Novel Online Optimized Control for Underwater Pipe-Cleaning Robots

Due to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm (BA) online optimized fuzzy control method using vision localization was developed based on the constraints of the underwater operational environment. Vision localization was achieved based on images from a catadioptric panoramic imaging system. The features of the pipe edge and the boundary of the area covered by biofouling were obtained by image processing and feature extraction. The feature point chosen as the “highest” point of the boundary was calculated by projection transformation to generate the reference path. The specialized fuzzy controller was designed to drive the robot to track the reference path, and an improved bat algorithm with dynamic inertia weight and differential evolution method was developed to optimize the scale factors of the fuzzy controller online. The control method was simulated and further implemented on an underwater pipe-cleaning robot (UPCR), and the results indicate its rationality and validity.

AGV Localization System Based on Ultra-Wideband and Vision Guidance

Aiming at the problems of low localization accuracy and complicated localization methods of the automatic guided vehicle (AGV) in the current automatic storage and transportation process, a combined localization method based on the ultra-wideband (UWB) and the visual guidance is proposed. Both the UWB localization method and the monocular vision localization method are applied to the indoor location of the AGV. According to the corner points of an ArUco code fixed on the AGV body, the monocular vision localization method can solve the pose information of the AGV by the PnP algorithm in real-time. As an auxiliary localization method, the UWB localization method is called to locate the AGV coordinates. The distance from the tag on the AGV body to the surrounding anchors is measured by the time of flight (TOF) ranging algorithm, and the actual coordinates of the AGV are calculated by the trilateral centroid localization algorithm. Then, the localization data of the UWB is corrected by the mean compensation method to obtain a consistent and accurate localization trajectory. The experiment result shows that this localization system has an error of 15mm, which meets the needs of AGV location in the process of automated storage and transportation.

Localization of Substation Fittings Based on a Stereo Vision Method

We propose a novel stereo vision method based on a fast template matching strategy to improve localization accuracy and efficiency of substation fittings. First, considering the salient features of the substation fittings that can be recognized easily, the method searches for features that are similar to the ones in the matching template related to the sub-image of the substation fittings from the global image. When the substation fittings are confirmed, the method repeatedly searches for the one of screw holes in the local region of the substation fittings. It then computes the centering coordinates of the template in the source images until the screw holes are matched. The experimental results show that the proposed template matching method increases the accuracy and efficiency of the substation fitting localization from the global to local search area. Correspondingly, the accuracy and efficiency of stereo vision localization of substation fittings is improved.