On-board visual navigation system for unmanned aerial vehicles autonomous aerial refueling

Xu, Yan; Duan, Haibin; Li, Cong; Deng, Yimin

doi:10.1177/0954410017748182

Cited by 7 publications

(7 citation statements)

References 28 publications

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“…Once the UA and the tanker are in closer proximity, as defined by the astern position (10 to 15 ft. aft of the drogue), it is necessary to transition to CV to provide guidance information to the GNC for the placement of the probe tip into the drogue coupler. Given the limitations associated with DGPS, demonstrations to date [ 37 , 38 , 89 ], and academic research on the A3R portion of a mission, a pivot to a CV solution is most appropriate for the final engagement [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. As the aircraft moves to an astern position ( Figure 4 ) using an INS/GNSS/DGPS-derived position solution, the camera system installed on the UA can begin to detect objects within the domain.…”

Section: Review Of Sensor Requirements For A3rmentioning

confidence: 99%

“…While no UA currently exists in the Department of Defense (DoD) that has been authorized to conduct the A3R portion of a mission, the task has been accomplished on both crewed aircraft and UA as a demonstration. Extensive research has been conducted on the algorithms required to complete the task from as a receiver, specifically the computer vision (CV) portion of A3R [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. As ranges increase for UAs to travel to complete the mission, the demand for a UA capable of A3R will continue to increase as well.…”

Section: Introductionmentioning

confidence: 99%

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Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft

Parry

Hubbard

2023

Sensors

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As technologies advance and applications for uncrewed aircraft increase, the capability to conduct automated air-to-air refueling becomes increasingly important. This paper provides a review of required sensors to enable automated air-to-air refueling for an uncrewed aircraft, as well as a review of published research on the topic. Automated air-to-air refueling of uncrewed aircraft eliminates the need for ground infrastructure for intermediate refueling, as well as the need for on-site personnel. Automated air-to-air refueling potentially supports civilian applications such as weather monitoring, surveillance for wildfires, search and rescue, and emergency response, especially when airfields are not available due to natural disasters. For military applications, to enable the Air Wing of the Future to strike at the ranges required for the mission, both crewed and uncrewed aircraft must be capable of air-to-air refueling. To cover the sensors required to complete automated air-to-air refueling, a brief history of air-to-air refueling is presented, followed by a concept of employment for uncrewed aircraft refueling, and finally, a review of the sensors required to complete the different phases of automated air-to-air refueling. To complete uncrewed aircraft refueling, the uncrewed receiver aircraft must have the sensors required to establish communication, determine relative position, decrease separation to astern position, transition to computer vision, position keep during refueling, and separate from the tanker aircraft upon completion of refueling. This paper provides a review of the twelve sensors that would enable the uncrewed aircraft to complete the seven tasks required for automated air-to-air refueling.

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Section: Review Of Sensor Requirements For A3rmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft

Parry

Hubbard

2023

Sensors

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“…the length of Semi − minor axis the length of Semi − major axis (13) Each indicator has its shortcomings and false extractions cannot be completely excluded when the indicators are used alone [48]. Therefore, we set a score of ratios.…”

Section: ) Arc Extraction and Constraintmentioning

confidence: 99%

“…Jing et al [10] and Chen et al [11] presented the measurement methods of the drogue's pose, which are vision methods based on dual-quaternion and infrared vision sensor, respectively. Xu et al [13] designed a binocular vision-based UAV autonomous aerial refueling platform for AAR and obtained the poses using the known geometrical relationship of 7 points. Johnson et al [14] designed an extended Kalman filter to combine the stereo camera system and inertial navigation for automated aerial refueling.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Measuring Drogue-UAV Relative Pose in Autonomous Aerial Refueling Based on Monocular Vision

Zhao

Liu

et al. 2019

IEEE Access

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The key to the docking phase of autonomous aerial refueling missions is the relative pose measurement between the drogue and unmanned aerial vehicles. A novel measurement method for drogue-UAV (unmanned aerial vehicle) relative poses based on monocular vision is proposed in this paper. An adaptive arc-level structural feature extraction algorithm is applied to obtain the features that can be used for the measurements. In this algorithm, the projection of the end plane of the drogue in the image plane is accurately extracted based on an extraction quality metric. The projection contour and centroid of the internal black part of the drogue form the structural feature for the measurements. A robust pose estimation algorithm is presented to estimate the relative pose between the drogue and the UAV. The pose can be solved using a cone that is composed of the optical center of the camera and the structural feature. A Kalman filter is then applied to robustly estimate the pose of the drogue. A simulation and ground experiment are used to verify the robustness and effectiveness of the proposed method, which achieves good performance compared with other methods.

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“…Unmanned aerial vehicles (UAVs) have been successfully applied in military and civilian areas. 1,2 The distinguishing feature of UAVs is “unmanned,” that is, no pilot has direct control of the UAVs, so they rely more on navigation technology. 3,4 Unmanned aerial vehicles often carry out complex missions in harsh environments, such as electromagnetic fields, urban canyons, and so on, which will affect the performance of navigation systems.…”

Section: Introductionmentioning

confidence: 99%

A novel interactive robust filter algorithm for GNSS/SINS integrated navigation

Zhao

Zeng

Liu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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To solve the problem of Kalman filter (KF) performance degradation in unmanned aerial vehicle (UAV) applications, a novel interactive robust filter algorithm for GNSS/SINS integrated navigation is proposed in this paper. The strong tracking Kalman filter (STKF) is robust to uncertain system noise but is ineffective to abnormal measurement information. Based on the same performance index function with STKF, a measurement noise covariance matrix adaptive Kalman filter algorithm (MAKF) is presented, but it is ineffective under uncertain system noise. Furthermore, the interactive robust filter algorithm based on STKF and MAKF (IF-STKF-MAKF) is proposed, given the complementary characteristics of the above two filter algorithms. The STKF and MAKF operate in parallel based on the same system model. The filter probability of each filter is updated according to the likelihood function to perform output fusion and input interaction. The simulation and experiment results demonstrate that the IF-STKF-MAKF is effective and can achieve high estimation accuracy under both system noise anomalies and measurement information anomalies. In the vehicle experiment, the position accuracy of the proposed IF-STKF-MAKF method has been improved by more than 30% compared with KF, STKF, and MAKF. This method can also be extended to land vehicles, mobile robots, etc.

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On-board visual navigation system for unmanned aerial vehicles autonomous aerial refueling

Cited by 7 publications

References 28 publications

Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft

Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft

A Novel Method for Measuring Drogue-UAV Relative Pose in Autonomous Aerial Refueling Based on Monocular Vision

A novel interactive robust filter algorithm for GNSS/SINS integrated navigation

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