Autonomous landing has become a core technology of unmanned aerial vehicle(UAV)guidance,navigation,and control system in recent years.This paper discusses the vision⁃based relative position and attitude estimation bet...Autonomous landing has become a core technology of unmanned aerial vehicle(UAV)guidance,navigation,and control system in recent years.This paper discusses the vision⁃based relative position and attitude estimation between fixed⁃wing UAV and runway,which is a key issue in autonomous landing.Images taken by a airborne camera was used and a runway detection method based on long⁃line feature and gradient projection is proposed,which solved the problem that the traditional Hough transform requires much calculation time and easily detects end points by mistake.Under the premise of the known width and length of the runway,position and attitude estimation algorithm used the image processing results and adopted an estimation algorithm based on orthogonal iteration.The method took the objective space error as error function and effectively improved the accuracy of linear algorithm through iteration.The experimental results verified the effectiveness of the proposed algorithms.展开更多
The lack of autonomous take-off and landing capabilities of bird-like flapping-wing aerial vehicles(BFAVs)seriously restricts their further development and application.Thus,combined with the current research results o...The lack of autonomous take-off and landing capabilities of bird-like flapping-wing aerial vehicles(BFAVs)seriously restricts their further development and application.Thus,combined with the current research results on the autonomous take-off and landing technology of unmanned aerial vehicles,four types of technologies are studied,including jumping take-off and landing technology,taxiing take-off and landing technology,gliding take-off and landing technology,and vertical take-off and landing(VTOL)technology.Based on the analytic hierarchy process(AHP)-comprehensive evaluation method,a fuzzy comprehensive evaluation model for the autonomous take-off and landing scheme of a BFAV is established,and four schemes are evaluated concretely.The results show that under the existing technical conditions,the hybrid layout VTOL scheme is the best.Furthermore,the detailed design and development of the prototype of a BFAV with a four-rotor hybrid layout are carried out,and the vehicle performance is tested.The results prove that through the four-rotor hybrid layout design,the BFAV has good autonomous take-off and landing abilities.The power consumption analysis shows that for a fixed-point reconnaissance mission,when the mission radius is less than 3.38 km,the VTOL type exhibits longer mission duration than the hand-launched type.展开更多
In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding...In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding scenarios.It bridges vision and control for ground‐based vision guidance systems having the multi‐modal data obtained by diverse sensors and pushes forward the development of computer vision and autopilot algorithms tar-geted at visually assisted landing of one fixed‐wing vehicle.The dataset is composed of sequential stereo images and synchronised sensor data,in terms of the flying vehicle pose and Pan‐Tilt Unit angles,simulated in various climate conditions and landing scenarios.Since real‐world automated landing data is very limited,the proposed dataset provides the necessary foundation for vision‐based tasks such as flying vehicle detection,key point localisation,pose estimation etc.Hereafter,in addition to providing plentiful and scene‐rich data,the developed dataset covers high‐risk scenarios that are hardly accessible in reality.The dataset is also open and available at https://github.com/micros‐uav/micros_air2land as well.展开更多
基金Sponsored by the Fundamental Research Funds for the Central Universities(Grant No.NP2019105)the Funds from the Post⁃graduate Creative Base in Nanjing University of Aeronautics and Astronautics(Grant No.kfjj20190716).
文摘Autonomous landing has become a core technology of unmanned aerial vehicle(UAV)guidance,navigation,and control system in recent years.This paper discusses the vision⁃based relative position and attitude estimation between fixed⁃wing UAV and runway,which is a key issue in autonomous landing.Images taken by a airborne camera was used and a runway detection method based on long⁃line feature and gradient projection is proposed,which solved the problem that the traditional Hough transform requires much calculation time and easily detects end points by mistake.Under the premise of the known width and length of the runway,position and attitude estimation algorithm used the image processing results and adopted an estimation algorithm based on orthogonal iteration.The method took the objective space error as error function and effectively improved the accuracy of linear algorithm through iteration.The experimental results verified the effectiveness of the proposed algorithms.
基金supported in part by the National Key Research and Development Program of China(No.2017YFB1300102)the Key R&D Program in Shaanxi Province of China(No.2020ZDLGY06-05,No 2021ZDLGY09-10)the National Natural Science Foundation of China(No.11902103,No.11872314).
文摘The lack of autonomous take-off and landing capabilities of bird-like flapping-wing aerial vehicles(BFAVs)seriously restricts their further development and application.Thus,combined with the current research results on the autonomous take-off and landing technology of unmanned aerial vehicles,four types of technologies are studied,including jumping take-off and landing technology,taxiing take-off and landing technology,gliding take-off and landing technology,and vertical take-off and landing(VTOL)technology.Based on the analytic hierarchy process(AHP)-comprehensive evaluation method,a fuzzy comprehensive evaluation model for the autonomous take-off and landing scheme of a BFAV is established,and four schemes are evaluated concretely.The results show that under the existing technical conditions,the hybrid layout VTOL scheme is the best.Furthermore,the detailed design and development of the prototype of a BFAV with a four-rotor hybrid layout are carried out,and the vehicle performance is tested.The results prove that through the four-rotor hybrid layout design,the BFAV has good autonomous take-off and landing abilities.The power consumption analysis shows that for a fixed-point reconnaissance mission,when the mission radius is less than 3.38 km,the VTOL type exhibits longer mission duration than the hand-launched type.
文摘In this paper,a novel deep learning dataset,called Air2Land,is presented for advancing the state‐of‐the‐art object detection and pose estimation in the context of one fixed‐wing unmanned aerial vehicle autolanding scenarios.It bridges vision and control for ground‐based vision guidance systems having the multi‐modal data obtained by diverse sensors and pushes forward the development of computer vision and autopilot algorithms tar-geted at visually assisted landing of one fixed‐wing vehicle.The dataset is composed of sequential stereo images and synchronised sensor data,in terms of the flying vehicle pose and Pan‐Tilt Unit angles,simulated in various climate conditions and landing scenarios.Since real‐world automated landing data is very limited,the proposed dataset provides the necessary foundation for vision‐based tasks such as flying vehicle detection,key point localisation,pose estimation etc.Hereafter,in addition to providing plentiful and scene‐rich data,the developed dataset covers high‐risk scenarios that are hardly accessible in reality.The dataset is also open and available at https://github.com/micros‐uav/micros_air2land as well.