A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots
IMUs (inertial measurement units) and cameras are popular sensors for autonomous localization due to their convenient integration. This article proposes a collaborative localization method, the CICEKF (collaborative IMU-aided camera extended Kalman filter), with a loosely coupled and two-step struct...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/10/3086 |
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| author | Cheng Liu Tao Wang Zhi Li Shu Li Peng Tian |
| author_facet | Cheng Liu Tao Wang Zhi Li Shu Li Peng Tian |
| author_sort | Cheng Liu |
| collection | DOAJ |
| description | IMUs (inertial measurement units) and cameras are popular sensors for autonomous localization due to their convenient integration. This article proposes a collaborative localization method, the CICEKF (collaborative IMU-aided camera extended Kalman filter), with a loosely coupled and two-step structure for the autonomous locomotion estimation of collaborative robots. The first step is for single-robot localization estimation, fusing and connecting the IMU and visual measurement data on the velocity level, which can improve the robustness and adaptability of different visual measurement approaches without redesigning the visual optimization process. The second step is for estimating the relative configuration of multiple robots, which further fuses the individual motion information to estimate the relative translation and rotation reliably. The simulation and experiment demonstrate that both steps of the filter are capable of accomplishing locomotion estimation missions, standalone or collaboratively. |
| format | Article |
| id | doaj-art-4b6564dec89b4fdcaf845b048d2c2fde |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-4b6564dec89b4fdcaf845b048d2c2fde2025-08-20T02:33:48ZengMDPI AGSensors1424-82202025-05-012510308610.3390/s25103086A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous RobotsCheng Liu0Tao Wang1Zhi Li2Shu Li3Peng Tian4State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Electrical Engineering, Liaoning University of Technology, Jinzhou 121000, ChinaSchool of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 401100, ChinaIMUs (inertial measurement units) and cameras are popular sensors for autonomous localization due to their convenient integration. This article proposes a collaborative localization method, the CICEKF (collaborative IMU-aided camera extended Kalman filter), with a loosely coupled and two-step structure for the autonomous locomotion estimation of collaborative robots. The first step is for single-robot localization estimation, fusing and connecting the IMU and visual measurement data on the velocity level, which can improve the robustness and adaptability of different visual measurement approaches without redesigning the visual optimization process. The second step is for estimating the relative configuration of multiple robots, which further fuses the individual motion information to estimate the relative translation and rotation reliably. The simulation and experiment demonstrate that both steps of the filter are capable of accomplishing locomotion estimation missions, standalone or collaboratively.https://www.mdpi.com/1424-8220/25/10/3086loosely coupled autonomous localizationvisual–inertial odometrymultiple robots collaborative localizationdata fusion |
| spellingShingle | Cheng Liu Tao Wang Zhi Li Shu Li Peng Tian A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots Sensors loosely coupled autonomous localization visual–inertial odometry multiple robots collaborative localization data fusion |
| title | A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots |
| title_full | A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots |
| title_fullStr | A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots |
| title_full_unstemmed | A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots |
| title_short | A Novel Loosely Coupled Collaborative Localization Method Utilizing Integrated IMU-Aided Cameras for Multiple Autonomous Robots |
| title_sort | novel loosely coupled collaborative localization method utilizing integrated imu aided cameras for multiple autonomous robots |
| topic | loosely coupled autonomous localization visual–inertial odometry multiple robots collaborative localization data fusion |
| url | https://www.mdpi.com/1424-8220/25/10/3086 |
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