Auto-Docking Gantry Locking for Jig-Based Robot Positioning
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Solution Overview
Problem
The identification of the appropriate jig, machine part, and job for autonomous robotic operations in industrial settings is computationally complex and prone to human error, requiring a system to automatically detect and determine the necessary template for robotic actions.
Innovation Solution
A robotic system that uses sensors to detect jigs and machine parts, determines a template specifying the distance and angle for robotic movement, and executes jobs by generating and implementing instructions based on sensor input, utilizing a network environment with local and remote computer systems for data processing and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual identification of jig, machine part, and job is used for robotic operations, then system complexity is reduced, but human error increases and productivity decreases
Solution Approach 1:
The robotic system automatically performs identification of jigs, machine parts, and jobs using sensors and computer vision without human intervention. The system self-determines the appropriate template and executes operations autonomously, eliminating manual identification processes and reducing human error while maintaining manageable complexity through automated decision-making algorithms.
Solution Approach 2:
Manual mechanical identification processes are replaced with sensor-based detection systems including cameras, LIDAR, and other sensing devices. The system uses optical and electronic fields to detect and identify objects, substituting human visual and cognitive processes with automated sensing and processing mechanisms that improve accuracy while managing system complexity through software algorithms.
2Productivity
If automated sensor-based detection is implemented, then productivity and precision are improved, but device complexity increases
Solution Approach 1:
The robotic system employs multi-functional sensors and detection mechanisms that can identify various types of jigs, machine parts, and operational contexts using the same hardware platform. The system processes multiple data types (visual, spatial, contextual) through integrated algorithms, enabling rapid deployment across different operations without requiring separate specialized systems for each function, thus improving productivity while managing complexity through consolidation.
3Measurement precision
If comprehensive sensor input processing is used, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The data processing system divides comprehensive sensor input into distinct processing stages and modules. Each sensor type and detection function is handled by specialized sub-routines that process specific data aspects independently before integration. This segmented approach enables high measurement precision through detailed analysis of each data source while managing overall computational complexity through modular architecture and distributed processing.
Data Source
AI summary
The present disclosure relates to system for auto-docking a robot to jig holding an airplane part to execute a job. In an example, a robot is tasked with performing an operation associated with an airplane part held by or affixed to a jig. To do so, the robot may utilize sensor input from associated sensors to identify the jig, the airplane part, and determine a particular template associated with the jig and airplane part. The particular template may specify a threshold distance which the robot needs to move towards the jig and dock itself near the jig in order to execute the job associated with the airplane part. Once a particular template is identified, the robot may be instructed to move towards the jig using the input from the associated sensors until it reaches the threshold distance.