Mars Rover Autonomous Navigation

Autonomous navigation of a rover on Mars surface can improve very significantly the daily traverse, particularly when driving away from the lander, into unknown areas. The autonomous navigation process developed at CNES is based on stereo cameras perception, used to build a model of the environment and generate trajectories. Multiple perception merging with propagation of the locomotion and localization errors have been implemented. The algorithms developed for Mars exploration programs, the vision hardware, the validation tools, experimental platforms and results of evaluation are presented. Portability and the evaluation of computing resources for implementation on a Mars rover are also addressed. The results show that the implementation of autonomy requires only a very small amount of energy and computing time and that the rover capabilities are fully used, allowing a much longer daily traverse than what is enabled by purely ground-planned strategies.     

多传感器数据融合的智能电动车自主导航

以四轮驱动电动车为研究对象,将智能电动车上多种传感器所采集的信息进行处理与融合,实现校园环境里的自主行驶与导航.提出了在空旷路段和沿墙导航的控制决策,着重研究了沿墙算法和入弯算法,使智能电动车在不同的环境下可以有效地完成自主导航.实验结果表明:该导航控制策略和算法具有较高的可靠性.     

基于传感器信息的智能移动机器人导航评述

导航是研究智能移动机器人技术中的一个重要领域,对自主导航技术的关键问题——路径规划进行了评述。路径规划一般可分为基于模型的环境信息完全知道的全局路径规划和基于传感器的环境信息完全未知或部分未知的局部路径规划2种类型。分别对各种方法的发展现状进行了总结,指出了各种方法的优点和不足。     

Deliberative On-Line Local Path Planning for Autonomous Mobile Robots

This paper describes a method for local path planning for mobile robots that combines reactive obstacle avoidance with on-line local path planning. Our approach is different to other model-based navigation approaches since it integrates both global and local planning processes in the same architecture while other methods only combine global path planning with a reactive method to avoid non-modelled obstacles. Our local planning is only triggered when an unexpected obstacle is found and reactive navigation is not able to regain the initial path. A new trajectory is then calculated on-line using only proximity sensor information. This trajectory can be improved during the available time using an anytime algorithm. The proposed method complements the reactive behaviour and allows the robot to navigate safely in a partially known environment during a long time period without human intervention.     

Two-dimensional navigation problems: A knowledge-based system approach

Many researchers are studying ways to create machines that can make their own decisions and act on them. Recently, great advances have been made in intelligent mobile robot technology, advances which will provide autonomous traveling ability to autonomous systems, allowing them not only to surmount stairs but also other obstacles. The autonomous systems are expected to gather knowledge about their environment, construct a symbolic world model of the environment, and use this model in planning and carrying out tasks set them in high-level style. An approach to automatic path planning for self-navigation problems is presented. It is structured as a knowledge-based system and is a method of planning safe paths around circular obstacles in a two-dimensional plane for autonomous systems. The expert system path planner reduces the complexity of the problem and the computer run-time, enabling the agent to achieve a quicker response to its own environment. Also, computer run-time increases very slowly with problem complexity. It is done by: (1) representing the environmental information by sets of facts; (2) guiding the moving object by groups of rules and (3) deriving the result with simple algorithm and fewer calculations. This algorithm is implemented in the expert system environment, and some examples drawn from the system are also demonstrated.     

Autonomous Driving with Concurrent Goals and Multiple Vehicles: Experiments and Mobility Components

In this paper, we describe a complete system for mission planning and execution for multiple robots in natural terrain. We report on experiments with a system for autonomously driving two vehicles based on complex mission specifications. We show that the system is able to plan local paths in obstacle fields based on sensor data, to plan and update global paths to goals based on frequent obstacle map updates, and to modify mission execution, e.g., the assignment and ordering of the goals, based on the updated paths to the goals.Two recently developed sensors are used for obstacle detection: a high-speed laser range finder, and a video-rate stereo system. An updated version of a dynamic path planner, D*, is used for on-line computation of routes. A new mission planning and execution-monitoring tool, GRAMMPS, is used for managing the allocation and ordering of goals between vehicles.We report on experiments conducted in an outdoor test site with two HMMWVs. Implementation details and performance analysis, including failure modes, are described based on a series of twelve experiments, each over 1/2 km distance with up to nine goals.The work reported here includes a number of results not previously published, including the use of a real-time stereo machine and a high-performance laser range finder, and the use of the GRAMMPS planning system.     

Autonomous Driving with Concurrent Goals and Multiple Vehicles: Mission Planning and Architecture

We introduce a new distributed planning paradigm, which permits optimal execution and dynamic replanning of complex multi-goal missions. In particular, the approach permits dynamic allocation of goals to vehicles based on the current environment model while maintaining information-optimal route planning for each individual vehicle to individual goals. Complex missions can be specified by using a grammar in which ordering of goals, priorities, and multiple alternatives can be described. We show that the system is able to plan local paths in obstacle fields based on sensor data, to plan and update global paths to goals based on frequent obstacle map updates, and to modify mission execution, e.g., the assignment and ordering of the goals, based on the updated paths to the goals.The multi-vehicle planning system is based on the GRAMMPS planner; the on-board dynamic route planner is based on the D* planner. Experiments were conducted with stereo and high-speed ladar as the to sensors used for obstacle detection. This paper focuses on the multi-vehicle planner and the systems architecture. A companion paper (Brumitt et al., 2001) analyzes experiments with the multi-vehicle system and describes in details the other components of the system.     

Planetary exploration by a mobile robot: Mission teleprogramming and autonomous navigation

Sending mobile robots to accomplish planet exploration missions is scientifically promising and technologically challenging. We present in this paper a complete approach that encompasses the major aspects involved in the design of a robotic system for planetary exploration. It includes mission teleprogramming and supervision at a ground station, and autonomous mission execution by the remote mobile robot. We have partially implemented and validated these concepts. Experimental results illustrate the approach and the results.     

Full-parameter vision navigation based on scene matching for aircrafts

Vision navigation based on scene matching between real-time images and a reference image has many advantages over the commonly used inertial navigation system （INS）, such as no cumulative measurement errors for long-endurance flight. Recent developments in vision navigation are mainly used for partial navigation parameters measurements, such as the position and the relative velocity, which cannot meet the requirements of completely autonomous navigation. We present the concept, principle and method of full-parameter vision navigation （FPVN） based on scene matching. The proposed method can obtain the three-dimensional （3D） position and attitude angles of an aircraft by the scene matching for multiple feature points instead of a single point in existing vision navigations. Thus, FPVN can achieve the geodetic position coordinates and attitude angles of the aircraft and then the velocity vector, attitude angular velocity and acceleration can be derived by the time differentials, which provide a full set of navigation parameters for aircrafts and unmanned aerial vehicles （UAVs）. The method can be combined with the INS and the cumulative errors of the INS can be corrected using the measurements of FPVN rather than satellite navigation systems. The approach provides a completely autonomous and accurate navigation method for long-endurance flight without the help of satellites.     

月球表面巡视探测自主局部避障规划

路径规划是月球表面巡视探测自主导航的重要功能,是提高地外天体表面探测效率和安全性的关键.国外已实现的地外天体表面自主路径规划方法以局部避障为主要目标,不考虑全局目标可达性和完备性,本文针对该问题,提出一种基于地形通过性定量评价和目标可达的综合自主局部避障规划方法,通过对稠密地形数据进行可通过性能的综合评价,并考虑与目标的方位和距离,规划出能够到达目标的避障安全路径.该方法已经成功应用于我国\"玉兔号\"和\"玉兔二号\"月球车的自主导航中.     

采用改进D*Lite算法的自主移动机器人路径规划

针对动态环境下自主移动机器人的路径规划问题提出了改进D*Lite算法;该算法在D*Lite算法的基础上,引入Bresenham画线算法对扩展节点进行可视检测,得到方向任意且避免不必要转折的预规划路径,并建立分辨率高于全局障碍图的局部障碍图,动态存储传感器实时获取的局部环境信息,充分利用局部环境信息实时重规划机器人当前位置到目标点的最优路径,提高算法的规划精度及对动态环境的适应性;仿真实验结果证明,该算法大大缩短了路径长度,并且具有可行性和实时性.     

全自主机器人足球系统的研究综述

综述了全自主机器人足球系统的历史和研究现状 .对机器人足球系统的协作系统体系结构、机器学习、路径规划、实时通信、视觉和多传感器融合等技术进行了较为详细的分析 ,并且对各种研究方法的优势与不足进行了比较 .     

基于Walker星座的导航卫星自主导航的GDOP最小值分析

卫星自主定轨时选择测量卫星的几何构型对于定轨精度有着重要的影响.目前地面接收机与导航卫星的几何构型对定位精度的影响主要由GDOP（几何衰减因子）来衡量,GDOP值的下限限制了在一定的测量精度下用户定位的精度范围.通过构建Walker构型的导航星座将地面接收机GDOP取最小值时的边界确定,推广应用到自主导航环境下,利用均匀采样和遗传算法分别独立得到GDOP的最小值,同时用仿真数据验证了这个值的正确性.     

地形对雷达高度计卫星自主导航精度影响分析

以中低轨道卫星为应用背景,对基于星载雷达高度计的卫星自主导航系统展开研究,着重分析了雷达高度计卫星自主导航中的关键因素,即地形起伏对导航精度的影响。根据实际地形的统计特性,并结合导航精度仿真分析的需要,建立了模拟地形的数学模型;对不同地形条件下雷达高度计卫星自主导航系统的导航精度进行了仿真研究,分析了不同的地形条件对雷达高度计卫星自主导航精度的影响。研究的结论对雷达高度计自主导航技术的实际应用将具有重要的参考价值。     

无人动力伞飞行航路自主控制方法研究

根据无人动力伞的特点,提出了一种无人动力伞飞行航路自主控制方法;研究了动力伞的自主导航原理,重点分析了动力伞航路预置的方法,并给出了航线的设定与规划,同时给出了根据GPS反馈的飞行实时状态对航路进行检测的具体方法;并在自行开发的动力伞航路自主控制演示平台上,对动力伞自主飞行控制系统进行仿真;试验证明,无人动力伞基本能按照预定航线进行自主飞行,系统有较好的动态特性和稳态控制精度,达到了预期的目标。     

基于多传感器信息融合的移动机器人导航综述

综述了自主式移动机器人导航技术,对其中的同步定位与地图创建、路径规划以及多传感器信息融合等技术进行了详细的分析,并从基于地图、基于环境和基于行为3个方面全面地阐述了移动机器人路径规划技术的研究现状.对当前的研究热点SLAM技术、遗传算法和基于行为的规划算法等进行了较为详细的介绍和分析.同时,展望了移动机器人导航技术的发展趋势.     

基于X射线脉冲星导航系统探测器研究

综述了基于X射线脉冲星导航系统探测器的原理,分析了现有的几种不同类型探测器的性能、测时特点和应用的局限性;给出了由多只探测器组成的探测器系统的原理设计,并分析了探测器系统的构成、安装方式以及处理电路;阐述了X射线脉冲星导航系统探测器在航天器导航中的应用以及国外应用先例,为基于X射线脉冲星导航系统探测器的研制提供有用的参考。     

室外自主移动机器人AMOR的导航技术

在非结构化环境,移动机器人行驶运动规划和自主导航是非常挑战性的问题。基于实时的动态栅格地图,提出了一个快速的而又实效的轨迹规划算法,实现机器人在室外环境的无碰撞运动导航。AMOR是自主研发的室外运动移动机器人,它在2007年欧洲C-ELROB大赛中赢得了野外自主侦察比赛的冠军。它装备了SICK的激光雷达,用来获取机器人运动前方的障碍物体信息,建立实时动态的环境地图。以A*框架为基础的改造算法,能够在众多的路径中快速地找到最佳的安全行驶路径,实现可靠的自主导航。所有的测试和比赛结果表明所提方案是可行的、有效的。     

基于ROS的无人配送车导航系统的设计与实现

针对无人配送车在自主导航过程中存在的寻路效率低、避障能力弱、转折幅度过大等问题,该文采用搭载机器人操作系统(ROS)的Turtlebot3机器人作为无人配送车,设计并实现了高效稳定的无人配送车自主导航系统。ROS是专门用于编写机器人软件的灵活框架,对其集成的SLAM算法进行改进,以完成无人配送车在封闭园区环境中的即时定位与地图构建,同时对ROS导航功能包集成的路径规划算法进行改进,使无人配送车在已知环境地图中规划生成出适合无人配送车工作的路径和有效避开障碍物。最后在Gazebo仿真环境中对无人配送车自主导航系统进行测试与验证。仿真试验结果表明,设计实现的无人配送车导航系统能够很好地满足无人配送车在封闭园区中的自主导航功能。     

Design and Control of Autonomous Underwater Robots: A Survey

During the 1990s, numerous worldwide research and development activities have occurred in underwater robotics, especially in the area of autonomous underwater vehicles (AUVs). As the ocean attracts great attention on environmental issues and resources as well as scientific and military tasks, the need for and use of underwater robotic systems has become more apparent. Great efforts have been made in developing AUVs to overcome challenging scientific and engineering problems caused by the unstructured and hazardous ocean environment. In the 1990s, about 30 new AUVs have been built worldwide. With the development of new materials, advanced computing and sensory technology, as well as theoretical advancements, R&D activities in the AUV community have increased. However, this is just the beginning for more advanced, yet practical and reliable AUVs. This paper surveys some key areas in current state-of-the-art underwater robotic technologies. It is by no means a complete survey but provides key references for future development. The new millennium will bring advancements in technology that will enable the development of more practical, reliable AUVs.