通信降级下的分布式多机器人任务分配：性能、可靠性与计算基准

中文摘要 AI 辅助

为自主平台上的嵌入式部署选择分布式多机器人任务分配（MRTA）方法时，需要考虑的不仅仅是路径性能。我们在协同访问（CV）场景中对六种分布式MRTA分配器（CBAA、ACBBA、PI、HIPC、DMCHBA和DGA）进行了基准测试，以刻画MinMax和MinSum行程、通信鲁棒性和需求、分配可靠性、计算负担以及规模敏感性之间的权衡。核心研究使用了500对十个目标的实例，涵盖25种理想和降级通信条件，包括Bernoulli丢包、Gilbert-Elliott丢包和Rayleigh衰落，并额外开展了针对预分配、执行集成计算以及对网格大小、机器人密度和目标负载敏感性的实验。在24种受损核心条件下，DGA和DMCHBA分别以24.49和24.78步的平均MinMax行程达到最低。HIPC以66.95步的平均MinSum行程略微领先，其次是DGA的67.22步，这两种方法在所有受损条件下均占据前两名。DMCHBA的发布强度最低，为每团队步2.08次发布。在十个目标的预分配中，HIPC和DMCHBA在所有测试条件下均保持可行和稳定，而ACBBA、PI和DGA在通信降级时失去稳定性或可行性。在理想投递下，主要十目标比较中全协议计算的中位数从DMCHBA的4.88毫秒到DGA的1.346秒不等。静态路径质量使DGA和DMCHBA保持为领先的MinMax方法，而DGA在四个目标负载中的三个中领先MinSum，HIPC在50个目标时领先。随着任务负载增加，静态和执行集成计算的排名出现分歧。结果确定了不同分配器在路径目标、通信行为、可靠性和计算约束方面的操作区域。

英文摘要

Selecting a decentralized Multi-Robot Task Allocation (MRTA) method for embedded deployment on autonomous platforms requires considering more than route performance alone. We benchmark six decentralized MRTA allocators (CBAA, ACBBA, PI, HIPC, DMCHBA, and DGA) in the Collaborative Visit (CV) scenario to characterize tradeoffs among MinMax and MinSum travel, communication robustness and demand, allocation reliability, computational burden, and scale sensitivity. The core study uses 500 paired ten-target instances across 25 ideal and degraded communication conditions spanning Bernoulli loss, Gilbert--Elliott loss, and Rayleigh fading, with additional campaigns examining pre-allocation, execution-integrated computation, and sensitivity to grid size, robot density, and target load. Across the 24 impaired core conditions, DGA and DMCHBA achieved the lowest mean MinMax travel at 24.49 and 24.78 steps, respectively. HIPC narrowly led mean MinSum travel at 66.95 steps, followed by DGA at 67.22, with both methods occupying the top two in every impaired condition. DMCHBA had the lowest publication intensity at 2.08 publications per team step. In ten-target pre-allocation, HIPC and DMCHBA remained viable and stable in every tested condition, while ACBBA, PI, and DGA lost stability or viability as communication degraded. Under ideal delivery, median full-protocol computation $\Cterm$ in the primary ten-target comparison ranged from 4.88 ms for DMCHBA to 1.346 s for DGA. Static route quality preserved DGA and DMCHBA as the leading MinMax methods, while DGA led MinSum at three of four target loads and HIPC led at 50 targets. Static and execution-integrated computation rankings diverged as task load increased. The results identify distinct allocator operating regions across route objective, communication behavior, reliability, and computational constraints.

发表机构

• University of San Diego（圣地亚哥大学）

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