A Multirobot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-Inspired Neural Network

Chen, Bin; Zhang, Hui; Zhang, Fangfang; Liu, Yanhong; Tan, Cheng; Yu, Hongnian; Wang, Yaonan

doi:10.1109/tcds.2022.3218718

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…14 With unknown environment, the accuracy of map building directly affects the quality of CPP. Therefore, some researches utilize machine learning 15,16 or neural network 17 to establish and update map, then accomplish CPP based on it. As we can see, the quality of CPP is limited by the accuracy of sensors equipped on robots.…”

Section: Cpp For 2d Surfacesmentioning

confidence: 99%

Multiple chromosomes particle swarm optimization-based coverage path planning for complex surfaces spray painting

Gao,

2024

International Journal of Advanced Robotic Systems

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Coverage path planning for complex three-dimensional surfaces spray painting is one of the challenging problems in robotics. In this article, we propose a multiple chromosomes particle swarm optimization approach to address the coverage path planning problem for complex three-dimensional surfaces spray painting. Firstly, a layered segmentation method, which is composed of three-dimensional hole identification and region partition, is proposed to divide the complex surface into multiple simple regions with little curvature change and no holes. Secondly, a zigzag path is determined in each region by considering the practical aspects for spray painting. Thirdly, by taking short distance, few turns and high coverage rate into account, a multiple chromosomes particle swarm optimization algorithm is presented to connect the zigzag paths of the regions. Experimental tests are carried out on a complex surface, and the results validate the effectiveness of the proposed approach.

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Section: Cpp For 2d Surfacesmentioning

confidence: 99%

Multiple chromosomes particle swarm optimization-based coverage path planning for complex surfaces spray painting

Gao,

2024

International Journal of Advanced Robotic Systems

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“…To address the many constraints for a multi‐robot system to perform a region coverage search task in an unknown environment, (Chen et al, 2022) propose a novel multi‐robot distributed collaborative region coverage search algorithm based on GBNN. The model converts the environmental information detected by the robot into dynamic neural activity landscape of GBNN.…”

Section: Related Workmentioning

confidence: 99%

GBNN algorithm enhanced by movement planner for UV‐C disinfection

Rodrigo,

Sierra‐García,

Santos

2023

Expert Systems

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In order to maintain adequate levels of cleanliness and sanitation in public facilities, prevent the buildup of viruses and other harmful pathogens, and ensure health and safety, health and labor authorities have repeatedly warned of the need to adhere to proper disinfection protocols in the workplace. This is particularly important in public places where food is handled, where there are more vulnerable people, including hospitals and health care centers, or where there is a large concentration of people. One promising approach is the combination of ultraviolet‐C (UV‐C) light and mobile robots to automate disinfection processes. Being this technology effective for disinfection, an excessive dose of UV can damage the materials, limiting its applicability. Therefore, a major challenge for automatic disinfection is to find a route that covers the entire surface, ensures cleanliness, and provides the correct radiation dose while preventing environmental materials from being damaged. To achieve this, in this paper a novel intelligent control approach is proposed. A bio‐inspired Glasius neural network with a motion planner, an UV estimation module, a speed regulator, and pure pursuit controller are combined into one intelligent system. The motion planner proposes a sequence of movements to go through the space in the most efficient way possible, avoiding obstacles of the environment. The speed controller adjusts the dose of UV‐C radiation and the pure pursuit regulator ensures the following of the path. This approach has been tested in various simulation scenarios of increasing complexity and in four different areas of dosing requirements. In simulation, a 44% reduction of the maximum dose is achieved, 17% less distance travelled by the robot and, what is more important, 229% more locations with the appropriate dose.

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Optimal coverage path planning for USV-assisted coastal bathymetric survey: Models, solutions, and lake trials

Zhao,

Bai,

Paik

2024

Ocean Engineering

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A Multirobot Distributed Collaborative Region Coverage Search Algorithm Based on Glasius Bio-Inspired Neural Network

Cited by 6 publications

References 34 publications

Multiple chromosomes particle swarm optimization-based coverage path planning for complex surfaces spray painting

Multiple chromosomes particle swarm optimization-based coverage path planning for complex surfaces spray painting

GBNN algorithm enhanced by movement planner for UV‐C disinfection

Optimal coverage path planning for USV-assisted coastal bathymetric survey: Models, solutions, and lake trials

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