Edge-assisted Collaborative Digital Twin for Safety-Critical Robotics in Industrial IoT

TL;DR

This paper presents an edge-assisted collaborative digital twin for safety-critical robotics in industrial IoT, enabling real-time obstacle avoidance and adaptive operation of a robotic arm in dynamic environments.

Contribution

It introduces a novel edge-assisted digital twin framework for safety-critical robotics, demonstrating real-time obstacle avoidance in industrial IoT settings.

Findings

Successful implementation on a Franka-Emika-Panda robotic arm

Real-time obstacle avoidance in dynamic environments

Enhanced safety and adaptability in industrial robotics

Abstract

Digital Twin technology is playing a pivotal role in the modern industrial evolution. Especially, with the technological progress in the Internet-of-Things (IoT) and the increasing trend in autonomy, multi-sensor equipped robotics can create practical digital twin, which is particularly useful in the industrial applications for operations, maintenance and safety. Herein, we demonstrate a real-world digital twin of a safety-critical robotics applications with a Franka-Emika-Panda robotic arm. We develop and showcase an edge-assisted collaborative digital twin for dynamic obstacle avoidance which can be useful in real-time adaptation of the robots while operating in the uncertain and dynamic environments in industrial IoT.