Aiming at the problem that it is difficult to accurately locate the underwater circular pipe orifice for the underwater pipe orifice inspection robot, a visual position measurement method for the underwater circular pipe orifice based on the spatial elliptic cone model is designed. Firstly, a simple and easy solution is proposed for the influence of underwater light refraction on camera calibration, and then a set of image processing procedures is proposed for the problems of low recognition rate and poor image quality of underwater orifice images, which can stably extract the edge contour of the underwater orifice. The algorithm process mainly includes the use of bilinear interpolation to narrow the edge transition region, the use of dark channel a priori defogging algorithm to eliminate the image blurring caused by the water body, and the Canny algorithm combined with elliptic filtering to finally get the target orifice contour. Finally, the spatial elliptic cone model is used to calculate the position and attitude of the target orifice in the camera coordinate system. In order to verify the feasibility of this underwater nozzle position measurement method, a positional accuracy measurement device is constructed using a high-precision rotary stage and a translation stage. The experimental results show that the visual localization method designed in this paper has high recognition and localization accuracy, and can meet the needs of practical localization.
An improvement project for LAMOST is to be implemented soon. In order to reduce the heat generation of the drive system and improve the observation accuracy. In this paper, an ultra-low power drive system for an integrated fiber positioner robot is designed, and its hardware drive circuit and low-power software driver are described in detail. Each module in the hardware driver circuit is designed with its size and power consumption in mind, and the driver board is powered by time-sharing and partitioning. A task scheduling mechanism based on STM32 low-power mode is designed in the software driver of the fiber positioner robot, which analyzes the idle state between tasks when it receives a control command task, and selectively enters the low-power mode after executing the drive task in each round. In order to evaluate the low-power characteristics of this ultra-low power drive system, we built a power consumption measurement platform. The experimental results show that the static power supply current of each driver board in this designed ultra-low power driver system is 16.20mA, and its static power consumption is reduced by 92.50% compared with the previous generation of fiber positioner robot driver boards.
An improvement project of LAMOST will be implemented soon. To improve the observation accuracy and spectral acquisition rate, a new integrated fiber positioner was designed for the new robotic Focal Plane System. This paper designs the drive system for the integrated fiber positioner, and introduces the mechanical, electronic and software design in detail. We also built a vision measurement platform with a telecentric lenses to test the position performance. The fiber positioner positions the fiber to target by first blind positioning and multiple position corrections. After the positioner completes the first blind move, the camera takes the fiber image and calculates the offset between the actual position of the fiber from its target position. Then, the drive system controls the fiber positioner move according the offset value to correct the fiber position. We achieve the final accuracy through iterative position corrections. Experimental results show that both the drive system and the fiber positioner have reliable performance and high efficiency. With a first blind move inside of its workspace, the positioner can position the fibers with a planar precision better than 100um, the position error is less than 10um after the second correction and the RMS error is less than 3um.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.