|Cooperative AUV SLAM
Cooperative mapping is challenging underwater primarily due to the difficulties associated with the acoustic communications channel. It is high latency, low bandwidth, unreliable, and unacknowledged. In this work we are developing algorithms that are able to overcome these challenges and provide robust cooperative AUV SLAM algorithms.
|Ship Hull Inspection
In collaboration with Franz Hover (MIT), Ryan Eustice (UMich) and Michael Kaess (CMU), we are addressing the problem of navigation for underwater vehicles in harbor surveillance tasks including ship hull inspection. Maintaining accurate localization is important for navigation and ensuring coverage, but is difficult in cluttered environments such as harbors, where acoustic-based localization systems are difficult to employ.
An autonomous underwater vehicle (AUV) is achieved that integrates state of the art simultaneous localization and mapping (SLAM) into the decision processes. This autonomy is used to carry out undersea target reacquisition missions that would otherwise be impossible with a low-cost platform. The AUV requires only simple sensors and operates without navigation equipment such as Doppler Velocity Log, inertial navigation or acoustic beacons. Demonstrations of the capability show that the vehicle can carry out the task in an ocean environment. The system includes a forward looking sonar and a set of simple vehicle sensors.
|Cooperative AUV Navigation
Localization or navigation of AUVs using only onboard local sensors, such as a Doppler Velocity Logger (DVL) or Inertial Measurement Unit (IMU), are certain to experience accumulated positioning error. One can, of course, utilize more precise sensors to reduce the rate of accumulated error but uncertainty will eventually grow. Two approaches have been considered in this work: 1. AUV and CNA Cooperation 2. AUV-only Cooperation.