Embedded Evaluation of Task Admission Coalescing in Decentralized Multi-Robot Systems

Key points

• We evaluate task-admission coalescing as a mechanism for controlling allocator processor work while accounting for target-service latency, using CBAA, ACBBA, PI, and HIPC as a representative MRTA suite.1
• The study comprises a 3,000-mission AGX Orin campaign with measured computation delay, 3,000 paired zero-compute missions, and a 96-mission Pololu 3pi+ RP2040 allocator hardware-in-the-loop campaign.1
• Across four matched medium-arrival HIPC scenarios, Count b=4 reduces mean RP2040 work by 59.85% and service latency by 39.47%, while the corresponding AGX cases increase latency by 27.69%.1
• These results show that the usefulness of task-admission coalescing depends on arrival intensity, allocator-specific behavior, and the relative cost of computation on the execution platform.1

Sources (1)

• [1]Embedded Evaluation of Task Admission Coalescing in Decentralized Multi-Robot Systems
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 10:37 PM

  Multi-robot task allocators in dynamic missions commonly admit newly released tasks immediately, potentially invoking allocation for each new arrival.

  We evaluate task-admission coalescing as a mechanism for controlling allocator processor work while accounting for target-service latency, using CBAA, ACBBA, PI, and HIPC as a representative MRTA suite.

Extractive summary: sentences quoted from the sources.