Cloud Robot System Offloading Computing to Reduce Complexity
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Solution Overview
Problem
Conventional robots are limited by their fixed computing ability and storage capacity, leading to inefficient resource utilization and complex communication management among multiple robots.
Innovation Solution
A cloud robot system that utilizes a cloud computing platform to process and manage data, status, and requests from robots, enabling scalable computing and storage resources, and facilitating efficient communication and collaboration among robots through a cloud brain module, social module, and communication modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional robots use chips as brains with fixed computing ability and storage capacity, then the robot structure is simple and independent, but the computing ability and storage capacity are limited and cannot be expanded
Solution Approach 1:
The patent extracts the computing brain (chip) from the robot body and places it in the cloud computing platform. The robot retains only basic control functions while offloading complex computing and storage tasks to the cloud, thereby expanding computing ability without increasing robot structure complexity
Solution Approach 2:
The patent introduces a cloud computing platform as an intermediary between multiple robots. This platform provides centralized computing resources and coordination services, enabling robots to access expanded computing ability and storage capacity while simplifying inter-robot communication through the intermediary
2Productivity
If robots occupy fixed computing ability and storage capacity regardless of task complexity, then resource allocation is simple, but resource utilization efficiency is low
Solution Approach 1:
The patent implements dynamic resource allocation where computing and storage resources are not fixed to individual robots but are dynamically assigned based on task requirements. The cloud platform adjusts resource distribution in real-time, allowing simple resource management architecture while achieving high utilization efficiency
Solution Approach 2:
The cloud computing platform serves multiple robots with a single shared resource pool, making the resource management system universal. The same platform manages computing, storage, and coordination for all robots, simplifying management while improving overall utilization through multi-functional use of resources
3Ease of operation
If M robots communicate peer to peer, then each robot can directly access other robots, but the number of communication paths becomes M*(M-1)/2 which is complex and difficult to manage
Solution Approach 1:
The patent introduces the cloud computing platform as a communication intermediary that centralizes all inter-robot communication. Instead of direct peer-to-peer paths, robots communicate through the cloud platform which routes messages and coordinates interactions, reducing communication paths from M*(M-1)/2 to M simple connections while improving ease of management
Data Source
AI summary
The present disclosure discloses a cloud robot system, including: a cloud computing platform and at least one robot; wherein the cloud computing platform is used for receiving perform information sent by the at least one robot in the system; the perform information includes data, status and requests of the at least one robot; the cloud computing platform is used for processing the data and status, sending process results back to the at least one robot, and sending control instructions to corresponding robot according to the requests; the at least one robot is used for sending the perform information to the cloud computing platform, receiving process results from the cloud computing platform, and performing according to the control instructions sent from the cloud computing platform. By using the present disclosure, computing ability and storage capacity of the robots can be expanded unlimited, while the thinking ability and memory of the robots are improved. Besides, the ability of the brains of the robots can be allocated according to demand, thus lowering the cost of the robots.