Towards Long-term Autonomy: A Perspective from Robot Learning
This is an incremental perspective piece discussing the importance of online learning for long-term robot autonomy in service robotics.
The paper examines the challenge of enabling service robots to operate autonomously for extended periods without human intervention, focusing on the need for robots to learn on-site and on-the-fly in changing environments, but does not present specific results or concrete numbers.
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".