Experimenting with robotic intra-logistics domains
Martin Gebser, Philipp Obermeier, Thomas Otto, Torsten Schaub, Orkunt, Sabuncu, Van Nguyen, Tran Cao Son

TL;DR
This paper introduces the asprilo framework, a versatile tool for experimental research in robotic intra-logistics, enabling benchmarking, visualization, and analysis of multi-agent planning approaches within a unified, logic-based environment.
Contribution
The paper presents asprilo, a new framework combining benchmark generation, solution checking, and visualization for robotic intra-logistics, supporting diverse ASP techniques and fostering research and education.
Findings
asprilo effectively supports complex intra-logistics scenarios
it enables benchmarking of different planning approaches
visualization aids in analyzing solution validity and strategies
Abstract
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,…
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