GobySoft has extensive experience implementing autonomy algorithms on a variety of marine vehicles (robots) and supporting these autonomous vehicles at sea. This includes development, simulation/testing, and implementation of autonomy algorithms and behaviors that allow for dynamically-configurable and/or adaptive motion of the autonomous marine vehicles. A complete list of our autonomy software contributions can be found here, and a number of our former and current major autonomy projects are further described below.
Distributed Agile Submarine Hunting (DASH)
Website: DARPA DASH Program
This DARPA project is focused on using deep ocean sonar nodes for rapid detection of submarines overhead. GobySoft is an integral software designer for the Submarine Hold at RisK (SHARK) prototype, an unmanned underwater vehicle (UUV). We have contributed to the design of the autonomy and a significant number of integration and sea support tasks. In addition, we have designed the SHARK communications infrastructure.
Mission configuration structure for MOOS & IvP Helm autonomy on marine vehicles
Configuration management is a significant task for deployments of multiple vehicles for different tasks. We developed a mission configuration system that works on a class-based inheritance design to rapidly and portably switch between different vehicles and different applications (or cruises). See this paper for more details and the LAMSS project page for the missions-lamss repository.
Adaptive oceanographic feature tracking
Researchers in the oceanographic community are often limited in their shipboard data collection time due to the high cost of available ship time. Thus, it is important to perform sampling of oceanographic features both efficently and accurately to gather the necessary data sets. This is often complicated further by the spatiotemporally dynamic nature of hydrographic features from one location to the next based on the local environment.
An alternatve approach to the traditional oceanographic feature sampling methods of towing instruments behind a ship or deploying instruments off the side of a stationary vessel in preplanned transects is to deploy one or more AUVs to preform the sampling. To even further improve the efficiency of AUV sampling beyond pre-planned survey patterns, environmentally adaptive autonomy behaviors may be employed. Using adaptive autonomy, an AUV can autonomously survey an area initally, determine where the desired feature is located, and actively track the feature as it moves and/or changes shape in space and time without a human operator in the loop. We have experience developing and implementing such environmentally adaptive behavior algorithms using the MOOS middleware and IvP Helm autonomy.