We’re all excited for the Jetson-like world with robotics in every aspect of life, solving a variety of challenging problems. But most are failing to leave safe, controlled lab spaces. Why?
The Imperfect Information Problem: Operating in the real-world requires robust solutions that can readily manage the chaos of dynamic environments and imperfect data. In the case of robotics, this is the deciding factor between a commercially-successful robot and a failure to launch.
Why Marine Vehicles: Coordinating marine vehicles is an ideal example of automation in a complex, dynamic environment. How do you ensure that your vehicles can safely track and operate around other ships, make the most of the variety of potentially-disagreeing sensors, and robustly handle the busy environment while completing critical tasks?
The NavAbility Case Study: At NavAbility we’re using data from MIT SeaGrant‘s REx/Philos vehicles to demonstrate how any robot can extract map information from multiple sensors, identify and track dynamic objects like ships, and use prior information to navigate effectively in a dynamic environment.
