CPS: Synergy: Tracking Fish Movement with a School of Gliding Robotic Fish
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The goal of this project is to create an integrative framework for the design of coupled biological and robotic systems that accommodates system uncertainties and competing objectives in a rigorous, holistic, and effective manner. The design principles are developed using a concrete, end-to-end application of tracking and modeling fish movement with a network of gliding robotic fish. The proposed robotic platform is an energy-efficient underwater gliding robotic fish that travels by changing its buoyancy and mass distribution (gliding) or by flapping tail fin (swimming). Field tests were carried out in Higgins Lake, MI, where the detection performance of the acoustic receiver on the robot was compared to that of stationary receivers at varying distances from the acoustic tags. Experimental results showed that the robotic platform can reliably detect the tags for distances up to 300m, which is well within the useful range for acoustic telemetry. Furthermore, analytical work has been done on distributed localization and tracking of a moving target using time-difference-of-arrival (TDOA) measurements. We demonstrated the ability of a network in localizing a moving target without any agent having sufficient information on its own, and then used those estimates in developing energy-efficient algorithms that ensure reliable localization performance.
Submitted by Xiaobo Tan
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The goal of this project is to create an integrative framework for the design of coupled biological and robotic systems that accommodates system uncertainties and competing objectives in a rigorous, holistic, and effective manner. The design principles are developed using a concrete, end-to-end application of tracking and modeling fish movement with a network of gliding robotic fish. The proposed robotic platform is an energy-efficient underwater gliding robotic fish that travels by changing its buoyancy and mass distribution (gliding) or by flapping tail fin (swimming). Field tests were carried out in Higgins Lake, MI, where the detection performance of the acoustic receiver on the robot was compared to that of stationary receivers at varying distances from the acoustic tags. Experimental results showed that the robotic platform can reliably detect the tags for distances up to 300m, which is well within the useful range for acoustic telemetry. Furthermore, analytical work has been done on distributed localization and tracking of a moving target using time-difference-of-arrival (TDOA) measurements. We demonstrated the ability of a network in localizing a moving target without any agent having sufficient information on its own, and then used those estimates in developing energy-efficient algorithms that ensure reliable localization performance.