In the future, service robots are expected to be able to operate autonomously for long periods of time without human intervention. Many work striving for this goal have been emerging with the development of robotics, both hardware and software. Today we believe that an important underpinning of long-term robot autonomy is the ability of robots to learn on site and on-the-fly, especially when they are deployed in changing environments or need to traverse different environments. In this paper, we examine the problem of long-term autonomy from the perspective of robot learning, especially in an online way, and discuss in tandem its premise "data" and the subsequent "deployment".

A British-led consortium is developing new computer software to help the robots of the future navigate through the messy and cluttered environments of working life, working independently for up to 120 days. Dr Nick Hawes, lecturer in intelligent robotics at the University of Birmingham, is co-ordinating the work. He says that although robots can currently work in "predictable" environments for short periods of times, he wants to push for further developments. "Recent advances in robotics and artificial intelligence have enabled mobile robots to operate intelligently in predictable environments for limited periods of time," he said. "Our challenge is to develop robots which can go way beyond this, running reliably in dynamic real-world security and care environments for as long as they're required. This will make these machines truly useful assistants in our workplaces."