仮想化を用いたリソース制約ロボットのための文脈認識型タスク処理
Context-Aware Task Handling in Resource-Constrained Robots with Virtualization
限られた計算資源の移動ロボットで複数タスクをリアルタイムに処理するため、動的タイムシェアリング・イベント駆動スケジューリング・軽量仮想化を組み合わせた手法を提案し、Raspberry Pi上でSLAM等を42%高速化した。
著者: Ramyad Hadidi, Nima Shoghi Ghalehshahi, Bahar Asgari, Hyesoon Kim
分類: cs.RO
原文アブストラクト
Intelligent mobile robots are critical in several scenarios. However, as their computational resources are limited, mobile robots struggle to handle several tasks concurrently and yet guaranteeing real-timeliness. To address this challenge and improve the real-timeliness of critical tasks under resource constraints, we propose a fast context-aware task handling technique. To effectively handling tasks in real-time, our proposed context-aware technique comprises of three main ingredients: (i) a dynamic time-sharing mechanism, coupled with (ii) an event-driven task scheduling using reactive programming paradigm to mindfully use the limited resources; and, (iii) a lightweight virtualized execution to easily integrate functionalities and their dependencies. We showcase our technique on a Raspberry-Pi-based robot with a variety of tasks such as Simultaneous localization and mapping (SLAM), sign detection, and speech recognition with a 42% speedup in total execution time compared to the common Linux scheduler.