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21 pages, 5334 KB

Open AccessFeature PaperArticle

EKF-SLAM for Quadcopter Using Differential Flatness-Based LQR Control

by Shyam Rauniyar, Sameer Bhalla, Daegyun Choi and Donghoon Kim

Electronics 2023, 12(5), 1113; https://doi.org/10.3390/electronics12051113 - 24 Feb 2023

Cited by 14 | Viewed by 3119

SLAM (Simultaneous Localization And Mapping) in unmanned aerial vehicles can be an advantageous proposition during dangerous missions where aggressive maneuvers are paramount. This paper proposes to achieve it for a quadcopter using a differential flatness-based linear quadratic regulator while utilizing sensor measurements of [...] Read more.

SLAM (Simultaneous Localization And Mapping) in unmanned aerial vehicles can be an advantageous proposition during dangerous missions where aggressive maneuvers are paramount. This paper proposes to achieve it for a quadcopter using a differential flatness-based linear quadratic regulator while utilizing sensor measurements of an inertial measurement unit and light detection and ranging considering sensors’ constraints, such as a limited sensing range and field of view. Additionally, a strategy to reduce the computational effort of Extended Kalman Filter-based SLAM (EKF-SLAM) is proposed. To validate the performance of the proposed approach, this work considers a quadcopter traversing an 8-shape trajectory for two scenarios of known and unknown landmarks. The estimation errors for the quadcopter states are comparable for both cases. The accuracy of the proposed method is evident from the Root-Mean-Square Errors (RMSE) of 0.04 m, 0.04 m/s, and 0.34 deg for the position, velocity, and attitude estimation of the quadcopter, respectively, including the RMSE of 0.03 m for the landmark position estimation. Lastly, the averaged computational time for each step of EKF-SLAM with respect to the number of landmarks can help to strategically choose the respective number of landmarks for each step to maximize the use of sensor data and improve performance. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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16 pages, 30033 KB

Open AccessArticle

Synthetic Infra-Red Image Evaluation Methods by Structural Similarity Index Measures

by Sky H. Lee and Henzeh Leeghim

Electronics 2022, 11(20), 3360; https://doi.org/10.3390/electronics11203360 - 18 Oct 2022

Cited by 1 | Viewed by 3260

Abstract

For synthetic infra-red (IR) image generation, a new approach using CycleGAN based on the structural similarity index measure (SSIM) is addressed. In this study, how window sizes and weight parameters of SSIM would affect the synthetic IR image constructed by CycleGAN is analyzed. [...] Read more.

For synthetic infra-red (IR) image generation, a new approach using CycleGAN based on the structural similarity index measure (SSIM) is addressed. In this study, how window sizes and weight parameters of SSIM would affect the synthetic IR image constructed by CycleGAN is analyzed. Since it is focused on the acquisition of a more realistic synthetic image, a metric to evaluate similarities between the synthetic IR images generated by the proposed CycleGAN and the real images taken from an actual UAV is also considered. For image similarity evaluations, the power spectrum analysis is considered to observe the extent to which synthetic IR images follow the actual image distribution. Furthermore, the representative t-SNE analysis as a similarity measure is also conducted. Finally, the synthetic IR images generated by the CycleGAN suggested is investigated by the metrics proposed in this paper. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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13 pages, 9877 KB

Open AccessArticle

Fault Detection of an Actuator with Dual Type Motors and One Common Motion Sensor

by Jaehyun Jin

Electronics 2022, 11(20), 3338; https://doi.org/10.3390/electronics11203338 - 17 Oct 2022

Cited by 2 | Viewed by 2060

Abstract

In urban aerial mobility (UAM), the blade pitch angle is adjusted for flight control. Electro-mechanical actuators based on redundant motors have been used for controlling the blade pitch angle. This study addresses the problem of detecting faults in such redundant motors. In particular, [...] Read more.

In urban aerial mobility (UAM), the blade pitch angle is adjusted for flight control. Electro-mechanical actuators based on redundant motors have been used for controlling the blade pitch angle. This study addresses the problem of detecting faults in such redundant motors. In particular, the system is composed of two redundant motors using one common sensor for acquiring rotation-related information. In this study, the authors do not use current signals that have been widely used for fault detection in previous studies. Instead, we propose a method of modulating control signals with time-varying weights for determining a faulty motor. The proposed method is verified through simulation examples and experiments. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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21 pages, 3058 KB

Open AccessArticle

Dubins Path-Oriented Rapidly Exploring Random Tree* for Three-Dimensional Path Planning of Unmanned Aerial Vehicles

by Youyoung Yang, Henzeh Leeghim and Donghoon Kim

Electronics 2022, 11(15), 2338; https://doi.org/10.3390/electronics11152338 - 27 Jul 2022

Cited by 9 | Viewed by 3727

Abstract

Unmanned aerial vehicles (UAVs) do not collide with obstacles, generate a path in real-time, and must fly to the target point. The sampling-based rapidly exploring random tree (RRT) algorithm has the advantages of fast computation and low computational complexity. It is suitable for [...] Read more.

Unmanned aerial vehicles (UAVs) do not collide with obstacles, generate a path in real-time, and must fly to the target point. The sampling-based rapidly exploring random tree (RRT) algorithm has the advantages of fast computation and low computational complexity. It is suitable for real-time path generation, but the optimal path cannot be guaranteed. Further, the direction of the flight and the minimum radius of rotation have not been taken into account for the characteristics of the UAVs. This work proposes a Dubins path-oriented RRT* algorithm, which applies the Dubins path to the RRT algorithm to consider the direction of flight and the minimum radius of rotation and improves optimality and convergence. The proposed algorithm sets the sample node as the target point, orients toward the Dubins path, and then generates a tree. To verify the performance of the proposed algorithm, it is compared with existing RRT algorithms. As a result of performance analysis, the proposed algorithm improved the path length by 14.87% and the calculation time by 82.36%. Finally, the algorithm’s performance is verified by applying the proposed algorithm to a fixed-wing UAV and performing a numerical analysis of the generated path. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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10 pages, 4857 KB

Open AccessArticle

YOLO MDE: Object Detection with Monocular Depth Estimation

by Jongsub Yu and Hyukdoo Choi

Electronics 2022, 11(1), 76; https://doi.org/10.3390/electronics11010076 - 27 Dec 2021

Cited by 19 | Viewed by 15483

Abstract

This paper presents an object detector with depth estimation using monocular camera images. Previous detection studies have typically focused on detecting objects with 2D or 3D bounding boxes. A 3D bounding box consists of the center point, its size parameters, and heading information. [...] Read more.

This paper presents an object detector with depth estimation using monocular camera images. Previous detection studies have typically focused on detecting objects with 2D or 3D bounding boxes. A 3D bounding box consists of the center point, its size parameters, and heading information. However, predicting complex output compositions leads a model to have generally low performances, and it is not necessary for risk assessment for autonomous driving. We focused on predicting a single depth per object, which is essential for risk assessment for autonomous driving. Our network architecture is based on YOLO v4, which is a fast and accurate one-stage object detector. We added an additional channel to the output layer for depth estimation. To train depth prediction, we extract the closest depth from the 3D bounding box coordinates of ground truth labels in the dataset. Our model is compared with the latest studies on 3D object detection using the KITTI object detection benchmark. As a result, we show that our model achieves higher detection performance and detection speed than existing models with comparable depth accuracy. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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19 pages, 1560 KB

Open AccessArticle

Angular Rate Constrained Sliding Mode Control of UAVs for Path Following

by Seok-ho Jang, Youyoung Yang and Henzeh Leeghim

Electronics 2021, 10(22), 2776; https://doi.org/10.3390/electronics10222776 - 12 Nov 2021

Cited by 2 | Viewed by 2332

Abstract

In this work, a sliding-mode-based attitude controller constrained with the angular rate for unmanned aerial vehicles (UAVs) is addressed to withstand conditions below the allowable maximum angular velocity of UAVs in order to avoid the possibility of structural failure and to operate UAVs [...] Read more.

In this work, a sliding-mode-based attitude controller constrained with the angular rate for unmanned aerial vehicles (UAVs) is addressed to withstand conditions below the allowable maximum angular velocity of UAVs in order to avoid the possibility of structural failure and to operate UAVs safely. The sliding mode controller suggested in this work defines a new sliding surface, inherently having two equilibrium points. These equilibrium points are carefully inspected, and the stability of the system controlled by means of the proposed approach is also analyzed using Lyapunov stability theory. To highlight the angular-rate constrained attitude control technique, a three-dimensional path is constructed using the Dubins path technique, and three-axis attitude commands for UAV are also generated by augmenting the line-of-sight algorithm. Compared with conventional sliding mode control measures, the excellent performance of the suggested control algorithm has been demonstrated by conducting numerical simulations. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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13 pages, 8687 KB

Open AccessArticle

Autonomous Trajectory Planning and Control of Anti-Radiation Loitering Munitions under Uncertain Conditions

by Linyuan Bai, Hongchuan Luo and Haifeng Ling

Electronics 2021, 10(19), 2399; https://doi.org/10.3390/electronics10192399 - 30 Sep 2021

Cited by 1 | Viewed by 6154

Abstract

As an autonomous system, an anti-radiation loitering munition (LM) experiences uncertainty in both a priori and sensed information during loitering because it is difficult to accurately know target radar information in advance, and the sensing performance of the seeker is affected by disturbance [...] Read more.

As an autonomous system, an anti-radiation loitering munition (LM) experiences uncertainty in both a priori and sensed information during loitering because it is difficult to accurately know target radar information in advance, and the sensing performance of the seeker is affected by disturbance and errors. If, as it does in the state of the art, uncertainties are ignored and the LM travels its planned route, its battle effectiveness will be severely restricted. To tackle this problem, this paper studies the method of autonomous planning and control of loitering routes using limited a priori information of target radar and real-time sensing results. We establish a motion and sensing model based on the characteristics of anti-radiation LMs and use particle filtering to iteratively infer the target radar information. Based on model predictive control, we select a loitering path to minimize the uncertainty of the target information, so as to achieve trajectory planning control that is conducive to the acquisition of target radar information. Simulation results show that the proposed method can effectively complete the autonomous trajectory planning and control of anti-radiation LMs under uncertain conditions. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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15 pages, 2288 KB

Open AccessArticle

The Method of Static Semantic Map Construction Based on Instance Segmentation and Dynamic Point Elimination

by Jingyu Li, Rongfen Zhang, Yuhong Liu, Zaiteng Zhang, Runze Fan and Wenjiang Liu

Electronics 2021, 10(16), 1883; https://doi.org/10.3390/electronics10161883 - 5 Aug 2021

Cited by 8 | Viewed by 3472

Abstract

Semantic information usually contains a description of the environment content, which enables mobile robot to understand the environment and improves its ability to interact with the environment. In high-level human–computer interaction application, the Simultaneous Localization and Mapping (SLAM) system not only needs higher [...] Read more.

Semantic information usually contains a description of the environment content, which enables mobile robot to understand the environment and improves its ability to interact with the environment. In high-level human–computer interaction application, the Simultaneous Localization and Mapping (SLAM) system not only needs higher accuracy and robustness, but also has the ability to construct a static semantic map of the environment. However, traditional visual SLAM lacks semantic information. Furthermore, in an actual scene, dynamic objects will reduce the system performance and also generate redundancy when constructing map. these all directly affect the robot’s ability to perceive and understand the surrounding environment. Based on ORB-SLAM3, this article proposes a new Algorithm that uses semantic information and the global dense optical flow as constraints to generate dynamic-static mask and eliminate dynamic objects. then, to further construct a static 3D semantic map under indoor dynamic environments, a fusion of 2D semantic information and 3D point cloud is carried out. the experimental results on different types of dataset sequences show that, compared with original ORB-SLAM3, both Absolute Pose Error (APE) and Relative Pose Error (RPE) have been ameliorated to varying degrees, especially on freiburg3-walking-xyz, the APE reduced by 97.78% from the original average value of 0.523, and RPE reduced by 52.33% from the original average value of 0.0193. Compared with DS-SLAM and DynaSLAM, our system improves real-time performance while ensuring accuracy and robustness. Meanwhile, the expected map with environmental semantic information is built, and the map redundancy caused by dynamic objects is successfully reduced. the test results in real scenes further demonstrate the effect of constructing static semantic maps and prove the effectiveness of our Algorithm. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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20 pages, 3454 KB

Open AccessArticle

Intelligent Multi-Robot System for Collaborative Object Transportation Tasks in Rough Terrains

by Daegyun Choi and Donghoon Kim

Electronics 2021, 10(12), 1499; https://doi.org/10.3390/electronics10121499 - 21 Jun 2021

Cited by 10 | Viewed by 3928

Abstract

Human missions on other planets require constructing outposts and infrastructures, and one may need to consider relocating such large objects according to changes in mission spots. A multi-robot system would be a good option for such a transportation task because it can carry [...] Read more.

Human missions on other planets require constructing outposts and infrastructures, and one may need to consider relocating such large objects according to changes in mission spots. A multi-robot system would be a good option for such a transportation task because it can carry massive objects and provide better system reliability and redundancy when compared to a single robot system. This paper proposes an intelligent and decentralized approach for the multi-robot system using a genetic fuzzy system to perform an object transportation mission that not only minimizes the total travel distance of the multi-robot system but also guarantees the stability of the whole system in a rough terrain environment. The proposed fuzzy inference system determines the multi-robot system’s input for transporting an object to a target position and is tuned in the training process by a genetic algorithm with an artificially generated structured environment employing multiple scenarios. It validates the optimality of the proposed approach by comparing the training results with the results obtained by solving the formulated optimal control problem subject to path inequality constraints. It highlights the performance of the proposed approach by applying the trained fuzzy inference systems to operate the multi-robot system in unstructured environments. Full article

(This article belongs to the Special Issue Guidance, Navigation, and Fault-Tolerant Control of Autonomous Systems)

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