Selecting the image elements of earth and moon centers as observed quantity , measurement noise model and observed equations of autonomous navigation system are built up . the spacecraft orbit is determined by using the recursive weighted least square based on ud factorization 在奔选取地心和月心像素作为观测量,建立了符合实际情况的量测噪声模型和自主导航系统的观测方程,并利用基于ud分解的递推加权最小二乘算法估计了奔月探测器的轨道参数。
In deep space exploration missions , autonomous navigation technology is very important , and in this paper , we do some research into the autonomous navigation schemes of encountering small celestial bodies . it is mainly described as the follows : firstly , by analyzing the orbit characteristics and task requirements in encounter , the simplified orbit dynamic model for the deep space probe is built up , and whether the corresponding model error that meets the demanding of autonomous navigation task is validated 在深空探测任务中,自主导航技术是十分重要的,本文对交会小行星的自主导航方法进行研究,主要内容包括:首先,分析交会小行星的轨道特性及任务需求,建立简化的深空探测器轨道动力学模型,并验证了简化模型的误差能否满足自主导航任务的需求。
By analyzing the method mathematically , the basic architecture of autonomous navigation system of constellation was designed . and also , the orbit determination method using whole net , the robust estimation method , and the integrated navigation method based on inter - satellite measurement and stellar refraction were studied emphatically 通过对该方法进行数学分析,设计了星座自主导航系统的基本框架,并重点研究了整网定轨方法、抗差估计方法和基于星间观测+星光折射的组合导航方法。
Supported by the national natural science foundation of china ( nsfc ) 2 , the research topic of this paper has been focused on reinforcement learning and its applications in mobile robot navigation . one part of the main contents in this paper is the generalization methods for reinforcement learning in solving markov decision problems with continuous states and actions . another part of the main contents is the applications of reinforcement learning methods in the optimization of the path tracking controllers and the autonomous navigation controllers for mobile robots 本文在国家自然科学基金项目“增强学习泛化方法研究及其在移动机器人导航中的应用”的资助下，以增强学习及其在移动机器人导航控制中的应用为研究内容，重点研究了增强学习在求解连续状态和行为空间markov决策问题时的泛化( generalization )方法，并针对移动机器人在未知环境中的自主导航和路径跟踪控制器的优化设计问题，研究了增强学习在上述领域中的应用。
On the basis of investigation and synthesis of the relative theory and key technology on the topological structure of locomotion , control system architecture , maneuverability , trafficability , the integration of exact mechanical engineering , net - based communication and sensor technology , an innovative robot with reconfiguration and biomimetic characteristics has been developed for 863 program of china ? study on autonomous navigation system for intelligence mobile robot in unknown environment 本文针对“未知环境中自主工作智能移动机器人导航系统研究”的国家863项目,在综述国内外关于移动机器人走行部拓扑结构、控制体系、机动性和通过性等移动机器人的相关理论和关键技术的基础上,综合利用精密机械、网络通信、传感技术等学科的技术,研制开发出一种多机动模式可重构移动机器人。
The research on autonomous navigation and orbital keeping technology of geosynchronous satellites : selecting position vector in the inertia space and longitude , latitude , radial errors in the hill equation as state variables , the precision of orbit determination caused by track dynamic model error , sampling period , and sensor measurement and install error is analyzed 同步卫星自主导航与轨道保持技术研究：分别选取惯性空间位置矢量和采用hill方程表示的经、纬、向径误差作为状态量，分析轨道动力学模型误差、采样周期以及敏感器测量、安装等误差对定轨精度的影响。
Autonomous navigation system is a important part of its , it can help to get safe , and smooth drive , and can ease or avoid unwanted traffic jam , and also can make the movement and usage of vehicle more convenient . it can facilitate the vehicle consumption and the environment inprovement 自主式导航系统是智能交通系统的一个重要组成部分，这一智能系统不仅能实现安全、通畅的驾驶，缓解或避免多余的交通堵塞，而且能使车辆的移动和使用变得更加方便，促进了汽车消费和使用环境的完善。
According to the requirement under dynamic structured environment of research projects , the main purpose of this thesis is to accomplish an autonomous navigation experiment system for mobile robot on which to study environment perception , behavior planning , motion control , knowledge learning and multi - robot cooperation strategy and its algorithm 为此引入了在不确定性知识获取领域具有独特优势的粗糙集理论,以涉及的动态结构化环境为背景基础,建立一个移动机器人基本实验系统,研究自主导航中环境感知、行为决策、知识学习及多机器人协作等方面的相关策略与实现算法。
This paper , reviews the development history of autonomous navigation system - navistar 2001 , and illustrated that it has great importance to the modernization of traffic of our country to research and develop self - designed navigation system . at the same time , this paper give the prototype of navigation system navi - star2001 as a example and discusses specially several aspest of the research and development : 1 . the structure design and module function assignmeng of the system ; 2 . the realiztion method of the module mapdisplay , routecalculate and routeguide ; 3 . the design of properly structured data storage structure which can reflect the complex road network in reality ; 4 同时，本文还以自主式导航系统原型navi - star2001为例子，重点论述了我们在进行navi - star2001开发过程中所作的下面几个工作： 1 、 navi - star2001的系统结构设计及模块划分，各模块的功能分配，这部分工作从整体上对自主式导航系统进行了规划，对于自主式导航系统这样复杂系统的开发工作来说，具有重要意义； 2 、地图显示、路径规划、路径引导的实现方法、关键技术； 3 、设计一个结构合理，能够准确反映真实道路网络的数据存储结构，按照这个存储结构组织起来的道路网数据构成了系统中导航功能的数据基础； 4 、设计车辆定位模块中的道路分块索引技术、 gps数据的接收处理方法及三段式道路匹配算法，这三部分紧密配合实现了移动车辆实时准确的定位。
Finally , based on the observability analysis and error analysis , two autonomous navigation schemes for encounter phase are respectively proposed in detail . monte carlo simulations are done for the two schemes . by analyzing and comparing the simulation results , we can get the conclusion that , under the accuracy conditions provided by the instruments in existence , the position estimation accuracy for probe encountering object celestial body is 0 . 42km and 0 . 04km , which demonstrate the feasibility of the two navigation schemes 最后,在可观性分析和误差分析的基础上,分别给出基于图像测量的自主导航方法和基于视线方向及夹角测量的自主导航方法,并对这两种方法进行蒙特卡罗数值仿真,通过对仿真结果的分析和比较,在现有仪器的测量精度下,探测器在与目标天体交会时刻的位置估计精度分别是0 . 42km和0 . 04km ,由此表明两种自主导航方案都是可行的。
