COTORRA: COntext-aware Testbed fOR Robotic Applications

TL;DR

COTORRA is a modular, context-aware robotic testbed leveraging Edge & Fog computing to validate robotic applications with low latency and quick federation, facilitating development before deployment.

Contribution

It introduces COTORRA, a novel, open, modular testbed integrating context and sensor data for robotic systems on heterogeneous networks.

Findings

Achieved autonomous navigation latency below 15ms.

Enabled inter-domain federation within 19 seconds.

Demonstrated feasibility of Edge & Fog in robotic testing environments.

Abstract

Edge & Fog computing have received considerable attention as promising candidates for the evolution of robotic systems. In this letter, we propose COTORRA, an Edge & Fog driven robotic testbed that combines context information with robot sensor data to validate innovative concepts for robotic systems prior to being applied in a production environment. In lab/university, we established COTORRA as an easy applicable and modular testbed on top of heterogeneous network infrastructure. COTORRA is open for pluggable robotic applications. To verify its feasibility and assess its performance, we ran set of experiments that show how autonomous navigation applications can achieve target latencies bellow 15ms or perform an inter-domain (DLT) federation within 19 seconds.