut in the intact animal.

Controlling underwater robots with electronic nervous systems

We are developing robot controllers based on biomimetic design principles. The goal is to realise the adaptive capabilities of the animal models in natural environments. We report feasibility studies of a hybrid architecture that instantiates a command and coordinating level with computed discrete-time map-based DTM neuronal networks and the central pattern generators with analogue VLSI Very Large Scale Integration electronic neuron aVLSI networks. DTM networks are realised using neurons based on a 1-D or 2-D Map with two additional parameters that define silent, spiking and bursting regimes. Electronic neurons ENs based on Hindmarsh--Rose HR dynamics can be instantiated in analogue VLSI and exhibit similar behaviour to those based on discrete components. We have constructed locomotor central pattern generators CPGs with aVLSI networks that can be modulated to select different behaviours on the basis of selective command input. The two technologies can be fused by interfacing the signals from the DTM circuits directly to the aVLSI CPGs. Using DTMs, we have been able to simulate complex sensory fusion for rheotaxic behaviour based on both hydrodynamic and optical flow senses. We will illustrate aspects of controllers for ambulatory biomimetic robots. These studies indicate that it is feasible to fabricate an electronic nervous system controller integrating both aVLSI CPGs and layered DTM exteroceptive reflexes.

Low power, high PVT variation tolerant central pattern generator design for a bio-hybrid micro robot

This paper presents a low power circuit design for an electronic nervous system composed of central pattern generator (CPG) to control a biomimetic robot that mimics the lamprey swimming system. The circuit has been designed using 65nm CMOS technology model at 0.8V supply. The design challenges of narrow voltage design margin and high sensitivity to parameter variation are addressed by circuit optimization techniques as well as amplitude and time parameter scaling. The electronic CPG consists of electronic neurons connected through electronic synapses, where the behaviors of the neuron and synapse adopt Hindmarsh-Rose (HR) dynamics to replicate biological neurons and a first order chemical synapse model is utilized to achieve active synapses. The simulation results validate the electronic CPG performance at 0.8V supply voltage with parameter variation tolerance of 5% dissipating 3.28mW. The die size of the chip is 1.1mm2 including I/O pads.