[MITEI Seed] Robot learning from human operators for efficient renewable energy infrastructure maintenance

This research will develop robots that can learn maintenance tasks from natural human feedback, including physical intervention and verbal instructions. A key innovation is enabling a fleet of robots to intelligently coordinate when to ask for human help, allowing one operator to efficiently supervise multiple robots performing renewable energy infrastructure maintenance. By leveraging human-in-the-loop robot learning we can reduce costs, improve safety, and accelerate clean energy deployment.