A list of available projects for 4th year students enrolled in BEB 801/802 or students seeking independent research opportunities can be found on the student projects page. These projects cover a broad research area in aquatic robotics, and range in scope from a single semester to a Master's degree by research and even include some PhD topics. These are meant to be a general topic for a research project, with the specifics determined by an individual's knowledge, expertise and interests.

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. This project aims to obtain a synoptic view of these processes by developing algorithms that produce persistent monitoring missions for underwater vehicles. Balancing path following accuracy and sampling resolution in a given region, the developed techniques provide data collection capabilities across a range of spatiotemporal resolutions. We address a pressing need among ocean scientists to efficiently and effectively gather high-value data in key areas of interest. Developed algorithms are implemented in sea trials on underwater vehicles in southern California, and in Monterey Bay, California.

Intelligent path planning for AUVs is required to manoeuvre a vehicle to high-valued locations to perform data collection. In this research area, we focus on the use of ocean models to:

1. Track evolving features of interest
2. Increase navigational accuracy of AUVs
3. Optimise sampling strategies to place the AUV in the "right place at the right time"

One application of this effort is to develop derive the basic principles behind model synthesis for adaptive robot sampling for dynamic ocean features through the implementation of an end-to-end autonomous prediction and tasking system. A second application is to increase the utility of minimally actuated vehicles, e.g., gliders and floats.

The general submerged rigid body belongs to a class of simple mechanical control systems whose Lagrangian is of the form kinetic energy minus potential energy. There are many formulations for modelling such systems, and we choose a differential geometric formulation. The configuration space for an AUV corresponds naturally to a differentiable manifold in a one to one manner, and motions can be described via an affine connection control system on this manifold. This project focuses on increasing the autonomy of autonomous underwater vehicles by improving navigation capabilities via extensions to this affine geometric control theory. We are interested in extending the current notion of a kinematic reduction, investigating new formulations of an affine connection, and incorporating a wide range of external disturbances into the differential geometric architecture. Additionally, we are interested in developing a geometric formulation for vehicles that can alter their mass and buoyancy, e.g., gliders.

Coral reefs prosper in warm, shallow, clear, sunny and agitated waters,and are referred to as rain forests of the sea since they form some of the most diverse ecosystems on Earth. Computing an accurate estimate of the total surface area, volume and mass of an organism is considered of fundamental and practical importance in benthic ecology, specifically for understanding the complex dynamics of energy flow, cycling of organic matter, and carbonate production in aquatic ecosystems. However, few non-intrusive methods exist for in situ estimation, and many methods ultimately resort in destruction of the colony. This project is focused on developing a non-intrusive, and repeatable in situ method for generating a 3-D reconstruction of a coral reef environment for the purpose of estimating physical parameters, such as surface area, volume and long-term variability. The proposed technique aims to satisfy the following six requirements:

1. Works for images recorded in moderately turbid waters (visibility ~ 5 m), with non-uniform lighting, and with foreign objects (e.g., fish) that could interfere in the scene
2. Allows large data-sets and the investigation and analysis of significant areas of reef
3. Easily gather data in situ with commercial-off-the-shelf equipment
4. Deploy the system with a human diver or on an AUV for automated collection
5. Obtain measurement accuracies on the order of 1 mm
6. Perform the entire process including object reconstruction, and possibly object classification, on-line and in near-real time