Research on Intelligent Disinfection-Vehicle System Design and Its Global Path Planning

Chen, Lifang; Yang, Hua; Chen, Zhichao; Feng, Zhicheng

doi:10.3390/electronics12071514

Cited by 6 publications

(3 citation statements)

References 35 publications

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“…The paper [3] emphasizes the rising interest in unmanned non-contact robots for environmental disinfection, highlighting their autonomous disinfection capabilities in hospitals to reduce manpower costs, lower staff exposure risks, and enhance informatized management. Reference [4] employs ROS and SLAM for indoor mapping, proposing a novel A* and Floyd algorithm-based path-planning method. Reference [5] develops an autonomous navigation robot for high-risk areas, achieving a 99.9% disinfection effect against various bacterial strains.…”

Section: Related Workmentioning

confidence: 99%

A disinfection vehicle featuring dynamic mask recognition and spraying capability

Li,

Liu,

Zha

et al. 2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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In the context of advancing technology and artificial intelligence, this paper introduces an innovative disinfection vehicle with autonomous disinfection, mask recognition, and spraying capabilities. Leveraging advanced obstacle avoidance and positioning technologies, the robot autonomously plans disinfection routes, adapting to various environments and minimizing dependence on human resources. The integration of mask recognition enhances public health safety during the disinfection process. The robot's multifunctionality extends to spraying operations, optimizing overall operational efficiency. Empirical validation underscores its effectiveness and practicality, positioning this vehicle as a robust support system for public health prevention and control efforts. This technological advancement promises efficient and secure disinfection services for public spaces, making a significant contribution to the evolution of public health measures.

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Section: Related Workmentioning

confidence: 99%

A disinfection vehicle featuring dynamic mask recognition and spraying capability

Li,

Liu,

Zha

et al. 2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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“…Yu et al proposed to extend 20 neighborhoods and design a safe distance to make the planned path smoother [15] . Chen et al considered the safe distance of the robot and proposed A path planning method combining A* algorithm and Floyd algorithm to ensure the safety of the path [16] . Li et al introduced the bidirectional alternate search (BAS) strategy to improve the search path efficiency, and reduced the path length and turning angle by filtering the path nodes [17] .…”

Section: Introductionmentioning

confidence: 99%

Global path planning for mobile robots based on improved A-Star algorithm

Zhang,

Dong,

Zhang

et al. 2024

Preprint

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Aiming at the problems of lengthy planning time, easy to fall into local optimization, and insufficient ability to adapt to complex environments in the global path planning process of A-Star algorithm, we propose an improved A-Star algorithm. First, we introduce global obstacle information and local obstacle information into the heuristic function to adapt to different environmental requirements, and propose a U-shaped "trap" region filling strategy to reduce the number of searched nodes and improve the search efficiency. Secondly, we assign a priority to the search neighborhood and use directional gain to enhance the orientation of the search process. Then, we introduce a key node selection strategy to eliminate redundant nodes on the path and improve the smoothness of the path. Simulation results prove that the algorithm in this paper has significant improvement in terms of the number of traversed nodes, path nodes, path inflection nodes, turning angle, pathfinding time and path length. Finally, we experiment with the improved algorithm in a real environment, proving the effectiveness of the improved algorithm and demonstrating its ability to significantly enhance the performance of mobile robot path planning.

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“…Localization and mapping are two important basic capabilities for achieving safe autonomous driving. SLAM technology can quickly map the field environment and effectively assist vehicles in completing automatic driving in complex settings [ 7 , 8 ]. Therefore, it is of great practical significance to carry out research on SLAM technology in complex field environments.…”

Section: Introductionmentioning

confidence: 99%

A Localization and Mapping Algorithm Based on Improved LVI-SAM for Vehicles in Field Environments

Han

Shi

Wang

2023

Sensors

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Quickly grasping the surrounding environment’s information and the location of the vehicle is the key to achieving automatic driving. However, accurate and robust localization and mapping are still challenging for field vehicles and robots due to the characteristics of emptiness, terrain changeability, and Global Navigation Satellite System (GNSS)-denied in complex field environments. In this study, an LVI-SAM-based lidar, inertial, and visual fusion using simultaneous localization and mapping (SLAM) algorithm was proposed to solve the problem of localization and mapping for vehicles in such open, bumpy, and Global Positioning System (GPS)-denied field environments. In this method, a joint lidar front end of pose estimation and correction was designed using the Super4PCS, Iterative Closest Point (ICP), and Normal Distributions Transform (NDT) algorithms and their variants. The algorithm can balance localization accuracy and real-time performance by carrying out lower-frequency pose correction based on higher-frequency pose estimation. Experimental results from the complex field environment show that, compared with LVI-SAM, the proposed method can reduce the translational error of localization by about 4.7% and create a three-dimensional point cloud map of the environment in real time, realizing the high-precision and high-robustness localization and mapping of the vehicle in complex field environments.

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Research on Intelligent Disinfection-Vehicle System Design and Its Global Path Planning

Cited by 6 publications

References 35 publications

A disinfection vehicle featuring dynamic mask recognition and spraying capability

A disinfection vehicle featuring dynamic mask recognition and spraying capability

Global path planning for mobile robots based on improved A-Star algorithm

A Localization and Mapping Algorithm Based on Improved LVI-SAM for Vehicles in Field Environments

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