Aditya S. Gadre

Toward underwater navigation based on range measurements from a single location

Navigation technology is considered that enables an underwater vehicle to compute its trajectory in real-time by utilizing range measurements from a single known location. This concept is especially attractive for small underwater vehicles where more traditional navigation technology is prohibitive due to volume constraints. By assessing local observability of the underwater vehicle and available measurements about potential vehicle trajectories, we explicitly characterize those trajectories that can be asymptotically estimated. It is shown that all but a small class of trajectories can be estimated.

A complete solution to underwater navigation in the presence of unknown currents based on range measurements from a single location

An underwater navigation algorithm is considered that enables an underwater vehicle to compute its trajectory in the presence of unknown currents by utilizing range measurements from a single known location. There exists a small set of trajectories for which the algorithm does not converge. By assessing local observability about potential vehicle trajectories, we characterize those trajectories that cannot be asymptotically estimated. The navigation algorithm is illustrated using computer simulation and a hardware experiment.

Underwater navigation in the presence of unknown currents based on range measurements from a single location

An underwater navigation algorithm is considered that enables an underwater vehicle to compute its trajectory in the presence of unknown currents by utilizing range measurements from a single known location. There exists a small set of trajectories for which the algorithm does not converge. By assessing local observability about potential vehicle trajectories, we characterize those trajectories that cannot be asymptotically estimated. The navigation algorithm is illustrated using computer simulation and a hardware experiment.

Implementation of a Cooperative Navigation Algorithm on a Platoon of Autonomous Underwater Vehicles

Time-synchronized acoustic data transmissions can be used to calculate the relative range between underwater vehicles. Relative range, along with other information shared over the communication link, can be used for cooperative navigation. The low bandwidth and latency of the acoustic channel do not allow for a direct implementation of a standard Kalman filter for cooperative navigation. Specifically, there is insufficient bandwidth to share the data needed to accurately propagate the estimation error covariance matrix. Instead, we share only a scalar function of the main diagonal elements of the covariance matrix. We present analysis that suggests this is a reasonable approach and experimental results that demonstrate its efficacy.

Design elements of a small low-cost autonomous underwater vehicle for field experiments in multi-vehicle coordination

Field operations with multiple autonomous underwater vehicles are often expensive and logistically complex, yet the development of decentralized control and estimation algorithms suitable for cooperating autonomous vehicles requires in situ testing and experimentation. Toward the goal of creating a field-deployable testbed for multi-vehicle control and estimation algorithms, a small, inexpensive autonomous underwater vehicle has been developed. Design features of the AUV are presented along with design trade-offs imposed by developing an AUV that is small, inexpensive, yet fully-field deployable.

Design of a prototype miniature autonomous underwater vehicle

Platoons of cooperating autonomous underwater vehicles have the potential to contribute significantly to scientific investigations in the marine environment. Platoons of vehicles can survey large areas, adaptively track and measure time-varying processes such as tidal fronts and algal blooms, and they are robust to single-point failures. We have developed a prototype miniature low-cost autonomous underwater vehicle to address the platform requirements of these missions. The vehicle is designed as a test-bed for the development of distributed control and estimation algorithms, and for experiments in advanced navigation and control.

Cooperative localization of an acoustic source using towed hydrophone arrays

We describe field experiments in which a team of autonomous underwater vehicles cooperatively localize an acoustic source. The team implements a data fusion algorithm to enhance the localization performance of each individual vehicle and implements a decentralized motion control algorithm so that each vehicle maneuvers to minimize the joint localization error of the acoustic source. Each autonomous underwater vehicle is equipped with a custom-designed towed hydrophone array that measures the bearing angle between the array and the acoustic source. The noise statistics of the hydrophone arrays are state-dependent, and a generalized Kalman filter that accounts for the state-dependant measurement noise is utilized for localization.

Control-Oriented Planar Motion Modeling of Unmanned Surface Vehicles

This paper describes a comparison of experimentally identified dynamic models for the planar motion of an unmanned surface vehicle (USV). The objective is to determine a model which is rich enough to enable effective motion planning and control, simple enough to allow straight forward parameter identification, and general enough to describe a variety of hullforms and actuator configurations. Starting from a three degree-of-freedom nonlinear model obtained from physical principles, we consider four simplified variants: (1) a linear model obtained by linearizing about straight, constant-speed motion, (2) a first order steering model (for turn rate) coupled with a first order speed model, (3) a second order steering model (for turn rate and sideslip angle), coupled with a first order speed model, and (4) a nonlinear model for low speed operation. The paper provides analysis of system identification data collected from field trials of three USV platforms in Summer 2010. The platforms represent three distinct control system implementations: a servo-actuated outboard engine, a servo-actuated jet-drive thruster, and differential thrusters.

Boundary Tracking and Rapid Mapping of A Thermal Plume Using an Autonomous Vehicle

Adaptive sampling algorithms for rapidly mapping the outflow plume from a nuclear power plant are presented. Plume detection is based on the notion of a plume indicator function that, loosely speaking, indicates the likelihood that an environmental sample is from the plume rather than from the ambient environment. For the case of a power plant outflow, we show that a plume indicator function composed of several measured parameters, such as temperature, salinity, dissolved oxygen, and flow magnitude, greatly enhance the robustness of our adaptive sampling algorithms. Successful field trials using a small autonomous surface vehicle are reported

A topological map based approach to long range operation of an unmanned surface vehicle

We present an approach to planning dynamically feasible vehicle trajectories for applications where the vehicle operates in very large environments and for which a kinematic model is a poor approximation of the vehicles dynamics. Our approach is based on new methods for generating topological maps of a sparse and natural environment, such as a tropical riverine system.