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vPlanSim: An Open Source Graphical Interface for the Visualisation and Simulation of AI systems 31

vPlanSim: An Open Source Graphical Interface for the Visuali...

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31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Roberts, Jamie O. Mastorakis, Georgios Lazaruk, Brad Franco, Santiago Stokes, Adam A. Bernardini, Sara School of Engineering Institute for Integrated Micro and Nano Systems University of Edinburgh United Kingdom EPSRC CDT in Robotics and Autonomous Systems Edinburgh Centre for Robotics United Kingdom Department of Computer Science Royal Holloway University of London United Kingdom

ISBN: (纸本)9781713832317

We introduce vPlanSim, an open source tool to aid in AI PDDL development. This tool is primarily aimed at researchers and developers who need a visual representation of their planning problem so that they can make useful insights into the performance of their system, and also to naturally convey their system to others. It is an open-source tool which allows a user to quickly and easily visualise a target environment to generate the problem files and also to visualise a plan. It is particularly well suited to spatial planning problems. This paper will demonstrate vPlanSim on 2D and 3D planning problems. vPlanSim is based on a small and carefully considered set of dependencies such as VTK and PyQt. It can be set up on different platforms and compiled from source with minimal effort. The code is and maintained via a clear code review mechanism. We welcome contributions from the open-source community. Copyright © 2021, Proceedings of the 31st International Conference on Automated Planning and Scheduling. All rights reserved.

关键词： Open systems

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autonomous Building of Structures in Unstructured Environments via AI Planning 31

Autonomous Building of Structures in Unstructured Environmen...

引用

31st International Conference on Automated Planning and Scheduling, ICAPS 2021

作者： Roberts, Jamie O. Franco, Santiago Stokes, Adam A. Bernardini, Sara School of Engineering Institute for Integrated Micro and Nano Systems University of Edinburgh United Kingdom EPSRC CDT in Robotics and Autonomous Systems Edinburgh Centre for Robotics United Kingdom Department of Computer Science Royal Holloway University of London United Kingdom

ISBN: (纸本)9781713832317

In this paper, we offer a novel AI planning representation, based on a Cartesian coordinate system, for enabling the autonomous operations of Multi-Robot systems in 3D environments. Each robot in the system has to conform to unique actuation and connection constraints that create a complex set of valid configurations. Our approach allows Multi-Robot systems to self-assemble themselves into larger structures via AI planning, with the overarching goal of providing structural capabilities in harsh and uncertain environments. In comparing four different PDDL (Planning Domain Definition Language) domain representations, we show that our novel formulation satisfies the practical requirements emerging from robot deployment in the real world, resulting in an AI planning system that is accurate and efficient. We scale up performance by implementing direct FDR (Finite Domain Representation) generation based on the best performing PDDL model, bypassing the PDDL-to-FDR translation used by the majority of modern planners. The proposed approach is general and can be applied to a broad range of AI problems involving reasoning in 3D spaces. Copyright © 2021, Proceedings of the 31st International Conference on Automated Planning and Scheduling. All rights reserved.

关键词： Multipurpose robots

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