Robot Motion Teaching via Human Path Mapping Across Workpieces
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Solution Overview
Problem
Current robot movement teaching systems are inefficient and require skilled operators, especially when teaching complex movements to robots working on different types of workpieces, as they often rely on precise CAD data and teach pendants, which can be time-consuming and require identical shapes between the human-worked and robot-worked objects.
Innovation Solution
A robot movement teaching apparatus that includes a movement path extraction unit to process images of human fingers or arms working on a first workpiece, a mapping generation unit to create a transform function based on feature points of both workpieces, and a movement path generation unit to generate a robot movement path, allowing intuitive teaching of robot movements even when workpieces differ in shape, with optional locus optimization for efficient and collision-free paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional teach pendant methods are used to teach robot movements, then movement teaching can be performed with simple equipment, but the teaching process becomes time-consuming and requires skilled operators
Solution Approach 1:
The patent replaces the mechanical teach pendant operation with an automated image processing system. Cameras capture human movement, and computer algorithms automatically extract movement paths and generate robot teaching data, eliminating the need for operators to manually program robot movements point-by-point
Solution Approach 2:
The system captures and copies human movement patterns through image processing. By recording human operators performing tasks and automatically converting these movements into robot teaching data, the system replicates expert movements without requiring the robot operator to have specialized programming skills
2Manufacturing precision
If precise CAD data is used for movement teaching, then accurate robot paths can be generated, but the process becomes complex and time-consuming
Solution Approach 1:
The patent replaces CAD-based path planning with direct image processing. Instead of importing and processing precise CAD models to generate movement paths, the system directly captures actual human movements through cameras and extracts paths from these images, achieving both accuracy and efficiency
Solution Approach 2:
The system performs preliminary capture of human movement patterns before robot teaching. By recording human operators performing the actual tasks in advance, the movement data is already available in the correct format, eliminating the need for time-consuming CAD modeling and path planning during the robot teaching phase
3Adaptability or versatility
If the system requires identical shapes between human-worked and robot-worked objects, then movement transformation becomes simpler, but the system loses versatility for different workpiece types
Solution Approach 1:
The patent uses feature point detection and coordinate transformation to adapt to different workpiece shapes. By identifying key feature points on various workpieces and applying appropriate transformation matrices, the system can handle diverse workpiece geometries without requiring identical shapes between human and robot tasks
Solution Approach 2:
The image processing system is designed to be universally applicable to different workpiece types. The feature point detection and coordinate transformation algorithms work with various geometries, allowing the same system to handle multiple workpiece configurations without requiring shape-matching constraints
Data Source
AI summary
A robot movement teaching apparatus including a movement path extraction unit configured to process time-varying images of a first workpiece and fingers or arms of a human working on the first workpiece, and thereby extract a movement path of the fingers or arms of the human; a mapping generation unit configured to generate a transform function for transformation from the first workpiece to a second workpiece worked on by a robot, based on feature points of the first workpiece and feature points of the second workpiece; and a movement path generation unit configured to generate a movement path of the robot based on the movement path of the fingers or arms of the human extracted by the movement path extraction unit and based on the transform function generated by the mapping generation unit.