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3D safe and intelligent trajectory generation for multi-axis machine tools using machine vision

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Multi-axis high speed production technology importance and complexity is increasing with the increasing demand of its intelligence. Lack of proper automation and intelligence may cause collision risks, time delays and production interruption. Collision is an important problem for multi-axis machines because the current machine technology lacks the proper feedback communication process and hence a minor difference between a real and virtual scene may cause collision in real production. Similarly, minor operator mistakes and complexity of the Computer Aided Design or Manufacturing (CAD/CAM) process can cause collisions in virtual production simulations. Current CAM software and multi-axis machines are capable of detecting collision but are unable to provide safe paths intelligently for its avoidance. This paper uses image processing techniques and CAD/CAM data in order to define safe simulated trajectories for online/off-line virtual production extendible to real production. The 3D Rectangular Enveloped object Safe and Intelligent Trajectory (3D-RESIT) algorithm has been developed to generate safe and intelligent 3D transversal trajectories for virtual preparation by detecting and avoiding collision intelligently. The approach takes three images from the 3D machine model, interprets trajectories from the CAM (G-code), captures the trajectory and objects positions in 3D, detects collisions and provides many intelligent solutions to avoid the same collision process and finally selects the feasible solution. The final results are validated by applying the generated trajectories points back to CAM software simulations for verification.
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Keywords: collision detection and avoidance; image processing; machine intelligence; multi-axis CNC machines; tool paths; trajectory generation

Document Type: Research Article

Affiliations: IRCCyN, Ecole Centrale Nantes, UMR-CNRS 6597 (Team MO2P), 1, rue de la Noe, 44321, Nantes CEDEX 3, France

Publication date: April 1, 2013

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