Cloud Service Managing Robotic Device Pool
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Solution Overview
Problem
Current cloud computing systems lack an efficient method for managing and controlling robotic devices, particularly in scenarios where tasks require specific configurations and labor, leading to inefficiencies in task execution and resource allocation.
Innovation Solution
A cloud-based service that allows users to rent robotic devices from a pool, providing configuration requirements and program instructions, and facilitating payment for tasks performed by these devices, enabling flexible task execution and revenue generation for device owners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a traditional cloud computing model is used where users own and maintain robotic devices, then device control and task execution are possible, but hardware and software installation and maintenance tasks increase user burden and cost
Solution Approach 1:
The cloud service automatically manages robotic device provisioning, configuration, and maintenance. The system self-services by handling software updates, device provisioning, and task management without requiring user intervention in hardware and software installation and maintenance tasks.
Solution Approach 2:
The cloud service provides a universal platform that manages multiple robotic devices with different configurations and capabilities. It offers unified task management, device provisioning, and maintenance functions that work across diverse robotic devices, eliminating the need for users to handle device-specific complexity.
2Productivity
If robotic devices are dedicated to specific users, then task execution is reliable, but resource allocation efficiency decreases and cost increases
Solution Approach 1:
The system dynamically allocates robotic devices to tasks based on real-time availability, task requirements, and device capabilities. Devices can be reassigned between tasks and users dynamically, optimizing resource utilization while maintaining reliable task execution through automated provisioning and configuration management.
Solution Approach 2:
The cloud service implements feedback mechanisms to track device status, task completion, and performance metrics. This feedback enables automated device selection, task assignment, and resource allocation decisions that maintain task execution reliability while maximizing resource allocation efficiency.
3Productivity
If robotic devices are shared among multiple users, then resource allocation efficiency improves, but device configuration and task management complexity increases
Solution Approach 1:
The cloud service acts as an intermediary between multiple users and shared robotic devices. It manages device configuration, task assignment, and coordination automatically, shielding users from the complexity of shared resource management while enabling efficient resource allocation through centralized control.
Solution Approach 2:
The system creates virtual copies or profiles of device configurations for different users and tasks. Each user receives a customized configuration profile that simplifies interaction with shared devices, while the cloud service manages the actual physical device state and coordination behind the scenes.
4Ease of operation
If users purchase and maintain their own robotic devices, then task execution is reliable, but cost and hardware maintenance burden increase
Solution Approach 1:
The cloud service provides self-service capabilities for device maintenance, including automated software updates, diagnostics, and repair coordination. This maintains task execution reliability through professional management while eliminating user burden for hardware maintenance tasks.
Solution Approach 2:
The cloud service offers a universal maintenance and management platform that handles diverse robotic device types through standardized procedures. This maintains reliability across different devices while simplifying user interaction through unified maintenance management.
Data Source
AI summary
Methods and systems enabling a cloud service to manage robotic devices are provided. An example method includes receiving a task order including information that identifies configuration requirements for a robotic device to perform a task, program instructions executable by the robotic device to perform the task, and payment information for the task. The method may also include selecting one or more robotic devices to perform the task from among a pool of robotic devices. For instance, the selected one or more robotic devices may be leased for a period of time to perform the task. The method may further include providing the configuration requirements and the program instructions to the selected one or more robotic devices, and receiving confirmation that the task has been performed. According to the method, payment may be provided to one or more accounts registered with the selected one or more robotic devices.