A flexible, reaction-wheel-driven fish robot: Flow sensing and flow-relative control

Distributed Flow Estimation for Autonomous Underwater Robots Using Proper Orthogonal Decomposition-Based Model Reduction

“…The optimal sensor placement for observing POD coefficient c 1 is one sensor near the polar angle 160. 21 Based on the observability indices, we propose the following composite performance index to assist with the sensor placement: (19) where l 1 , l 2 , and l 3 are the design coefficients that balance the weights of performance indices. In sensor placement design, we will use simulation/experiment to search for optimal sensor positions that minimize the composite index to achieve maximum observability.…”

“…Parallel to designing flow sensors to directly measure local flow velocity, more and more research efforts have been put into using multiple low-cost, commercially available sensors, and a flow estimation algorithm to estimate the whole flow field. Inspired by the high performance of fish lateral line, scientists and engineers have been making great efforts in developing similar flow-sensing systems [15][16][17][18][19][20][21][22]. The lateral line helps aquatic vertebrates sense surrounding flow fields and assists with flow relative behaviors, such as rheotaxis, predation, and schooling [23].…”

“…The lateral line helps aquatic vertebrates sense surrounding flow fields and assists with flow relative behaviors, such as rheotaxis, predation, and schooling [23]. Some papers use linear regression to approximate the flow field [22], while others use nonlinear estimation algorithms including extended Kalman filter [16], Bayesian filter [15,[17][18][19], unscented Kalman filter [20], and particle filter [21] to assimilate distributed (pressure and velocity) sensor measurements for flow sensing. For example, in our prior work [18,19], co-author Zhang studied flow estimation for a Joukowski hydrofoil locomoting in a uniform flow using a Bayesian filter.…”

“…The flow estimation algorithms typically require a mathematical flow model, which is obtainable through one of the many methods such as analytical flow modeling [15][16][17][18][19], computational fluid dynamics (CFD) simulation [20], and towing tank experiments [21,22]. The analytical flow modeling method is easy-to-implement and cost-effective.…”

“…For example, the potential flow model in Refs. [15] and [19] can only be used with the same foil shape described by a conformal mapping function. CFD simulation on the other hand can provide accurate flow models for underwater robots with any designed shape.…”