# The STRANDS Project: Long-Term Autonomy in Everyday Environments

arXiv: https://arxiv.org/abs/1604.04384 · HTML: https://mlsanity.com/paper/1604.04384/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2016.

## Built on by (most cited first, 13 of 13)

- [ERASOR: Egocentric Ratio of Pseudo Occupancy-based Dynamic Object Removal for Static 3D Point Cloud Map Building](https://mlsanity.com/paper/2103.04316/) (2021)
- [Reasoning with Scene Graphs for Robot Planning under Partial Observability](https://mlsanity.com/paper/2202.10432/) (2022)
- [Visual Representation Learning for Preference-Aware Path Planning](https://mlsanity.com/paper/2109.08968/) (2021)
- [GS-LTS: 3D Gaussian Splatting-Based Adaptive Modeling for Long-Term Service Robots](https://mlsanity.com/paper/2503.17733/) (2025)
- [FEAST: A Flexible Mealtime-Assistance System Towards In-the-Wild Personalization](https://mlsanity.com/paper/2506.14968/) (2025)
- [A Framework for Learning from Demonstration with Minimal Human Effort](https://mlsanity.com/paper/2306.09211/) (2023)
- [Learning on the Job: Long-Term Behavioural Adaptation in Human-Robot Interactions](https://mlsanity.com/paper/2203.10518/) (2022)
- [Machine Learning Systems: A Survey from a Data-Oriented Perspective](https://mlsanity.com/paper/2302.04810/) (2023)
- [Towards Long-term Autonomy: A Perspective from Robot Learning](https://mlsanity.com/paper/2212.12798/) (2022)
- [PEPA: a Persistently Autonomous Embodied Agent with Personalities](https://mlsanity.com/paper/2603.00117/) (2026)
- [Competence-Aware Path Planning via Introspective Perception](https://mlsanity.com/paper/2109.13974/) (2021)
- [SEAL: Semantic Frame Execution And Localization for Perceiving Afforded Robot Actions](https://mlsanity.com/paper/2303.14067/) (2023)
- [A Glimpse into Long-term Physical Coexistence with Intelligent Robots](https://mlsanity.com/paper/2607.11377/) (2026)

## Abstract (arXiv)

Thanks to the efforts of the robotics and autonomous systems community, robots are becoming ever more capable. There is also an increasing demand from end-users for autonomous service robots that can operate in real environments for extended periods. In the STRANDS project we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots, and deploying these systems for long-term installations in security and care environments. Over four deployments, our robots have been operational for a combined duration of 104 days autonomously performing end-user defined tasks, covering 116km in the process. In this article we describe the approach we have used to enable long-term autonomous operation in everyday environments, and how our robots are able to use their long run times to improve their own performance.