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1、1 GTI 5G and Cloud Robotics White Paper http:/www.gtigroup.org 3 Confidentiality: This document may contain information that is confidential and access to this document is restricted to the persons listed in the Confidential Level. This document may not be used, disclosed or reproduced, in whole or
2、in part, without the prior written authorization of GTI, and those so authorized may only use this document for the purpose consistent with the authorization. GTI disclaims any liability for the accuracy or completeness or timeliness of the information contained in this document. The information con
3、tained in this document may be subject to change without prior notice. Document History Date Meeting # Version # Revision Contents DD-MM-YYYY NA DD-MM-YYYY DD-MM-YYYY DD-MM-YYYY DD-MM-YYYY 4 5 Cloud Robotics: Trends, Technologies, Communications Abstract Cloud robots are controlled from a “brain” in
4、 the cloud. The brain, located in a data center, makes use of Artificial Intelligence and other advanced software technologies to deal with tasks that in traditional robots were undertaken by a local, on-board controller. Compared to local robots, cloud robots will generate new value chains, new tec
5、hnologies, new architectures, new experiences and new business models, this white paper will explore these aspects. 1. Introduction Cloud robotics is a relatively recent concept. Early work dates back to 2010, when the European Commissions RoboEarthi project began. This aimed to establish a “World W
6、ide Web for robots”. RoboEarth and later projects such as Rapyutaii and Robohowiii formalized the basic concept and technologies, and are still influencing cloud robotic research today. There are three core advantages of cloud robots compared to stand-alone robots: Information sharing Many cloud rob
7、ots can be controlled from one brain, and the brain can accumulate visual, verbal, and environmental data from all connected robots. Intelligence derived from this data can be used by all the robots controlled by the brain. As with other cloud services, information collected and processed on each ro
8、bot will always be up-to-date and backed-up safely. Developers also benefit, as they can build reusable solutions for all cloud-connected robots. Offloaded computation Some robot tasks require more computational power than a local controller can economically deliver. Offloading to the cloud data-int
9、ensive tasks such as voice and image recognition, voice generation, environmental mapping and motion planning will lower the hardware requirements and power consumption of robots, making them lighter, smaller, and cheaper. Collaboration Cloud robots do not need to work alone. Using the cloud as a co
10、mmon medium, two robots can work together to carry an object too heavy for one, or a group of simple worker robots can work with a local map, provided by a leader robot with costly sensors. 6 Distributed version of AlphaGo exploited 40 search threads, 1202 CPUs and 176 GPUs x, no ordinary robot can
11、install inside. But cloud robot can make use of it. 2. Applications for cloud robots Using cloud resources empowers robots and gives them new capabilities in many areas: Intelligent visual processing: image classification, target detection, image segmentation, image description, character recognitio
12、n. Natural language processing: semantic understanding based on depth learning, accurate identification of user intent, multi-intention analysis, emotional analysis. Makes use of a powerful background knowledge base. Facial recognition: face detection algorithm based on depth learning; In the real-t
13、ime video stream to accurately detect the face; Any face mask and real-time detection under the viewing angle; To overcome: the side face, half obscured, blurred face; Extension from current robot applications: outdoor map navigation, indoor positioning and navigation, typical product identification
14、, universal item identification, environmental understanding, text reading, voice prompts. Figure 1: Large scale data collection with an array of robots (14 robots are sharing experiences of machine learning for grasping ) Source: https:/ 7 The applications that will emerge for cloud robots are of m
15、any kinds; some are emerging now others are at an early stage of development. Logistics Amazon, Jingdong, S.F. Express and other companies have deployed logistics robot systems. The wheeled AGV (Automated Guided Vehicle) is the main type of logistics robot (though logistics companies are also triall
16、ing the use of aerial drones). By connecting to the cloud, AGVs can achieve unified scheduling (where all AGVs are working as a single system for maximum efficiency). In addition, AGVs can be equipped with machine vision systems, and video can be transmitted to cloud-based systems to handle a variety of situations on the road. Eventually this will resu
