# Towards Long-term Autonomy: A Perspective from Robot Learning

arXiv: https://arxiv.org/abs/2212.12798 · HTML: https://mlsanity.com/paper/2212.12798/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 32 references that are in the map.
- First posted on arXiv 24 Dec 2022.

## Builds on (most cited first, 8 of 8)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Continual Learning for Robotics: Definition, Framework, Learning Strategies, Opportunities and Challenges](https://mlsanity.com/paper/1907.00182/) (2019)
- [Artificial Intelligence for Long-Term Robot Autonomy: A Survey](https://mlsanity.com/paper/1807.05196/) (2018)
- [The STRANDS Project: Long-Term Autonomy in Everyday Environments](https://mlsanity.com/paper/1604.04384/) (2016)
- [3DOF Pedestrian Trajectory Prediction Learned from Long-Term Autonomous Mobile Robot Deployment Data](https://mlsanity.com/paper/1710.00126/) (2017)
- [Multisensor Online Transfer Learning for 3D LiDAR-based Human Detection with a Mobile Robot](https://mlsanity.com/paper/1801.04137/) (2018)
- [Learning on the Job: Long-Term Behavioural Adaptation in Human-Robot Interactions](https://mlsanity.com/paper/2203.10518/) (2022)
- [Efficient Online Transfer Learning for 3D Object Classification in Autonomous Driving](https://mlsanity.com/paper/2104.10037/) (2021)

## Built on by (most cited first, 1 of 1)

- [Online Context Learning for Socially Compliant Navigation](https://mlsanity.com/paper/2406.11495/) (2024)

## Abstract (arXiv)

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".