Zero-Footprint RPA Bot Execution Across Operating Systems
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Solution Overview
Problem
Conventional Robotic Process Automation (RPA) systems face administrative complexity and limited scalability due to the requirement for preinstalled software robots on specific devices and operating system dependencies, which restricts the deployment and processing capabilities.
Innovation Solution
A platform-agnostic RPA system that decouples bot creation and execution from specific devices and operating systems, using a control room to manage task processing instructions and node managers on client devices, allowing bots to operate across different platforms and devices without preinstalled software, and enabling execution within virtual machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software robots are preinstalled on specific devices with operating system dependencies, then bot execution capability is provided, but administrative complexity increases and scalability is limited
Solution Approach 1:
A control room server acts as an intermediary between users and bot execution. The control room provides a centralized platform for bot creation, storage, and deployment, eliminating the need for users to directly install and manage bot software on their devices. Bot code is delivered on-demand from the control room to node managers, simplifying administrative overhead while maintaining platform compatibility across different operating systems and devices.
Solution Approach 2:
The system implements a universal bot execution architecture where a single control room server can manage and deploy bots across multiple different operating systems and devices. The node manager component provides universal functionality by adapting bot execution to various platforms without requiring separate installation processes for each device type, thereby reducing administrative complexity while enhancing adaptability.
2Adaptability or versatility
If software robots are preinstalled on specific devices, then bot creation and execution capability is provided, but deployment cost increases
Solution Approach 1:
The control room server serves as a centralized intermediary that manages the entire bot deployment lifecycle. Instead of requiring manual preinstallation on each device, the control room automatically delivers bot code to node managers on-demand. This centralized approach reduces deployment complexity and costs by eliminating repetitive manual installation processes across multiple devices while maintaining the ability to deploy to various platforms.
Solution Approach 2:
Bot code is prepared and stored in the control room in advance, ready for immediate deployment. When a user requests bot execution, the pre-prepared code is automatically delivered to the appropriate node manager without requiring on-site installation or configuration. This preliminary preparation of bot code reduces deployment complexity and accelerates the deployment process across different devices and platforms.
3Productivity
If bots are executed at application level like human users, then task automation capability is provided, but operating system dependency increases
Solution Approach 1:
The control room and node manager act as intermediaries that decouple bot execution from specific operating systems. The control room manages bot code delivery, and the node manager handles platform-specific adaptations, allowing the same bot to execute across different operating systems. This intermediary architecture maintains full automation capability while eliminating operating system dependencies.
Solution Approach 2:
The system segments bot execution into separate functional components: the control room handles bot management and code delivery, while node managers handle platform-specific execution details. This segmentation allows the core automation logic to remain operating system-agnostic, with platform-specific adaptations isolated to the node manager layer, thereby maintaining productivity across diverse operating systems.
Data Source
AI summary
Computerized RPA methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.