Trust-Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial-Magnetic Sensor
文献类型：期刊论文
| 作者 | Jia, Nan2,3; Wei, Zongkang3; Li, Bangyu1
|
| 刊名 | DRONES
 |
| 出版日期 | 2023-06-01 |
| 卷号 | 7期号:6页码:25 |
| 关键词 | onboard sensor fusion nonlinear optimization visual measurement drone orientation estimator |
| DOI | 10.3390/drones7060351 |
| 通讯作者 | Li, Bangyu(bangyu.li@ia.ac.cn) |
| 英文摘要 | This paper proposes a novel robust orientation estimator to enhance the accuracy and robustness of orientation estimation for inertial-magnetic sensors of the small consumer-grade drones. The proposed estimator utilizes a trust-region strategy within a nonlinear optimization framework, transforming the orientation fusion problem into a nonlinear optimization problem based on the maximum likelihood principle. The proposed estimator employs a trust-region Dogleg gradient descent strategy to optimize orientation precision and incorporates a Huber robust kernel to minimize interference caused by acceleration during the maneuvering process of the drone. In addition, a novel method for evaluating the performance of orientation estimators is also presented based on visuals. The proposed method consists of two parts: offline calibration of the basic cube using Augmented Reality University of Cordoba (ArUco) markers and online orientation measurement of the sensor carrier using a nonlinear optimization solver. The proposed measurement method's accuracy and the proposed estimator's performance are evaluated under low-dynamic (rotation) and high-dynamic (shake) conditions in the experiment. The experimental findings indicate that the proposed measurement method obtains an average re-projection error of less than 0.1 pixels. The proposed estimator has the lowest average orientation error compared to conventional orientation estimation algorithms. Despite the time-consuming nature of the proposed estimator, it exhibits greater robustness and precision, particularly in highly dynamic environments. |
| WOS关键词 | ROBUST |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:001017113400001 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53588]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 通讯作者 | Li, Bangyu |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100098, Peoples R China 2.China Acad Launch Vehicle Technol, Beijing 100076, Peoples R China 3.Beijing Inst Aerosp Control Device, Beijing 100854, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jia, Nan,Wei, Zongkang,Li, Bangyu. Trust-Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial-Magnetic Sensor[J]. DRONES,2023,7(6):25. |
| APA | Jia, Nan,Wei, Zongkang,&Li, Bangyu.(2023).Trust-Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial-Magnetic Sensor.DRONES,7(6),25. |
| MLA | Jia, Nan,et al."Trust-Region Nonlinear Optimization Algorithm for Orientation Estimator and Visual Measurement of Inertial-Magnetic Sensor".DRONES 7.6(2023):25. |
入库方式： OAI收割
来源：自动化研究所
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