Autonomous Assembly Robots Using Sensor-Guided Fixtureless Welding
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Solution Overview
Problem
Conventional single-manipulator robotic solutions for assembly tasks are limited in the types of assemblies they can handle, require high setup and operational costs, and are inflexible, often needing human intervention for modifications, leading to increased downtime and operational costs.
Innovation Solution
A robotic system configured with multiple robots and sensors to autonomously locate, pose, and weld objects, using a controller to coordinate their movements and perform manufacturing tasks, such as welding, without the need for rigid fixtures or human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional single-manipulator robotic solutions are used for assembly tasks, then the system structure is simple, but the adaptability and versatility are limited
Solution Approach 1:
The system divides the assembly task among multiple independent robot manipulators, each responsible for specific components or operations. This segmentation allows each robot to be optimized for particular tasks while collectively handling diverse assembly requirements, thereby improving adaptability without requiring complete system redesign for different tasks.
Solution Approach 2:
The patent implements a multi-functional robotic system where multiple manipulators can perform various operations including welding, assembly, and material handling. The system's controller coordinates these manipulators to handle different assembly tasks, making the system universally applicable to multiple assembly types rather than being dedicated to a single task.
2Manufacturing precision
If rigid fixtures are used to account for positional uncertainties, then assembly precision is maintained, but set-up, installation, maintenance, and operation costs increase
Solution Approach 1:
The system replaces rigid mechanical fixtures with sensor-based detection and active compensation mechanisms. Sensors detect actual component positions and orientations, and the controller calculates correction values to compensate for deviations, eliminating the need for expensive rigid fixtures while maintaining assembly precision.
Solution Approach 2:
The patent implements a feedback mechanism where sensors continuously monitor component positions during assembly. The controller receives this position information, calculates deviations from target positions, and adjusts manipulator movements in real-time to achieve precise assembly without requiring rigid fixtures.
3Manufacturing precision
If teach pendent or on-pendant devices are used for control, then assembly parameter optimization is achieved, but human intervention is required increasing operational costs and downtime
Solution Approach 1:
The robotic system performs self-programming and self-optimization through sensor data collection and automated parameter adjustment. The controller automatically learns optimal assembly parameters from sensor feedback without requiring human operators to manually program or adjust settings, thereby eliminating downtime associated with human intervention while maintaining precision.
Solution Approach 2:
The patent introduces an intelligent controller as an intermediary between sensors and manipulators that automatically processes sensor data, optimizes assembly parameters, and generates control commands. This automated intermediary eliminates the need for human operators to directly intervene in parameter optimization, maintaining precision while improving operational efficiency.
4Productivity
If multiple robots are used to perform assembly tasks autonomously, then adaptability and productivity are improved, but device complexity increases
Solution Approach 1:
The patent merges multiple robot manipulators into a coordinated system controlled by a single intelligent controller. This unified control architecture manages task allocation, motion coordination, and parameter optimization across all manipulators, achieving high productivity through autonomous operation while preventing system complexity from becoming unmanageable through integrated control.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables flexible and efficient assembly of complex components by accommodating changes in manufacturing processes, improving sensing and control capabilities, and reducing downtime through autonomous operation.
Implementation Method 1
a welding tool configured to weld the first seam formed between the first object and the second object
Data Source
AI summary
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect of the disclosure, the assembly robotic system includes a tool coupled to a robot device and configured to be selectively coupled to a first object. The assembly robotic system also includes a welding tool, one or more sensors configured to generate sensor data, and a controller. The controller is configured to control the tool to couple the tool to the first object based on the sensor data, control the robot device to bring the first object into a spatial relationship with a second object, and generate a weld instruction to cause the weld tool to weld a seam formed between the first and second objects. Other aspects and features are also claimed and described.