Cloud Robotics: Architecture, Challenges and Applications

MOTIVATION

In this paper, the author introduces an integration framework between robotic technologies and network technologies. The cloud robotics infrastructure consists of Machine to Machine (M2M) and Machine to Cloud (M2C) communication tiers. These networked robots face many physical challenges. The paper describes a method to overcome the challenges using cloud robotic architecture.

KEY POINTS

• The major constraints of the network robot systems are resource constraints, difficulty in updating resource configurations, constraints in storing and sharing of information, communication troubles like requirement of complex computations and large memory.

• These constraints are overcome using with the help of centralized cloud infrastructure with elastic resources.

        ARCHITECTURE

• The architecture comprises of M2M and M2C tiers. On M2M level, robotic groups are formed which communicate using wireless links and form a collaborative unit. This unit is formed to utilize combined computing capabilities and to enable easy sharing/communication of information between robots that helps in collaborative decision making.

• On M2C level, the elastic centralized cloud provides resources for computational offloading. The main advantage is the extensive memory provided by the cloud for unification of information and the library of behavioral skills that guides learning among robots.

• M2M wireless communication network is formed dynamically, in an ad-hoc manner. Gossip algorithm is used for the purpose of message transmission because they do not require route discovery and maintenance.

• Cloud robotics is built on virtual ad-hoc cloud and a centralized cloud. Peer-based, Proxy-based and Clone-based computing models are the three main models created for specific applications. The Clone-based model has maximum robustness and Proxy-based model has maximum interoperability. Network conditions, application requirements and resource availability are the parameters required to choose the required model.

         CHALLENGES AND SOLUTIONS

• Computation challenges mainly focus on the decision to offload and how offloading takes place with efficient use of resources to minimize the robot’s energy consumption. Dynamic Voltage Scaling (DVS) model is considered for standalone execution, and polynomial energy consumption model is considered for cloud execution.

• Delay sensitivity and failure rates are the two main factors of communication challenges. The communication network delay is calculated using the conductance. The authors have shown that worst case delay is O(N log N) for N nodes in a network.

• Optimal execution strategy is aimed to optimize communication and execution costs. It can be a combination of three kinds of execution strategy namely standalone execution (by robot), execution by group of robots, cloud execution.

• Security challenges are overcome by first verifying the VM-environment (Trust Establishment). Then, VM is monitored and trust measurements are reported to a third party. The VMs infrastructure is verified by user with the help of its service provider’s identity(Reputation-based Trust).

ADVANTAGES

• Extension of battery life as computation intensive code are offloaded. As the cloud hardware is independent of robotic network, it can be upgraded separately, thus extending operational life of robotic network.

• As vast amount of data is available in the cloud, the robots can access them. They can also share information and learn new skills from the existing data.

• Robotic navigation, grasping, Simultaneous Localization And Mapping (SLAM) are few of the applications.

COMMENTS

• The integration of network and cloud robotics provides a very positive impact in offloading techniques.

• The use of gossip protocols may not provide reliable communication. Also, the conductance may become low due to high message latency if there is a fault in the network.

• Though security is ensured using trust measurement, if the robot is hacked, all the information can be accessed by anyone.

• Constant internet connection is very much essential for efficient performance.