Weld line recognition and path planning with spherical tank inspection robots

2021 ◽  
Author(s):  
Jie Li ◽  
Shanshan Jin ◽  
Cunjin Wang ◽  
Jiameng Xue ◽  
Xingsong Wang
Keyword(s):  
Path Planning ◽  
Weld Line ◽  
Spherical Tank ◽  
Inspection Robots

scholarly journals Hybrid chaos-based particle swarm optimization-ant colony optimization algorithm with asynchronous pheromone updating strategy for path planning of landfill inspection robots

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141985908 ◽  
Author(s):  
Peng Chen ◽  
Qing Li ◽  
Chao Zhang ◽  
Jiarui Cui ◽  
Hao Zhou
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Ant Colony Optimization ◽  
Particle Swarm ◽  
Ant Colony ◽  
Planning Problem ◽  
Swarm Optimization ◽  
Gas Poisoning ◽  
Inspection Robots ◽  
Elitist Strategy

Robots are coming to help us in different harsh environments such as deep sea or coal mine. Waste landfill is the place like these with casualty risk, gas poisoning, and explosion hazards. It is reasonable to use robots to fulfill tasks like burying operation, transportation, and inspection. In these assignments, one important issue is to obtain appropriate paths for robots especially in some complex applications. In this context, a novel hybrid swarm intelligence algorithm, ant colony optimization enhanced by chaos-based particle swarm optimization, is proposed in this article to deal with the path planning problem for landfill inspection robots in Asahikawa, Japan. In chaos-based particle swarm optimization, Chebyshev chaotic sequence is used to generate the random factors for particle swarm optimization updating formula so as to effectively adjust particle swarm optimization parameters. This improved model is applied to optimize and determine the hyper parameters for ant colony optimization. In addition, an improved pheromone updating strategy which combines the global asynchronous feature and “Elitist Strategy” is employed in ant colony optimization in order to use global information more appropriately. Therefore, the iteration number of ant colony optimization invoked by chaos-based particle swarm optimization can be reduced reasonably so as to decrease the search time effectively. Comparative simulation experiments show that the chaos-based particle swarm optimization-ant colony optimization has a rapid search speed and can obtain solutions with similar qualities.

A Heuristic Path Planning Algorithm for Inspection Robots

2020 ◽  
Author(s):  
Qichao Tang ◽  
Lei Ma ◽  
Yongkui Sun ◽  
Guang Yang ◽  
Zhongfa Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Planning Algorithm ◽  
Inspection Robots ◽  
Path Planning Algorithm

scholarly journals Design and Collaborative Operation of Multimobile Inspection Robots in Smart Microgrids

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Nankai Chen ◽  
Yaonan Wang
Keyword(s):  
Neural Network ◽  
Path Planning ◽  
Single Point ◽  
Large Power ◽  
Power Stations ◽  
Simulation Results ◽  
Inspection Tasks ◽  
Point Inspection ◽  
Inspection Robots

This paper investigates the substation inspection problems of multimobile robots for large power stations in smart microgrids. Most multirobot inspection robots generally face the challenge of path planning, while the current widely used biological excitation neural network (BENN) methods often have the defect of the neuronal active field near boundaries and obstacles. To end this, we propose an improved biological excitation neural network (IBENN) method for path planning based on a detailed architecture and ontology framework, through which the single-point inspection, multipoint inspection, and full-area inspection tasks of substations in smart microgrids can be well completed. Simulation results show that the designed IBENN-based multirobot collaboration inspection (MRCI) system can effectively shorten the path as well as the number of turns and then show better performance than most existing results when implementing various substation inspection tasks.

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