Trend and Bounds for Error Growth in Controlled Lagrangian Particle Tracking

Abstract

This paper establishes the method of controlled Lagrangian particle tracking (CLPT) to analyze the offsets between physical positions of marine robots in the ocean and simulated positions of controlled particles in an ocean model. The offset, which we term the CLPT error, demonstrates distinguished characteristics not previously seen in drifters and floats that cannot be actively controlled. The CLPT error growth over time is exponential until it reaches a turning point that only depends on the resolution of the ocean model. After this turning point, the error growth slows down significantly to polynomial functions of time. In the ideal case, a theoretical upper threshold on exponential growth of CLPT error can be derived. These characteristics are proved theoretically, verified via simulation, and justified with ocean experimental data. The method of CLPT may be applied to improve the accuracy of ocean circulation models and the performance of navigation algorithms for marine robots.

Glider CT

“…To deal with these problems, we need to use a motion prediction system to predict the trajectories of the gliders. Such system has been developed by us previously [12] and has been used effectively in several glider deployments in the ocean [24,12,8,21]. It has been verified that the system can generate realistic predictions of the underwater trajectories of gliders.…”

Future Trends in Marine Robotics [TC Spotlight]

“…A key challenge in mobile ocean sensing is coordinating the motion of vehicles to achieve better map-making results. Since networks often operate over a larger area than a single vehicle, ocean circulation models may provide very useful information about the strength and direction of the current that affects the motion control and path planning of the platforms [21], [22]. New research directions are emerging here as well.…”

An adaptive control law for controlled Lagrangian particle tracking

“…Controlled Lagrangian particle tracking (CLPT), which is a new paradigm for the evaluation of ocean model accuracy, has been developed in [15,16]. To apply CLPT, we simulate a vehicle motion model with incorporated flow models and controllers to generate the predicted trajectory of AUVs, then the predicted trajectory is compared with the measured true trajectory of AUVs.…”

“…In this paper, we present an adaptive control law to decrease CLPE. CLPE can be increasing over time when we use feedback controllers designed in [15,16]. This implies that the true trajectory is significantly deviated from the predicted trajectory.…”