Path planning in complex 3D environments using a probabilistic roadmap method

This paper presents a 3D path planning algorithm for an unmanned aerial vehicle （UAV） in complex environments. In this algorithm, the environments are divided into voxels by octree algorithm. In order to satisfy the safety requirement of the UAV, free space is represented by free voxels, which have enough space margin for the UAV to pass through. A bounding box array is created in the whole 3D space to evaluate the free voxel connectivity. The probabilistic roadmap method （PRM） is improved by random sampling in the bounding box array to ensure a more efficient distribution of roadmap nodes in 3D space. According to the connectivity evaluation, the roadmap is used to plan a feasible path by using A＊ algorithm. Experimental results indicate that the proposed algorithm is valid in complex 3D environments.     

用于UAV视觉导航的跑道检测与跟踪

跑道检测与跟踪是UAV视觉导航研究的重点内容.针对UAV着陆过程中跑道变化情况,提出一种新的方法,利用单目视觉信息,基于距离跑道的远近不同采用不同的策略实现跑道检测与跟踪,帮助UAV自主降落在安全区域.当距离较远时,利用地平线检测和模板匹配的方法对跑道进行定位;结合模板更新策略实现跑道跟踪;当距离较近时,在融合远距离跑道方位信息的基础上利用改进型Canny算子和Hough变换对跑道边缘进行更精确的描述.实验结果表明,利用该方法可以有效地对跑道进行检测和跟踪,并且具有较快的处理速度.     

基于DWILS的无人机着陆导引与控制仿真

导引和控制技术是大型无人机实现自动着陆的两项关键技术。针对分米波仪表着陆系统（DWILS）的无人机着陆导引与控制技术的仿真验证,为了提高导引的可靠性,给出了基于DWILS的无人机着陆地面仿真系统的结构,着陆导引仿真设备,根据DWILS的工作原理给出了导引信号的计算公式,同时设计了着陆控制器。根据导引设备的原理建立了基于DWILS的无人机着陆导引与控制仿真系统模型,并进行仿真验证。仿真结果表明,基于DWILS的导引方式满足无人机着陆导引的需要,设计的着陆控制器具有较好的控制效果。     

一种基于PSO的多UAV协同航迹规划方法

本文针对多无人飞行器(UAV)协同执行任务的应用场景,提出了一种综合考虑任务分配和航迹规划因素的航迹规划算法。该算法借鉴微粒群算法(PSO)的思想,采用新的编码方式和优化策略。仿真实验验证了算法的有效性。     

无人机遥控指令加密方式的研究

介绍了无人机遥控指令的特点,提出对遥控指令进行加密的方式以实现更高的安全性;设计了基于序列密码的一次一密加密方案,通过分析遥控指令加解密的过程,给出了一种遥控指令的帧结构,更好地满足遥控指令高安全性、高可靠性的需求。     

基于HLA／RTI的无人机作战仿真系统框架设计

无人机系统与其他武器系统的联合训练是一项重要课题。在对无人机系统的进行深入分析的基础上,设计了基于HLA／RTI的无人机作战仿真系统的基本框架,实现了与炮兵C^3I系统的联合仿真,建立了无人机作战仿真系统的概念模型,为下一步仿真系统的开发实现奠定了基础。     

低成本的UTRV三维可视化仿真测试系统设计

相对于常规飞行器,倾转旋翼飞行器原本就对飞控系统有着更高的要求,而其无人化后的产品UTRV(无人倾转旋翼飞行器)对此的需要还要更上一层楼.为了满足开发UTRV飞控系统的需要,有必要开发更加方便的飞控系统仿真测试环境.使用现有货架商品构建了一套UTRV三维可视化仿真测试系统.系统内含可调整的UTRV全飞行包线非线性气动模型,用于提供控制律开发和动态仿真;系统可以方便的替换飞控模块程序进行仿真实验,以此验证控制律;同时,仿真实验全程数据以直观的实时三维视觉仿真方式显示,有利于发现飞控系统缺陷.使用货架商品还大大降低了成本,非常适合中小研究所和大学使用.     

A backstepping controller for path‐tracking of an underactuated autonomous airship

In this paper we propose a nonlinear control approach for the path‐tracking of an autonomous underactuated airship. A backstepping controller is designed from the airship nonlinear dynamic model including wind disturbances, and further enhanced to consider actuators saturation. Control implementation issues related to airship underactuation are also addressed, namely control allocation and an attitude reference shaping to obtain a faster error correction with smoother input requests. The results obtained demonstrate the capacity of an underactuated unmanned airship to execute a realistic mission including vertical take‐off and landing, stabilization and path‐tracking, in the presence of wind disturbances, with a single robust control law. Copyright © 2008 John Wiley & Sons, Ltd.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

无人机遥感影像获取及后续处理探讨

作为卫星遥感和航空遥感的有益补充,无人机航空遥感系统获取遥感影像具有多种特性。通过4次无人机航拍试验,根据所获取的遥感影像和飞行辅助数据,对航拍数据进行拼接。从航拍的多个方面对飞行试验以及实验成果进行了质量评价。并提出了无人机应用于航拍时存在的问题及一些改进方法。