The role of the aquatic environment is of great importance: it plays a critical role in climate; it contains the highest biodiversity on the planet; ports are among the most critical infrastructures for trade and transportation; and as much as 40% of the global population lives within 100km of the shoreline. Improving our understanding of the underwater domain is essential. Using autonomous robots to collect additional information will be safer, more cost effective, and can be extended to a larger scale than previous methods. The goal of this project is to enable autonomous operations of robotic systems in underwater environments. In order to achieve this goal, the robot needs to be aware of the environment, and of its own position inside the environment. The robot needs to develop movement strategies that would facilitate the efficient and accurate estimation of its position and the location of obstacles/objects in the environment, while taking into account the errors in the measurements. The underwater domain presents several unique challenges: there is no Global Positioning System (GPS); communication, when available, has extremely limited bandwidth; visibility conditions, even in the best-case scenarios, are limited due to particulates in the water that obstruct the view. The investigator will advance the state of the art in four areas: information from different robot sensors will be used to calculate the position of the robot as it moves through the underwater domain; then, the investigator and his graduate students will use all available information to produce a representation of the environment the robot can use to navigate; next, planning will be implemented to guide the robot through the environment taking into account the shorter distance and the areas with viewing interest; and finally, the team will investigate new strategies for exploring unknown environments efficiently. The investigator will use his research results from the underwater realm to raise interest for students and the general populace towards science, technology, engineering, and mathematics. 
The goal of this project is to enable autonomous operations of robotic systems in underwater environments. In order to achieve this goal, the robot needs situational awareness. Additionally, the robot needs to develop motion strategies that would facilitate the efficient and accurate estimation of its pose and the location of points of interest in the environment, while taking into account uncertainty buildup and the effect of external forces such as wind or current. The underwater domain renders satellite-based GPS ineffective. Communications, when available, have extremely limited bandwidth; and visibility conditions are limited due to hazing and blurring, lighting variations over time, and color loss. The investigator will advance the state of the art in four areas: information from different sensors will be used to calculate the pose of the robot as it moves through the underwater domain; all available information will be utilized to produce a dense representation of the environment; next, a decision process will be implemented to guide the robot through the environment taking into account efficiency (shorter distance) and the areas with viewing interest; finally, new strategies for exploring and covering unknown environments efficiently will be investigated. More specifically, robustness measures and divergence predictors will be developed for the state estimation in order to provide early warnings of erroneous estimates. Measuring the quality of the different sensors will result in the judicious use of the subset of sensors that provide accurate information. The mapping challenge will be addressed by augmenting the feature-based map with features generated from the lighting variations, such as shadows and caustic patterns. Coverage patterns will be employed in open areas with limited obstacles, while a frontier-based strategy will guide the underwater vehicle to unexplored areas. Returning to mapped areas in a systematic manner will maintain the localization uncertainty below a user defined level. The results will be published in conferences and journals of robotics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
