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Intelligent physical systems as embodied cognitive systems must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and control must manage the problem of converting continuous values from the real world to symbolic representations (and back). To generate effective behaviors, reasoning must include a capacity to replan, acquire and update new information, detect and respond to anomalies, and perform various operations on system goals. But, these processes are not independent and need further exploration. This paper examines an agent’s choices when multiple goal operations co-occur and interact, and it establishes a method of choosing between them. We demonstrate the benefits and discuss the trade offs involved with this and show positive results in a dynamic marine search task.

Abstract Background Autonomous underwater vehicles (AUVs) and animal telemetry have become important tools for understanding the relationships between aquatic organisms and their environment, but more information is needed to guide the development and use of AUVs as effective animal tracking platforms. A forward-facing acoustic telemetry receiver (VR2Tx 69 kHz; VEMCO, Bedford, Nova Scotia) attached to a novel AUV (gliding robotic fish) was tested in a freshwater lake to (1) compare its detection efficiency (i.e., the probability of detecting an acoustic signal emitted by a tag) of acoustic tags (VEMCO model V8-4H 69 kHz) to stationary receivers and (2) determine if detection efficiency was related to distance between tag and receiver, direction of movement (toward or away from transmitter), depth, or pitch. Results Detection efficiency for mobile (robot-mounted) and stationary receivers were similar at ranges less than 300 m, on average across all tests, but detection efficiency for the mobile receiver decreased faster than for stationary receivers at distances greater than 300 m. Detection efficiency was higher when the robot was moving toward the transmitter than when moving away from the transmitter. Detection efficiency decreased with depth (surface to 4 m) when the robot was moving away from the transmitter, but depth had no significant effectmore »on detection efficiency when the robot was moving toward the transmitter. Detection efficiency was higher when the robot was descending (pitched downward) than ascending (pitched upward) when moving toward the transmitter, but pitch had no significant effect when moving away from the transmitter. Conclusion Results suggested that much of the observed variation in detection efficiency is related to shielding of the acoustic signal by the robot body depending on the positions and orientation of the hydrophone relative to the transmitter. Results are expected to inform hardware, software, and operational changes to gliding robotic fish that will improve detection efficiency. Regardless, data on the size and shape of detection efficiency curves for gliding robotic fish will be useful for planning future missions and should be relevant to other AUVs for telemetry. With refinements, gliding robotic fish could be a useful platform for active tracking of acoustic tags in certain environments.« less

This paper presents an adaptive, needle variation-based feedback scheme for controlling affine nonlinear systems with unknown parameters that appear linearly in the dynamics. The proposed approach combines an online parameter identifier with a second-order sequential action controller that has shown great promise for nonlinear, underactuated, and high-dimensional constrained systems. Simulation results on the dynamics of an underwater glider and robotic fish show the advantages of introducing online parameter estimation to the controller when the model parameters deviate from their true values or are completely unknown.