面向分布式建筑的尺度场传感机器人团队与环境设计的计算复杂度(扩展摘要)

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI:10.1109/ACSOS-C52956.2021.00059

T. Wareham, A. Vardy

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引用次数: 3

摘要

机器人队伍和施工环境的自动化设计是一个重要的研究课题。尽管迄今为止大多数工作都集中在视觉传感机器人上，但了解与感知标量场(如化学梯度)的机器人相关的设计算法选择将是非常有趣的。在本文中，我们首次对设计用于建筑任务的尺度场传感机器人团队和环境的问题进行了计算和参数化的复杂性分析。我们的研究结果表明，尺度场传感机器人的可驾驭性和难驾驭性结果模式与视觉传感机器人的模式大致相似。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Computational Complexity of Designing Scalar-Field Sensing Robot Teams and Environments for Distributed Construction (Extended Abstract)

The automatic design of robot teams and environments for construction tasks is an important research problem. Though most work to date has focused on visual sensing robots, it would be of great interest to know algorithmic options for design relative to robots that sense scalar fields such as chemical gradients. In this paper we give the first computational and parameterized complexity analyses of the problems of designing scalar-field sensing robot teams and environments for construction tasks. Our results suggest that the pattern of tractability and intractability results for scalar-field sensing robots is broadly similar to that for visual sensing robots.

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2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

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