Cloud Data Library for Robotic Devices
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Solution Overview
Problem
Current cloud computing systems do not effectively enable robotic devices to access and share data elements associated with heuristics for interaction with environments, limiting their ability to perform tasks and adapt in real-time.
Innovation Solution
A method and system for robot cloud computing that allows robotic devices to request and receive data elements from a data library, determining the appropriate data elements to execute tasks and share information in real-time, facilitating interaction with environments through a cloud-based architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If robotic devices store all data elements locally, then access speed is fast, but device memory requirements and cost increase
Solution Approach 1:
The patent segments the data storage system into local cache memory on robotic devices and remote cloud-based data libraries. Frequently accessed data elements are cached locally for fast access, while the complete data repository is maintained remotely. This segmentation allows robotic devices to achieve fast access speeds for critical data without requiring large local storage capacity.
Solution Approach 2:
The patent introduces a cloud-based data library as an intermediary between robotic devices and the complete data repository. The data library acts as a mediator that stores comprehensive data elements and provides them to robotic devices on demand, eliminating the need for each device to maintain full local copies of all data while still enabling fast access through intelligent caching mechanisms.
2Adaptability or versatility
If robotic devices share data elements in real-time, then adaptability improves, but network bandwidth and communication overhead increase
Solution Approach 1:
The patent implements partial data sharing where robotic devices share only the specific data elements and heuristic information relevant to their current tasks and environment, rather than transmitting all available data. This partial action approach enables real-time adaptability through selective information exchange while minimizing network bandwidth consumption and communication overhead.
Solution Approach 2:
The patent enables each robotic device to maintain local quality of data by caching frequently accessed data elements and task-specific information locally. This allows devices to operate with high adaptability using local data while reducing the frequency and volume of network communications, thereby lowering energy consumption associated with data sharing.
3Adaptability or versatility
If data library stores comprehensive data elements, then task performance capability improves, but data library size and access complexity increase
Solution Approach 1:
The patent creates a universal data library architecture that serves multiple robotic devices and various task types through a single centralized system. The data library is designed to handle diverse data elements (sensor data, heuristic information, task parameters) in a unified manner, improving task performance capability across different robot types while avoiding the complexity of multiple separate data storage systems.
Solution Approach 2:
The patent uses selective copying mechanisms where only relevant data elements are copied from the comprehensive data library to individual robotic devices based on their specific task requirements. This approach allows the data library to maintain comprehensive data for high task performance capability while reducing access complexity by providing targeted copies rather than requiring devices to process entire data sets.
Data Source
AI summary
Methods and systems for robot cloud computing are described. Within examples, cloud-based computing generally refers to networked computer architectures in which application execution and storage may be divided, to some extent, between client and server devices. A robot may be any device that has a computing ability and interacts with its surroundings with an actuation capability (e.g., electromechanical capabilities). A client device may be configured as a robot including various sensors and devices in the forms of modules, and different modules may be added or removed from robot depending on requirements. A robot may interact with the cloud to perform any number of actions, such as to share information with other cloud computing devices. A robot's performance of a task can be augmented by a cloud service which contains a data library of elements which are delivered to the robot to help the robot execute actions.