Robot Conveyor Line Parameter Tuning via Simulation Models
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Solution Overview
Problem
In the logistics industry, configuring parameters for robot manipulators to efficiently pick and place objects on conveyors is time-consuming and requires experienced engineers, leading to a low success rate and inefficiency in optimizing working lines.
Innovation Solution
A method and apparatus that utilize an evaluation model to automatically update configuring parameters based on measuring parameters, such as physical attributes of the working line, to improve the success rate of moving items from one conveyor to another, allowing for optimization without on-site processes or expert involvement, using simulation software to achieve higher efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If engineers manually configure parameters based on experience and perform on-site tuning, then the success rate of pick and place operations can be improved, but the process becomes time-consuming and requires experienced engineers
Solution Approach 1:
The system performs self-optimization by automatically configuring parameters using the evaluation model and simulation environment, eliminating the need for manual engineering intervention. The closed-loop system continuously monitors success rates and adjusts parameters autonomously, making the system serve itself rather than requiring external expert assistance
Solution Approach 2:
The system pre-configures parameters using simulation environments before actual deployment. By performing preliminary optimization in a virtual setting, the system prepares optimal parameter sets in advance, avoiding time-consuming on-site tuning while maintaining high success rates from the start
2Reliability
If comprehensive graphical interfaces and powerful applications are used to control multiple robots, then the functionality and success rate improve, but the device complexity and configuration difficulty increase
Solution Approach 1:
The system creates a virtual copy of the physical working line through simulation environment. This digital twin allows for parameter optimization and testing without interfering with the actual system, simplifying the configuration process by separating the complexity of control from the user interface
Solution Approach 2:
The system replaces manual mechanical configuration processes with automated computational methods. Instead of engineers manually adjusting physical parameters, an evaluation model with automated algorithms configures parameters, substituting complex mechanical interaction with streamlined information processing
Data Source
AI summary
A method and an apparatus for optimizing a target working line are disclosed. The target working line includes at least one robot manipulator, at least one conveyor and at least one item on the conveyor to be displaced by the robot manipulator. The method includes: obtaining an evaluation model for the target working line, the evaluation model yielding an overall success rate of moving the item from one conveyor to another conveyor based on at least one measuring parameter, the measuring parameter being a physical attribute of the target working line; yielding the overall success rate for the target working line as a function of a value for the measuring parameter for the target working line; and in case that the yielded overall success rate is lower than a predetermined threshold rate, updating a value for a configuring parameter based on the overall success rate, the configuring parameter corresponding to the measuring parameter, and the configuring parameter being states of the working line. The optimization of the evaluation model does not require an implementation of an on-site process or an involvement of an experienced engineer or worker. Instead, simulation software can be used to obtain customized parameters used for the target working line, resulting in an increased success rate within a short period of time.