Autonomous Welding Robot Path Planning From 3D Seam Mapping
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Solution Overview
Problem
Conventional welding techniques are labor-intensive, inefficient, and inflexible, often resulting in misplaced welds and inefficiencies due to the need for skilled programmers to generate instructions for welding robots, which are not adequately precise for low- or medium-volume production settings and require manual path planning to avoid collisions.
Innovation Solution
A computer-implemented method that uses movable sensors to map the manufacturing workspace in 3D, allowing the welding robot to automatically and dynamically identify and weld seams with high accuracy, perform path planning, and adjust parameters without prior information, using a combination of sensor data and CAD models for precise positioning and collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional welding techniques with manual programming are used, then skilled operators can control the welding process, but the production efficiency is low and the precision is insufficient
Solution Approach 1:
The welding robot system performs self-positioning and self-adjustment by scanning the actual part geometry and automatically generating welding paths. The system identifies seams and features autonomously without requiring external programming or manual intervention, enabling it to adapt to variations in part positioning and geometry while maintaining high precision and productivity
Solution Approach 2:
The patent replaces manual mechanical programming with automated optical sensing and computer vision systems. Sensors scan the part to create a digital representation, and software algorithms automatically generate welding instructions, substituting the mechanical programming process with intelligent automated systems that improve both precision and efficiency
2Adaptability or versatility
If fixed welding instructions are used for high-volume production, then consistent welding quality is achieved, but the system lacks flexibility for low- or medium-volume production with variations
Solution Approach 1:
The welding system transitions from static, pre-programmed instructions to dynamic, real-time path generation. The robot scans the actual part geometry during operation and automatically adjusts welding paths based on detected features and variations, enabling flexibility across different production volumes while maintaining consistency through automated feedback control
Solution Approach 2:
The system incorporates sensor feedback loops where the welding robot scans the part before and during welding operations. This feedback information is used to automatically adjust welding parameters and paths, ensuring consistent quality while adapting to variations in part positioning, geometry, or material properties
3Ease of operation
If manual path planning is implemented to avoid collisions, then the welding robot can navigate complex workspaces, but the programming complexity increases significantly
Solution Approach 1:
The welding robot performs self-path-planning by scanning the workspace environment and automatically generating collision-free trajectories. The system identifies obstacles, part features, and optimal welding paths autonomously without requiring external programming, significantly reducing programming complexity while maintaining operational capability in complex workspaces
Solution Approach 2:
The patent replaces complex manual path planning with automated sensor-based environmental mapping and intelligent path generation algorithms. The system uses sensors to create a digital model of the workspace and automatically computes welding paths that avoid collisions, substituting manual programming complexity with automated intelligent systems
Data Source
AI summary
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.