Photogrammetric Cable Robot Layout for Collision-Free 3D Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Adapting cable robots for photogrammetry is complex due to accessibility issues caused by collisions between cables, the platform, and the environment, and ensuring camera stability and unobstructed views, making it difficult to perform 3D measurements of large objects.
Innovation Solution
A method for parameterizing a photogrammetric cable robot by determining sets of vectors representing possible cable exit points, applying genetic algorithms to optimize positions and orientations for collision minimization, equilibrium constraint satisfaction, and camera field of view, using a combination of objective functions to evaluate collision percentage, equilibrium violation, and tension constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If cable robots are used for photogrammetry, then rapid translation movement is achieved, but collision phenomena occur between cables, platform, and environment
Solution Approach 1:
The patent applies preliminary action by pre-determining the set of vectors representing all possible positions of cable exit points before actual operation. This allows the system to plan and avoid collision-prone configurations in advance, selecting only those exit point positions that enable collision-free operation while maintaining rapid translation capability.
Solution Approach 2:
The patent implements dynamics by making the exit points mobile relative to the frame, allowing adaptive configuration of the robot. The genetic algorithm dynamically selects optimal exit point positions from the predetermined set based on the specific measurement task, enabling the system to adapt its configuration to avoid collisions while maintaining speed.
2Measurement precision
If cable positions are adjusted to avoid collisions, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies self-service by using a genetic algorithm that automatically evaluates and selects optimal cable exit point configurations based on predefined criteria (collision avoidance, measurement accuracy, platform equilibrium). The system self-optimizes its parameterization without requiring manual intervention, handling the complexity internally while providing accurate measurements.
Solution Approach 2:
The patent implements parameter changes by varying the positions of cable exit points on the frame to optimize system performance. The genetic algorithm systematically explores different parameter configurations (exit point positions) to find the optimal set that balances measurement precision with collision avoidance, managing complexity through automated parameter optimization.
3Measurement precision
If multiple objective functions are combined for optimization, then measurement quality is improved, but computational complexity increases
Solution Approach 1:
The patent applies merging by combining multiple objective functions (collision percentage, equilibrium constraint violation, tension constraints) into a single fitness function. This unified fitness function allows the genetic algorithm to simultaneously optimize for multiple criteria in a single computational framework, improving measurement quality while managing computational complexity through integration rather than separate optimizations.
Data Source
AI summary
A method for parameterizing a photogrammetric cable robot, having a frame, a mobile platform carrying a camera and cables, each cable extending from a mobile platform attachment point to a position-adjustable exit point, while remaining linked to the frame. The robot's maximum workspace is defined by the ranges of possible positions of the different cable exit points. A set of pairs of setpoint positions and orientations of the platform is determined, for performing the point measurements of a scene by photogrammetry. Then, a genetic algorithm comprising crossing, transformation and selection operations is applied to a population of vectors, each representing respective positions of cable exit points, the selection being made via a fitness function involving a first objective function evaluating a collision percentage and a second objective function evaluating a percentage violation of a mobile platform constraint of equilibrium, when the platform assumes the different setpoint positions and orientations.