Visual Navigation System for Maritime UAV Autonomous Landing
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- 英文论文题名：Visual Navigation System for Maritime UAV Autonomous Landing
- 论文作者：YUAN Haiwen ; XIAO Changshi ; WEN Yuanqiao ; WU Xiaochun ; ZHOU Chunhui
- 英文论文作者：YUAN Haiwen ; XIAO Changshi ; WEN Yuanqiao ; WU Xiaochun ; ZHOU Chunhui ; School of Navigation ; Wuhan University of Technology ; Hubei Inland Shipping Technology Key Laboratory
- 年：2015
- 作者机构：School of Navigation,Wuhan University of Technology;Hubei Inland Shipping Technology Key Laboratory;
- 英文论文关键词：UAV ; visual navigation ; frequency feature ; particle filtering
- 会议召开时间：2015-09-01
- 会议录名称：中国航海科技优秀论文集（2014）
- 语种：英文
- 分类号：V279;V249.3
- 学会代码：PJJY
- 学会名称：上海浦江教育出版社有限公司
- 页数：18
- 文件大小：1702k
- 原文格式：O
摘要
In spite of a success in maritime UAVs' application,there still hold a challenge on real-time and accurate state estimation during small UAV autonomous landing.This paper presents a significant navigation system based on vision technology that could measure maritime UAV's position and attitude without other onboard sensors.In the system,a robust algorithm is proposed to detect special markers(LEDs owning fixed flicker frequency) mounted around maritime UAV well,which could recognize target by its frequency feature from complicated background.In actual process,there exist vast noises,i.e.Gaussian noise.Hence,Particle Filtering is suggested to filter the useful information from mixed observations and smooth the entire UAV's flight trajectory.Using the method mainly,we have expected to improve maritime UAV's autonomy and make it have the ability of take-off or landing on special‘habitat' for a temporary rest where the vehicle could recharge or avoid dangers,like bad weather.Finally,the visual navigation system for UAV is tested with our small quadrotor that has good performance on mobility,and results show it works well.
In spite of a success in maritime UAVs' application,there still hold a challenge on real-time and accurate state estimation during small UAV autonomous landing.This paper presents a significant navigation system based on vision technology that could measure maritime UAV's position and attitude without other onboard sensors.In the system,a robust algorithm is proposed to detect special markers(LEDs owning fixed flicker frequency) mounted around maritime UAV well,which could recognize target by its frequency feature from complicated background.In actual process,there exist vast noises,i.e.Gaussian noise.Hence,Particle Filtering is suggested to filter the useful information from mixed observations and smooth the entire UAV's flight trajectory.Using the method mainly,we have expected to improve maritime UAV's autonomy and make it have the ability of take-off or landing on special‘habitat' for a temporary rest where the vehicle could recharge or avoid dangers,like bad weather.Finally,the visual navigation system for UAV is tested with our small quadrotor that has good performance on mobility,and results show it works well.
In spite of a success in maritime UAVs' application,there still hold a challenge on real-time and accurate state estimation during small UAV autonomous landing.This paper presents a significant navigation system based on vision technology that could measure maritime UAV's position and attitude without other onboard sensors.In the system,a robust algorithm is proposed to detect special markers(LEDs owning fixed flicker frequency) mounted around maritime UAV well,which could recognize target by its frequency feature from complicated background.In actual process,there exist vast noises,i.e.Gaussian noise.Hence,Particle Filtering is suggested to filter the useful information from mixed observations and smooth the entire UAV's flight trajectory.Using the method mainly,we have expected to improve maritime UAV's autonomy and make it have the ability of take-off or landing on special‘habitat' for a temporary rest where the vehicle could recharge or avoid dangers,like bad weather.Finally,the visual navigation system for UAV is tested with our small quadrotor that has good performance on mobility,and results show it works well.
引文
[1]J.How,B.Bethke,A Frank,et al.Real-time Indoor Autonomous Vehicle Test Environment[J].IEEE Control Systems Magazine,2008.
[2]Sankalp Arora,Sezal Jain,Sebastian Scherer,et al.Infrastructure-free Shipdeck Tracking for Autonomous Landing[C].2013 IEEE International Conference on Robotics and Automation,May,2013.
[3]Sarioalli Saripalli,Montgomery J.F.,Sukhatme G.S..Visually Guided Landing of an Unmanned Aerial Vehicle[J].IEEE Transcation Robot Autonomous,2003:371-380.
[4]Jose Luis Sanchez-Lopez,Jesus Pestana,Srikanth Saripalli,et al.An Approach Toward Visual Autonomous Ship Board Landing of a VTOL UAV[J].Journal of Intelligence Robot System,2014:113-127.
[5]Karl E.Wenzel,Andreas Masselli,Andreas Zell.Automatic Take Off,Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle[J].Journal of Intelligent&Robotic Systems,2011:221-238.
[6]Bruno Herisse,Tarek Hamel,Robert Mahony,et al.Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow[J].IEEE Transactions on Robotics,2012,28(1):77-89.
[7]J.E.Gomez-Balderas,G.Flores,L.R.Garcia Carrillo,et al.Tracking a Ground Moving Target with a Quadrotor Using Switching Control[J].Journal of Intelligent Robot System,2012.
[8]XU Guili,QI Xiaopeng,ZENG Qinghua,et al.Use of Land's Coorperative Object to Estimate UAV's Pose for Autonomous Landing[J].Chinese Journal of Aeronautics,2013:1498-1 505.
[9]YANG Shaowu,Sebastian A Scherer,Konstantin Schauwecker,et al.Autonomous Landing of MAVs on an Arbitrarily Textured Landing Site Using Onboard Monocular Vision[J].Journal of Intelligent System,2014:27-43.
[2]Sankalp Arora,Sezal Jain,Sebastian Scherer,et al.Infrastructure-free Shipdeck Tracking for Autonomous Landing[C].2013 IEEE International Conference on Robotics and Automation,May,2013.
[3]Sarioalli Saripalli,Montgomery J.F.,Sukhatme G.S..Visually Guided Landing of an Unmanned Aerial Vehicle[J].IEEE Transcation Robot Autonomous,2003:371-380.
[4]Jose Luis Sanchez-Lopez,Jesus Pestana,Srikanth Saripalli,et al.An Approach Toward Visual Autonomous Ship Board Landing of a VTOL UAV[J].Journal of Intelligence Robot System,2014:113-127.
[5]Karl E.Wenzel,Andreas Masselli,Andreas Zell.Automatic Take Off,Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle[J].Journal of Intelligent&Robotic Systems,2011:221-238.
[6]Bruno Herisse,Tarek Hamel,Robert Mahony,et al.Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow[J].IEEE Transactions on Robotics,2012,28(1):77-89.
[7]J.E.Gomez-Balderas,G.Flores,L.R.Garcia Carrillo,et al.Tracking a Ground Moving Target with a Quadrotor Using Switching Control[J].Journal of Intelligent Robot System,2012.
[8]XU Guili,QI Xiaopeng,ZENG Qinghua,et al.Use of Land's Coorperative Object to Estimate UAV's Pose for Autonomous Landing[J].Chinese Journal of Aeronautics,2013:1498-1 505.
[9]YANG Shaowu,Sebastian A Scherer,Konstantin Schauwecker,et al.Autonomous Landing of MAVs on an Arbitrarily Textured Landing Site Using Onboard Monocular Vision[J].Journal of Intelligent System,2014:27-43.