In this project, we explore the challenges of developing smart and safe long-term autonomy for underwater vehicles.
Consider a science mission in which a marine robot is to follow and observe the behavior of a rare type of fish that feed on coral reefs. During its journey, the robot must:
Motivated by these issues, we aim to explore how human interaction with vehicles can be used to efficiently learn task specifications and autonomous behaviors in uncertain domains with incomplete/uncertain information. As part of this work, we develop new algorithmic strategies for efficiently programming and improving underwater vehicle autonomy in practical applications. Another aim of the project is to build a software stack and hardware testbed to support underwater vehicle research as well as developing new algorithmic strategies for efficiently programming and improving underwater vehicle autonomy in practical applications.