Robot Manipulator Placement Using Camera-Based Task Optimization
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Solution Overview
Problem
Determining the optimal installation site for a robot manipulator at a workstation to efficiently perform a specified task is challenging due to the need for precise spatial information and optimization of various parameters such as execution speed, wear, and energy consumption, which existing methods fail to address effectively.
Innovation Solution
A method using a camera unit to record images containing spatial information, which are then processed by a computing unit to apply non-linear optimization or neural networks to determine the optimal installation site based on predefined cost functions, considering parameters like execution speed, wear, and energy consumption, allowing for automatic and efficient placement of the robot manipulator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to determine the installation site of a robot manipulator, then the process is simple to implement, but the determination is time-consuming and lacks optimization for task performance
Solution Approach 1:
The patent replaces manual mechanical determination methods with an automated computing system that uses camera-based spatial information capture and non-linear optimization algorithms to automatically determine the optimal installation site, significantly improving determination speed while accepting increased system complexity
Solution Approach 2:
The system enables self-service by allowing the robot manipulator to automatically determine its own optimal installation site through the computing unit processing spatial data from camera units, eliminating the need for manual intervention in the optimization process
2Productivity
If multiple parameters (execution speed, wear, energy consumption) are optimized simultaneously, then task performance is improved, but the computational complexity increases
Solution Approach 1:
The patent transforms the multi-parameter optimization problem into a solvable form by changing the approach to using non-linear optimization of a cost function that incorporates multiple parameters (execution speed, wear, energy consumption) simultaneously, allowing comprehensive task performance optimization while managing computational complexity through structured mathematical formulation
Solution Approach 2:
The system performs preliminary action by pre-defining the cost function with all relevant parameters before the optimization process begins, and by using spatial information from camera units to pre-establish the geometric model, thereby simplifying the actual optimization computation
3Measurement precision
If precise spatial information is captured using specialized equipment, then measurement accuracy is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent applies universality by using standard camera units (including those in mobile devices) that serve multiple functions - capturing spatial information without requiring specialized measurement equipment, thereby maintaining measurement precision while significantly improving ease of operation through familiar, readily available technology
Solution Approach 2:
The system replaces complex specialized measurement equipment with camera-based optical measurement, substituting mechanical/meter-based spatial capture with photographic imaging that is both precise and easy to operate using standard digital cameras or mobile device cameras
Data Source
AI summary
A method of determining an installation site of a robot manipulator at a workstation, the method including: recording a respective image of the robot manipulator and of the workstation of the robot manipulator, and of a workpiece to be machined at the workstation via a camera unit, wherein the respective image contains spatial information; transmitting the respective image to a computing unit; and determining the installation site of the robot manipulator by applying a non-linear optimization of a predefined cost function and/or of a neural network via the computing unit based on a predefined task for machining the workpiece and based on the spatial information determined by the computing unit from the respective image.