We are developing a biomimetic robot based on the Sea Lamprey. The robot consists of a cylindrical electronics bay propelled by an undulatory body axis. Shape memory alloy (SMA) actuators generate propagating flexion waves in five undulatory segments of a polyurethane strip. The behavior of the robot is controlled by an electronic nervous system (ENS) composed of networks of discrete-time map-based neurons and synapses that execute on a digital signal processing chip. Motor neuron action potentials gate power transistors that apply current to the SMA actuators. The ENS consists of a set of segmental central pattern generators (CPGs), modulated by layered command and coordinating neuron networks, that integrate input from exteroceptive sensors including a compass, accelerometers, inclinometers and a short baseline sonar array (SBA). The CPGs instantiate the 3-element hemi-segmental network model established from physiological studies. Anterior and posterior propagating pathways between CPGs mediate intersegmental coordination to generate flexion waves for forward and backward swimming. The command network mediates layered exteroceptive reflexes for homing, primary orientation, and impediment compensation. The SBA allows homing on a sonar beacon by indicating deviations in azimuth and inclination. Inclinometers actuate a bending segment between the hull and undulator to allow climb and dive. Accelerometers can distinguish collisions from impediment to allow compensatory reflexes. Modulatory commands mediate speed control and turning. A SBA communications interface is being developed to allow supervised reactive autonomy.

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The adaptive capabilities of underwater organisms result from layered exteroceptive reflexes responding to gravity, impediment, and hydrodynamic and optical flow. In combination with taxic responses to point sources of sound or chemicals, these reflexes allow reactive autonomy in the most challenging of environments. We are developing a new generation of lobster and lamprey-based robots that operate under control by synaptic networks rather than algorithms. The networks, based on the command neuron, coordinating neuron, and central pattern generator architecture, code sensor input as labeled lines and activate shape memory alloy-based artificial muscles through a simple interface that couples excitation to contraction. We have completed the lamprey-based robot and are adapting this sensor, board, and actuator architecture to a new generation of the lobster-based robot. The networks are constructed from discrete time map-based neurons and synapses and are instantiated on the digital signal processing chip. A sensor board integrates inputs from a short baseline sonar array (for beacon tracking and supervisory control), accelerometer, a compass, antennae, and optionally chemosensors. Actuator control is mediated by pulse-width duty cycle coding generated by the electronic motor neurons and a comparator and power field-effect transistor (FET) system housed on low- and high-current driver boards. These circular boards are stacked in a tubular hull with the processor and batteries. This system can readily mimic the biomechanics of the model organisms by the addition of hydrodynamic control surfaces. The behavioral set results from chaining sequences of exteroceptive reflexes released by sensory feedback from the environment.

Abstract. As part of the Robobee project, we have modified a coaxial helicopter to operate using a discrete time map-based neuronal network for the control of heading, altitude, yaw, and odometry. Two concepts are presented: 1. A model for the integration of sensory data into the neural network. 2. A function for transferring the instantaneous spike frequency of motor neurons to a pulse width modulated signal required to drive motors and other types of actuators. The helicopter is provided with a flight vector and distance to emulate the information conveyed by the honeybee's waggle dance. This platform allows for the testing of proposed networks for adaptive navigation in an effort to simulate honeybee foraging on a flying robot.

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