Abstract

The trend towards automation and intelligence in aircraft final assembly testing has led to a new demand for autonomous perception of unknown cockpit operation scenes in robotic collaborative airborne system testing. To address this demand, a robotic automated 3D reconstruction cell which enables to autonomously plan the robot end-camera's trajectory is developed for image acquisition and 3D modeling of the cockpit operation scene. A continuous viewpoint path planning algorithm is proposed that incorporates both 3D reconstruction quality and robot path quality into optimization process. Smoothness metrics for viewpoint position paths and orientation paths are introduced together for the first time in 3D reconstruction. To ensure safe and effective movement, two spatial constraints, Domain of View Admissible Position (DVAP) and Domain of View Admissible Orientation (DVAO), are implemented to account for robot reachability and collision avoidance. By using diffeomorphism mapping, the orientation path is transformed into 3D, consistent with the position path. Both orientation and position paths can be optimized in a unified framework to maximize the gain of reconstruction quality and path smoothness within DVAP and DVAO. The reconstruction cell is capable of automatic data acquisition and fine scene modeling, using the generated robot C-space trajectory. Simulation and physical scene experiments have confirmed the effectiveness of the proposed method to achieve high-precision 3D reconstruction while optimizing robot motion quality.

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