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English(EN) Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

新的D2OC方法实现了高效的非线性多智能体空间覆盖

研究人员开发了密度驱动最优控制(D2OC)的非线性扩展,用于多智能体空间覆盖。这种新方法D2OC通过基于Wasserstein的目标驱动智能体分布趋向期望密度,并通过序贯凸规划将其扩展到非线性系统的有限时间域控制。对独轮车和四旋翼无人机团队的仿真表明,其性能与非线性模型预测控制相当,但计算时间显著减少。 AI

影响 这项研究为多智能体系统的空间覆盖提供了一种计算效率更高的方法,可能对机器人和自主系统产生影响。

排序理由 该集群包含一篇详细介绍多智能体系统新控制方法的 istat_research paper。 [lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.MA (Multiagent) 阅读 →

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新的D2OC方法实现了高效的非线性多智能体空间覆盖

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该集群包含一篇详细介绍多智能体系统新控制方法的 istat_research paper。 [lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Kooktae Lee ·

    用于多智能体空间覆盖的非线性密度驱动最优控制(D2OC)与序贯凸规划

    This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributions. Rather than assigning individual target locations, D2OC drives the collective spatial distribution of agents toward a desired…