Research on Coverage Path Planning of Mobile Robot Based on Genetic Algorithm

Deng, San Peng; Wang, Zhong Min; Zhou, Peng; Wu, Hong

doi:10.4028/www.scientific.net/amr.819.379

Cited by 3 publications

(1 citation statement)

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“…Despite these improvements, problems still exist such as complex calculations and low efficiency (Rai et al, 2014). Chen et al uses an uniform cubic B-splines method as a planning function and while this method ensures consistency of the joint angle, angular velocity and acceleration, it is computationally expensive and the functional equations highly complex (Chen, 1991 Xiang, Xie and Lu, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol.12, No.1 (2018) as fuzzy algorithm (Peng et al, 2015), genetic algorithm (Deng et al,2013) and neural network (Simon and Max, 2000) have also been used to improve the planning efficiency, however each has its own limitations and drawbacks.The robot examined in this study is currently used to repair the crack of the spent fuel pool when it is broken due to the external impact loads or stress in the nuclear power stations. To further optimize the welding quality, a smooth trajectory control strategy using Cartesian space planning is proposed.…”

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An optimal trajectory control strategy for underwater welding robot

Xiang

Xie

2018

JAMDSM

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The underwater welding robots are replacing humans in several harsh working environments however further strategies are required to achieve better control of robotic motion in order to extend their utility. This paper presents a smooth trajectory control strategy to improve the welding quality and efficiency using an underwater welding robot to perform the arc welding process. First, a mathematical model of the underwater welding robot is established using the D-H parameter method. Second kinematics equations for the movement of the robot are deduced. To improve the accuracy of the trajectory, the tool coordinate system is calibrated using the six-point method. Finally, linear interpolation with parabolic transition is combined with a six-dimensional space vector to develop a Cartesian space trajectory planning for the robot, which can ensure a smooth welding process. The results show that by using the above control strategy for underwater welding experiments, a smooth welding seam is achieved, which improves the weld quality and shortens the time taken to complete the weld. Keywords : IntroductionThe underwater welding robot is a device that can be moved underwater with a visual and perceptual system, which can replace humans in underwater operating environments. Under the underwater welding process of robot, the motion parameters and welding parameters of underwater welding robot need to be adjusted to adapt to the underwater environment due to the influence of water environment and underwater pressure. At present, underwater welding robots are used to complete a number of dangerous operations (Rowe and Liu, 2001); however the tasks that can be performed are limited due to the complexity of the underwater environment. As such, current robotic welding systems are mainly used for non-destructive testing of welds and crack repairs (Labanowski, 2011). More widespread use will require greater control over trajectory planning. In this study, the trajectory planning of an existing underwater welding robot is investigated with the aim of improving its accuracy. Welding robot trajectory planning allows the robot to move from an initial position to a target location of the process smoothly and at a certain speed and acceleration, within a certain timeframe. Two methods for trajectory planning exist: joint space planning and Cartesian space planning (Nardenio and Douglas, 2008). The former method has been used extensively in industrial robotics systems but presents a number of disadvantages.Joint space planning based on cubic polynomial interpolation has been applied to determine the position and velocity of the manipulator. However it does not take into account continuous planning of acceleration (Liu et al., 2013). The quintic polynomial interpolation method has been applied to the transition angle of the curve in order to achieve smooth transitions of robot motion. Despite these improvements, problems still exist such as complex calculations and low efficiency (Rai et al., 2014). Chen et al uses an uniform cu...

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confidence: 99%