Multiple-vehicle resource-constrained navigation in the deep ocean

Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2011.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 139-148).This thesis discusses sensor management methods for multiple-vehicle fleets of autonomous underwater vehicles, which will allow for more efficient and capable infrastructure in marine science, industry, and naval applications. Navigation for fleets of vehicles in the ocean presents a large challenge, as GPS is not available underwater and dead-reckoning based on inertial or bottom-lock methods can require expensive sensors and suffers from drift. Due to zero drift, acoustic navigation methods are attractive as replacements or supplements to dead-reckoning, and centralized systems such as an Ultra-Short Baseline Sonar (USBL) allow for small and economical components onboard the individual vehicles. Motivated by subsea equipment delivery, we present model-scale proof-of-concept experimental pool tests of a prototype Vertical Glider Robot (VGR), a vehicle designed for such a system. Due to fundamental physical limitations of the underwater acoustic channel, a sensor such as the USBL is limited in its ability to track multiple targets-at best a small subset of the entire fleet may be observed at once, at a low update rate. Navigation updates are thus a limited resource and must be efficiently allocated amongst the fleet in a manner that balances the exploration versus exploitation tradeoff. The multiple vehicle tracking problem is formulated in the Restless Multi-Armed Bandit structure following the approach of Whittle in [108], and we investigate in detail the Restless Bandit Kalman Filters priority index algorithm given by Le Ny et al. in [71]. We compare round-robin and greedy heuristic approaches with the Restless Bandit approach in computational experiments. For the subsea equipment delivery example of homogeneous vehicles with depth-varying parameters, a suboptimal quasi-static approximation of the index algorithm balances low landing error with safety and robustness. For infinite-horizon tracking of systems with linear time-invariant parameters, the index algorithm is optimal and provides benefits of up to 40% over the greedy heuristic for heterogeneous vehicle fleets. The index algorithm can match the performance of the greedy heuristic for short horizons, and offers the greatest improvement for long missions, when the infinite-horizon assumption is reasonably met.by Brooks Louis-Kiguchi Reed.S.M

Controller design for underwater vehicle systems with communication constraints

Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2015.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 181-201).Real-time cooperation between autonomous vehicles can enable time-critical missions such as tracking and pursuit of a dynamic target or environmental feature, but relies on wireless communications. Underwater, communication over distances beyond about one hundred meters is almost exclusively accomplished through acoustics, which bring challenges such as propagation delays, low data rates, packet loss, and scheduling constraints due to interference and limited bandwidth. These limitations make underwater pursuit missions preeminent applications of networked control. Motivated by such applications, this thesis presents contributions towards multi-vehicle feedback control in the presence of severe communication constraints. The first major area of work considers the formulation and solution of new underwater multi-vehicle tracking and pursuit problems using closed-loop control. We begin with a centralized robust optimization approach for multicast routing and power control which is suitable for integration with vehicle control. Next, we describe field experiments in range-based target pursuit at high tracking bandwidths in a challenging shallow-water environment. Finally, we present a methodology for pursuit of dynamic ocean features such as fronts, which we validate using hindcast ocean model data. The primary innovation is a projection algorithm which carries out linearization of ocean model forecast dynamics and uncertainty directly in vehicle coordinates via a forward model technique. The resulting coupled linear stochastic system is suitable for networked control. The second area of work presents a unified formalism for multi-vehicle control and estimation with measurement, control, and acknowledgment packets all subject to scheduling, delays and packet loss. The modular framework we develop is built around a jump linear system description incorporating receding horizon optimization and buffering at actuators. Integration of these elements enables synthesis of a novel technique for estimation using delayed and lossy control acknowledgments-a desirable and practical capability of fielded systems that has not been considered to date. Simulations and field experiments demonstrate the effectiveness of our approach.by Brooks Louis-Kiguchi Reed.Ph.D