CPS: Synergy: Tracking Fish Movement with a School of Gliding Robotic Fish

Abstract:

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 based on acoustic telemetry. There are five research tasks: (1) robotic platform enhancement by incorporating cellular data communication module, acoustic micro-modem, and telemetry receiver, (2) development of robust algorithms with analytical performance assurance for fish localization, (3) fish movement modeling using hidden Markov models and online model identification algorithms, (4) development of coordination and control schemes for the  robotic network to track fish, and (5) real-world experimental validation in Lake Huron, Thunder Bay. Over the past year, we have developed a distributed algorithm for estimating the location of a moving target (representing, for example, an acoustically tagged fish), based on time-difference-of-arrival measurements by a network of sensors. The algorithm combines extended Kalman filtering with a consensus protocol and has shown effectiveness in simulation. A new gliding robotic fish prototype has been developed, featuring modular configuration for sensors and significantly enhanced serviceability. In particular, it is equipped with an acoustic receiver for detecting a tagged fish in addition to five sensors for sampling biological and physical conditions of the aquatic environment.