Robotic End Effector Path Generation for Aircraft Fastener Removal
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Solution Overview
Problem
The challenge of uniformly removing aircraft fasteners due to their non-uniform arrangement across different aircraft models, which complicates automated fastener removal systems, as individual orientations and types of fasteners vary, necessitating precise path and trajectory planning for each fastener.
Innovation Solution
A system that guides a robot through dynamic path and trajectory planning using a user interface (UI) for point cloud data segmentation, feature identification, and registration to calculate a trajectory for a robotic end effector, accounting for collisions and robot limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed path planning approach is used for fastener removal, then the system structure is simple, but it cannot adapt to non-uniform fastener arrangements across different aircraft models
Solution Approach 1:
The path planning system transitions from a static fixed path approach to a dynamic adaptive approach. The system generates customized paths and trajectories in real-time based on detected fastener positions, aircraft model variations, and robot operational constraints, enabling adaptation to non-uniform fastener arrangements while maintaining system feasibility through algorithmic optimization
Solution Approach 2:
The system creates virtual models and digital twins of the aircraft and fastener configurations to simulate and plan removal paths before actual execution. This virtual copying allows the system to test and optimize paths for different aircraft models without physical trial-and-error, reducing real-world complexity while improving adaptability
2Manufacturing precision
If customized paths are generated for each fastener, then removal precision is improved, but the time required for path planning increases
Solution Approach 1:
The system performs preliminary path planning and simulation before actual fastener removal. Virtual models are used to pre-calculate optimal paths, and potential collision scenarios are anticipated and resolved in advance. This preliminary action ensures high removal precision while minimizing real-time planning delays during actual operation
Solution Approach 2:
The system replaces time-consuming manual path planning and physical trial-and-error with automated computational algorithms and virtual simulation. Digital twin technology and collision detection algorithms substitute for physical experimentation, enabling rapid generation of precise removal paths without iterative mechanical testing
3Reliability
If the robot trajectory accounts for all collision constraints and robot limitations, then operational safety is improved, but the trajectory calculation complexity increases
Solution Approach 1:
The system introduces virtual models and simulation environments as intermediaries between the robot control system and the physical aircraft. These virtual representations allow collision constraints and robot limitations to be tested and resolved in a risk-free digital environment before actual execution, improving operational safety while managing calculation complexity through staged validation
Solution Approach 2:
The system implements continuous feedback loops during path planning and execution. Real-time sensor data about robot position, aircraft geometry, and potential obstacles feed back into the trajectory calculation algorithms, allowing dynamic adjustment of paths to maintain safety margins. This feedback mechanism ensures operational reliability while distributing computational complexity across multiple processing stages
Data Source
AI summary
Aspects of the disclosure are directed towards path generation. A method includes a computing system registering a first coordinate system of a target object with a second coordinate system of a robot. The computing system can generate a trajectory over the surface of the target object based on the registration. The computing system can generate a robot job file based at least in part on the generated trajectory. The computing system can transmit the robot job file to a robot controller.