クラウドベースのスケジューリング機構によるスケーラブルでリソース効率の良い集中型制御
Cloud-Based Scheduling Mechanism for Scalable and Resource-Efficient Centralized Controllers
Kubernetesベースのスケジューリング機構で集中型非線形モデル予測制御(CNMPC)の計算負荷をクラウドにオフロードし、ロボット数が変動する状況でもスケーラブルに動作することを実験で示した。
著者: Achilleas Santi Seisa, Sumeet Gajanan Satpute, George Nikolakopoulos
分類: cs.DC, cs.MA, cs.RO, cs.SY, eess.SY
原文アブストラクト
This paper proposes a novel approach to address the challenges of deploying complex robotic software in large-scale systems, i.e., Centralized Nonlinear Model Predictive Controllers (CNMPCs) for multi-agent systems. The proposed approach is based on a Kubernetes-based scheduling mechanism designed to monitor and optimize the operation of CNMPCs, while addressing the scalability limitation of centralized control schemes. By leveraging a cluster in a real-time cloud environment, the proposed mechanism effectively offloads the computational burden of CNMPCs. Through experiments, we have demonstrated the effectiveness and performance of our system, especially in scenarios where the number of robots is subject to change. Our work contributes to the advancement of cloud-based control strategies and lays the foundation for enhanced performance in cloud-controlled robotic systems.
