Is Robotics Rule the Future – Artificial Intelligence Future

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Is Robotics Rule the Future

Abstract:

(Is Robotics Rule the Future) This paper introduces Cloud Robotics, which is a new field of research. With recent developments in robotic environments and in integrated multi-robot systems, robots are attaining richer functionalities and robotic systems are becoming much easier to develop. It tackles issues supporting daily activity throughout various locations in a continuous and seamless manner by extracting robotic devices and providing a means for utilizing them as a cloud of robots. But such robotic services are not enough for flawlessly supporting daily routine.As a case study, a field experiment in a shopping mall shows how our proposed prototype infrastructure of cloud networked robotics enables multi-location robotic services for life support. We examine the requirements in typical daily supporting services through example situations that target senior citizens and the disabled. Based on these requirements, let us discuss the key research issues in network robotics.”

 

Introduction

“Robotic systems have brought noteworthy economic and social impacts to human lives over the past few decades. For example, industrial robots have been widely deployed in factories to do repetitive, tedious, or dangerous tasks, such as painting, packaging, assembly, and welding. These pre-programmed robots have been very successful in industrial applications due to their high endurance, speed, and precision in structured factory environments. To enlarge the functional range of these robots or to deploy them in unstructured environments, robotic technologies are integrated with network technologies to foster the emergence of networked robotics. Networked robotics applications can be classified as either teleported robots or multi-robot systems. Application examples include remote control of a planetary rover and remote medical surgery. In a multi-robot system, a team of networked robots complete a task cooperatively in a distributed fashion by exchanging sensing data and information via the communication network. However, networked robotics, similar to standalone robots, faces inherent physical constraints as all computations are accomplished in the robotic network, and information access is restricted to the collective storage of the network. With the rapid advancement of recent innovations in cloud computing technologies, some of these constraints can be overcome through the concept of cloud robotics, leading to more efficient, intelligent and yet cheaper robotic networks. In this paper, we describe a cloud robotics architecture, some of the technical challenges, and its potential applications. Some preliminary results on optimal operation of cloud robotics are also presented.

 

Related Works

“The development process of robotic components has improved in the past few years because of the standardization of robotic components. Since such middle ware is commonly used, robotic functional modules are now becoming so that robot developers do not have to implement all the features of their robots; instead they can find and reuse modules suitable for their purposes. Improvements in network technologies, especially wireless networking, have also changed robot development. At the same time, robotic applications can now perform collaborative operations among multiple robots connected by networks. For example, the mobile-robotic ful fillment system proposed by Kiva Systems successfully improved the efficiency of logistics by deploying many transportation robots in a warehouse and organizing them based on their location information aggregated by a network. This approach suggests a requirement for common frameworks to aggregate and manage information about robots, such as location information for organizing multi-robot systems. Networked robot systems extended the concept of multi-robots toward association among different types of robots. Since its concept was proposed in 2002.”In the concept of networked robots, the various involved devices can be organized as three types of robots: visible and unconscious. Visible types are physically embodied agents with a physical actuation facility; virtual types appear on the screens of mobile information devices as agents for communicating with users; unconscious types are mainly deployed in environments for sensing and form ambient intelligence. Although these improvements have accelerated the implementation of interactive service robots, difficulties remain for developing robotic services that support a wide range of human activities. The dustbot project is an example of such a networked robot system. They are of two types; door-to-door garbage collection, and street cleaning. Information observed by the robot’s on-board sensors is also shared among other robots so that they can cooperate with each other to achieve their tasks. The technologies of web services and service-oriented architecture (SOA), which form the technical foundation of cloud computing, have also been applied to robotic technologies in three ways. One is the utilization of computational resources for enhancing the abilities of robots on cloud servers, as Kuffner“introduced with a cloud-enabled robot. The idea uses cloud computing for various calculations required in robot actions, such as behaviour planning and perception”. Such “remote-brain” robots can enhance the ability of single robots and simultaneously reduce cost and energy. Knowledge sharing and the exchange of semantic information are other issues where different types of robots collaborate. To realize cloud networked robotics, common protocols for robotic services must also be standardized for integration.

 

Computation Challenges

One of the key benefits of cloud robotics is the capability of ridding intensive tasks to the cloud for execution. However, the decision to offload a specific task requires a unified framework that can handle a list of complex issues. First, the offloading strategy should consider various factors, including the amount of data exchanged, and the delay deadline to complete the task. Second, the decision should also consider whether it is more advantageous to execute the task within the group of networked robots, given the presence of cloud resources. Specifically, our objective is to minimize the amount of energy consumed by the robot, under the constraint that the task should be completed within a specified deadline. The fundamental trade-off lies between the energy consumed for executing the task by the on-board CPU within the data to the cloud for remote execution. In our initial investigation, we have considered the two alternative choices of standalone execution by the robot and cloud execution.

 

Security Challenges

Trust and security issues are major considerations in cloud robotics. Specifically, our solution faces two major security challenges due to its cloud implementation. We need the VM environment to be trust-worthy. A malicious VM can subtly sabotage an important task without the robot being aware of the damage. In military applications, the robotic unit has to identify a trust-worthy VM infrastructure to connect and to avoid malicious .Trust measurement: some root-of-trust components that do not belong to the cloud platform provider especially when the computation and network traffic incur monetary costs. The computing environments in the cloud should be verifiable by a user or a trusted party, e.g., to ensure there is no hidden or malicious code running besides the delegated tasks. Moreover, confidential data may be stored in the public cloud storage, while logically private to clone devices. Therefore, strong integrity and confidentiality protection are needed to secure application data.

Applications

Future robotic applications will largely benefit from cloud robotics, which provides the following advantages over traditional networked robots. • Ability to offload computation-intensive tasks to the cloud. The robots only have to keep necessary sensors, actuators, and basic processing power to enable realtime actions (e.g., real-time control). The battery life is extended, and the robotic platform becomes lighter and less expensive with easier to maintain hardware. The maintenance of software on board the robots also becomes simpler, with less need for regular updates.  the operational life and usefulness of the robotic network can be easily extended. The robots can acquire information and knowledge to execute tasks through databases in the cloud. They do not have to deal with the creation and maintenance of such data. Access to shared knowledge and new skills.  cloud can host a database or library of skills or behaviors that map to different task requirements and environmental complexities. The Robo Earth project  is trying to turn this into a reality.

 

Conclusion

We have proposed a cloud robotics architecture to address the constraints faced by current networked robots. Cloud robotics allows robots to share computation resource, information and data with each other, and to access new knowledge. Submitted to IEEE Network On Magazine 7d skills not learned by themselves. This opens a new paradigm in robotics that we believe leads to exciting future developments. It allows the deployment of inexpensive robots with low computation power and memory requirements by leveraging on the communications network and the elastic computing resources offered by the cloud infrastructure.

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