Robot Kinematic Testing Framework Using Modular Agents
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Solution Overview
Problem
Current non-functional requirements testing mechanisms for robots lack a standards-based, configurable framework, which hinders accurate and efficient testing of kinematic parameters, especially for cognitive robots that need to interact with humans and perform tasks with high accuracy and throughput.
Innovation Solution
A method and system for non-functional requirement testing of robots that includes a kinematic non-functional requirements tester, which uses a controller program to determine and execute kinematic actions, receive characteristics from agents associated with robotic components, and generate test results based on predefined criteria and threshold values, enabling faster and more accurate testing by comparing current performance to past data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current non-functional requirements testing mechanisms are used, then testing can be performed, but the testing lacks a standards-based framework which hinders accurate and efficient testing of kinematic parameters
Solution Approach 1:
The testing framework is segmented into modular components including a tester system, controller program, agents, and standardized interfaces. Each component handles specific aspects of kinematic parameter testing independently, allowing for precise measurement while maintaining manageable system complexity through clear separation of concerns.
Solution Approach 2:
The framework implements configurable parameter settings that allow dynamic adjustment of test criteria, threshold values, and kinematic parameters. This enables accurate testing across different robot configurations and performance standards without requiring complete framework redesign, thus improving measurement precision while controlling complexity.
2Productivity
If comprehensive testing of cognitive robots is implemented, then high accuracy and throughput can be achieved, but the testing process becomes more time-consuming
Solution Approach 1:
The framework performs preliminary configuration of test scenarios, criteria, and parameters before actual testing begins. Test cases are pre-defined with expected outcomes and threshold values, allowing the testing system to execute comprehensive tests efficiently without time-consuming setup during execution, thus improving throughput while managing testing time.
Solution Approach 2:
The system incorporates feedback mechanisms where agents monitor robot performance in real-time and provide results to the controller program. This enables dynamic adjustment of test parameters and immediate identification of failures, reducing the time required for comprehensive testing by eliminating redundant checks and focusing resources on critical performance areas.
3Adaptability or versatility
If a standards-based interface is provided for testing, then extensibility and accuracy are improved, but the system complexity increases
Solution Approach 1:
The testing interface is designed with universal standards-based protocols that can accommodate multiple robot types, kinematic configurations, and test scenarios through a single unified framework. This multi-functional interface handles diverse testing requirements without requiring separate specialized interfaces for each case, thus improving extensibility while managing interface complexity through standardization.
4Measurement precision
If kinematic actions are executed and characteristics are collected from agents, then accurate test results are generated, but the processing requirements increase
Solution Approach 1:
The framework extracts and processes only the essential characteristics and parameters needed for accurate test results, filtering out unnecessary data from the agents. By selectively collecting and processing only critical kinematic parameters rather than all available sensor data, the system achieves accurate test results while reducing processing energy consumption and computational overhead.
Data Source
AI summary
In an approach to non-functional requirement testing of a robot, a computer determines one or more kinematic actions included in a received command. The computer determines at least one component of the robot included in an operation of the one or more kinematic actions. The computer determines at least one agent associated with the at least one component of the robot included in the one or more kinematic actions. The computer sends the one or more kinematic actions to the robot. In response to the robot performing the one or more kinematic actions, the computer receives, from the at least one agent, at least one characteristic of the performed one or more kinematic actions associated with the at least one component of the robot included in the one or more kinematic actions. The computer, based on the received at least one characteristic, generates one or more test results.