Abstract 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.
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