有界拉伸的连通协调运动规划

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Sándor P. Fekete, Phillip Keldenich, Ramin Kosfeld, Christian Rieck, Christian Scheffer
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引用次数: 7

摘要

我们考虑了一大群简单、相同的机器人的连接协调运动规划问题:从给定的机器人起始网格配置开始,我们需要通过一系列平行、无碰撞的机器人运动来达到所需的目标配置,从而使这组机器人在所有整数次上导出连接网格图。目标是最大限度地缩短运动计划的完成时间,即在最短的时间内达到新的配置。我们证明了这个问题是NP完全的,即使是在决定是否可以实现2的生成跨度时,也可以在多项式时间内检查是否可以实现1的生成跨度。在算法方面,我们通过实现恒定尺度的恒定拉伸,建立了两个基本参数的同时常数因子近似。比例形状(通过用相同的乘法因子增加给定物体的所有维度而产生)在之前关于自组装的开创性工作中已经被考虑过,通常具有无界或对数比例因子;我们提供了一个以常数为界的广义比例因子的方法。此外,我们的算法实现了一个恒定的拉伸因子:如果将开始配置映射到目标配置需要最大曼哈顿距离d,那么我们整个日程的总持续时间是\(\mathcal{O}(d)\),这在恒定因子下是最优的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Connected coordinated motion planning with bounded stretch

Connected coordinated motion planning with bounded stretch

We consider the problem of connected coordinated motion planning for a large collective of simple, identical robots: From a given start grid configuration of robots, we need to reach a desired target configuration via a sequence of parallel, collision-free robot motions, such that the set of robots induces a connected grid graph at all integer times. The objective is to minimize the makespan of the motion schedule, i.e., to reach the new configuration in a minimum amount of time. We show that this problem is NP-complete, even for deciding whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a makespan of 1 can be achieved. On the algorithmic side, we establish simultaneous constant-factor approximation for two fundamental parameters, by achieving constant stretch for constant scale. Scaled shapes (which arise by increasing all dimensions of a given object by the same multiplicative factor) have been considered in previous seminal work on self-assembly, often with unbounded or logarithmic scale factors; we provide methods for a generalized scale factor, bounded by a constant. Moreover, our algorithm achieves a constant stretch factor: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of d, then the total duration of our overall schedule is \(\mathcal {O}(d)\), which is optimal up to constant factors.

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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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