Mobile Robot Terrain Mapping for Path Planning using Karto Slam and Gmapping Technique

NT, Sanju Kumar; Gawande, Malika; M, Naga Praveen Babu; Verma, Harshal; Rajalakshmi, P.

doi:10.1109/globconpt57482.2022.9938337

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…In future projects, we will use a cost mapping system to generate a safe route to the object if there is an obstacle in the scenario that prevents proper navigation [41]. In addition, having solved the positioning to domestic waste in our BLUE robot, we will design a method for handling this domestic waste in outdoor environments with a robotic arm on board the BLUE robot.…”

Section: Discussionmentioning

confidence: 99%

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

Velasco-Sánchez,

Ángel Muñoz Bañón,

Candelas

et al. 2024

IEEE Access

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While Visual Servoing is deeply studied to perform simple maneuvers, the complex cases where the target is far out of the camera field of view (FOV) during the maneuver are not common in the literature. For this reason, in this paper, we present ViKi-HyCo (Visual Servoing and Kinematic Hybrid-Controller). This approach generates the necessary maneuvers for the complex positioning of a non-holonomic mobile robot in outdoor environments. In this method, we use LiDAR-camera fusion for automatic target calculation. The multi-modal nature of our target representation allows us to hybridize the visual servoing with a kinematic controller. In this way, we can perform complex maneuvers even when the target is far away from the camera's FOV. The automatic target calculation is performed through object localization for outdoor environments, which estimates the spatial location of a target point for the kinematic controller and allows the dynamic calculation of a desired bounding box of the detected object for the visual servoing controller. The proposed approach does not require an object-tracking algorithm and can be applied to any visually tracking robotic task where its kinematic model is known. ViKi-HyCo has an error of 0.0428 ± 0.0467 m in the X-axis and 0.0515 ± 0.0323 m in the Y-axis at the end of a complete positioning task.INDEX TERMS autonomous robots, domestic waste localization, hybrid-control, outdoor environment, sensor fusion, visual servoing.

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Section: Discussionmentioning

confidence: 99%

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

Velasco-Sánchez,

Ángel Muñoz Bañón,

Candelas

et al. 2024

IEEE Access

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Research on ROS-based SLAM Implementation for Indoor Environments

Chen,

Haung,

Chen

et al. 2023

2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE)

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Application and Research on Improved Adaptive Monte Carlo Localization Algorithm for Automatic Guided Vehicle Fusion with QR Code Navigation

Zhang,

Li,

Qiu

et al. 2023

Applied Sciences

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SLAM (simultaneous localization and mapping) technology incorporating QR code navigation has been widely used in the mobile robotics industry. However, the particle kidnapping problem, positioning accuracy, and navigation time are still urgent issues to be solved. In this paper, a SLAM fused QR code navigation method is proposed and an improved adaptive Monte Carlo positioning algorithm is used to fuse the QR code information. Firstly, the generation and resampling methods of initialized particle swarms are improved to improve the robustness and weights of the swarms and to avoid the kidnapping problem. Secondly, the Gmapping scan data and the data generated by the improved AMCL algorithm are fused using the extended Kalman filter to improve the accuracy and stability of the state estimation. Finally, in terms of the positioning system, Gmapping is used to obtain QR code data as marker positions on static maps, and the improved adaptive Monte Carlo localization particle positioning algorithm is matched with a library of QR code templates, which corrects for offset distances and achieves precise point-to-point positioning under grey-valued raster maps. The experimental results show that the particles encountered with kidnapping can be quickly adjusted in position, with a 68.73% improvement in adjustment time, 64.27% improvement in navigation and positioning accuracy, and 42.81% reduction in positioning time.

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Mobile Robot Terrain Mapping for Path Planning using Karto Slam and Gmapping Technique

Cited by 3 publications

References 7 publications

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

ViKi-HyCo: A Hybrid-Control Approach for Complex Car-Like Maneuvers

Research on ROS-based SLAM Implementation for Indoor Environments

Application and Research on Improved Adaptive Monte Carlo Localization Algorithm for Automatic Guided Vehicle Fusion with QR Code Navigation

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