# Experimenting with robotic intra-logistics domains

arXiv: https://arxiv.org/abs/1804.10247 · HTML: https://mlsanity.com/paper/1804.10247/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2018.

## Built on by (most cited first, 12 of 12)

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- [Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance](https://mlsanity.com/paper/2105.10993/) (2021)
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- [Clingraph: A System for ASP-based Visualization](https://mlsanity.com/paper/2303.10118/) (2023)
- [Automata for dynamic answer set solving: Preliminary report](https://mlsanity.com/paper/2109.01782/) (2021)
- [Dialogue Possibilities between a Human Supervisor and UAM Air Traffic Management: Route Alteration](https://mlsanity.com/paper/2308.06411/) (2023)
- [SM-based Semantics for Answer Set Programs Containing Conditional Literals and Arithmetic](https://mlsanity.com/paper/2511.01753/) (2025)
- [Automata Techniques for Temporal Answer Set Programming](https://mlsanity.com/paper/2109.08279/) (2021)
- [Relating Answer Set Programming and Many-sorted Logics for Formal Verification](https://mlsanity.com/paper/2502.09230/) (2025)
- [Diminution: On Reducing the Size of Grounding ASP Programs](https://mlsanity.com/paper/2508.08633/) (2025)
- [GRACE: A Unified 2D Multi-Robot Path Planning Simulator & Benchmark for Grid, Roadmap, And Continuous Environments](https://mlsanity.com/paper/2603.10858/) (2026)

## Abstract (arXiv)

We introduce the asprilo [1] framework to facilitate experimental studies of approaches addressing complex dynamic applications. For this purpose, we have chosen the domain of robotic intra-logistics. This domain is not only highly relevant in the context of today's fourth industrial revolution but it moreover combines a multitude of challenging issues within a single uniform framework. This includes multi-agent planning, reasoning about action, change, resources, strategies, etc. In return, asprilo allows users to study alternative solutions as regards effectiveness and scalability. Although asprilo relies on Answer Set Programming and Python, it is readily usable by any system complying with its fact-oriented interface format. This makes it attractive for benchmarking and teaching well beyond logic programming. More precisely, asprilo consists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques. Importantly, the visualizer's animation capabilities are indispensable for complex scenarios like intra-logistics in order to inspect valid as well as invalid solution candidates. Also, it allows for graphically editing benchmark layouts that can be used as a basis for generating benchmark suites. [1] asprilo stands for Answer Set Programming for robotic intra-logistics