A Simple Modeling Method and Trajectory Planning for a Car-Like Climbing Robot Used to Strip Coating From the Outer Surface of Pipes Underwater

Wang, Hansong; Yang, Canjun; Deng, Xuelei; Fan, Jinchang

doi:10.1142/9789814725248_0084

Cited by 1 publication

(2 citation statements)

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“…A UPCR is a wheeled climbing robot designed to clean biofouling covered on the jacket of offshore platforms. Equipped with magnetic wheels and a self-adaption mechanism, a UPCR can move steadily on the pipe, while stripping the biofouling with a cavitation water jet [9,25]. In order to observe the UPCR's surrounding environment during operation, a catadioptric panoramic imaging system composed of a camera and a mirror was designed to acquire images for local localization, as shown in Figure 2.…”

Section: Prototype Descriptionmentioning

confidence: 99%

“…The UPCR has three actuators situated in the front wheel, the back wheel, and the turning mechanism. Based on the kinematic model of the robot [25], the number of active degrees of freedom (DOFs) is two as movement of the back wheel is constrained by the front wheel and the turning mechanism. Meanwhile, because the velocity of the front wheel is always slow and does not affect the trajectory to follow the reference path, it is preset and the angle of the turning mechanism is determined as the control output.…”

Section: Fusion Bat Algorithm-optimized Fuzzy Controllermentioning

confidence: 99%

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Novel Online Optimized Control for Underwater Pipe-Cleaning Robots

et al. 2020

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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.

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Section: Prototype Descriptionmentioning

confidence: 99%

Section: Fusion Bat Algorithm-optimized Fuzzy Controllermentioning

confidence: 99%