Research on 2D-SLAM of Indoor Mobile Robot based on Laser Radar

Shen, Dong; Xu, Yuhang; Huang, Yunte

doi:10.1145/3351917.3351966

Cited by 11 publications

(2 citation statements)

References 6 publications

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“…Due to its rapid update rate, LIDAR can perform the scan matching function to detect borders and objects quickly and accurately. The initial frame data generated by LiDAR is immediately utilized to create a graph of the home location, after which the sensor data is compared with the map and the optimal position for the LiDAR unit is chosen [21]. The Hector algorithm employs the Gaussian-Newton minimization technique [22], which is regarded as an update to the Newton method and eliminates the need to calculate second derivatives.…”

Section: Environment Mapping Using the Hector Slam Methodsmentioning

confidence: 99%

Development of a Vision-Based Unmanned Ground Vehicle for Mapping and Tennis Ball Collection: A Fuzzy Logic Approach

Latifinavid

Azizi

2023

Future Internet

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The application of robotic systems is widespread in all fields of life and sport. Tennis ball collection robots have recently become popular because of their potential for saving time and energy and increasing the efficiency of training sessions. In this study, an unmanned and autonomous tennis ball collection robot was designed and produced that used LiDAR for 2D mapping of the environment and a single camera for detecting tennis balls. A novel method was used for the path planning and navigation of the robot. A fuzzy controller was designed for controlling the robot during the collection operation. The developed robot was tested, and it successfully detected 91% of the tennis balls and collected 83% of them.

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Section: Environment Mapping Using the Hector Slam Methodsmentioning

confidence: 99%

Development of a Vision-Based Unmanned Ground Vehicle for Mapping and Tennis Ball Collection: A Fuzzy Logic Approach

Latifinavid

Azizi

2023

Future Internet

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“…In addition, SLAM (Simultaneous Localization and Mapping) and path planning are crucial for the autonomous movement of rescue robots. Numerous scholars have made significant advancements in the fields of SLAM and path planning.Shen and colleagues compared three laser-based 2D SLAM algorithms (gapping, Hector-SLAM, and Cartographer) and discussed the strengths and weaknesses of each algorithm [28]. Zhang and collaborators, by comparing three SLAM algorithms and integrating a path planning analysis to assess their applicability in indoor rescue environments, have provided guidance for researchers in the construction of SLAM systems [29].…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of origami robot ROS-based SLAM and autonomous navigation

Zhao,

Zhang,

Shang

2024

PLoS ONE

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In this study an innovative parameterized water-bomb wheel modeling method based on recursive solving are introduced, significantly reducing the modeling workload compared to traditional methods. A multi-link supporting structure is designed upon the foundation of the water-bomb wheel model. The effectiveness of the supporting structure is verified through simulations and experiments. For robots equipped with this water-bomb wheel featuring the multi-link support, base on the kinematic model of multi-link structure, a mapping algorithm that incorporates parameterized kinematic solutions and IMU-fused parameterized odometry is proposed. Based on this algorithm, SLAM and autonomous navigation experiments are carried out in simulation environment and real environment respectively. Compared with the traditional algorithm, this algorithm the precision of SLAM is enhanced, achieving high-precision SLAM and autonomous navigation with a robot error rate below 5%.

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