Software improves autonomy of robotic ocean surveillance

Researchers at the Massachusetts Institute of Technology (MIT) and the University of Southern California are said to have improved the intelligence of autonomous vehicles under a programme sponsored by the US Navy, dubbed Adaptive Networks for Threat and Intrusion Detection or Termination.

They developed a persistent surveillance theory that provides a framework for decision-making software, which maximises a robot’s collection of information over a given area.

‘The ability to do surveillance that takes into account the actual conditions of the environment brings a whole new level of automation and capability,’ said Dr Daniela Rus, co-director of MIT’s computer science and artificial intelligence laboratory centre for robotics.

‘We have come up with a solution that lets the robot do local reasoning to make decisions and adjust the path autonomously without having to come up to the surface to interact with humans,’ she added.

The scientists produced an algorithm that incorporates both the user’s sensing priorities and environmental factors, such as ocean currents, into a computer model to help undersea robots conduct surveys and mapping missions more efficiently.