越野环境下自主车辆导航地图自动创建方法研究*

针对越野环境下的地图创建问题,提出了一种自动创建自主车导航地图的方法。首先将车载摄像机获得的图像投影到车体坐标系,然后结合车辆行驶轨迹信息采用基于标记的分水岭算法判定可通行区域,最后融合局部俯视图信息生成全局一致地图,并在实时导航需求下对地图进行优化得到最终的导航地图。自主车实车实验结果表明,该方法生成的地图满足自主车实时导航需求,提高了路径规划效率。     

越野环境建模与动态路径规划

针对越野环境下移动机器人的导航与控制问题，提出了一种越野环境下环境建模与动态路径规划方法。该方法能够针对地形的数字高程模型，在综合考虑机器人的性能约束和地形特征等因素的基础上有效地实现越野环境的建模；在此基础上的路径规划采用全局信息与局部信息、前期规划结果与当前规划相结合的方法，满足了越野环境下动态路径规划的要求。实验结果表明，该方法能够很好地适应各种复杂的越野环境。     

非合作航天器自主相对导航研究综述

非合作航天器自主相对导航作为与非合作航天器实现空间交会对接过程中的关键技术,是在轨服务技术的重点发展方向之一,其研究具有重要的理论价值与工程意义.针对在轨服务任务对于自主相对精确导航的需求,本文对发展非合作航天器自主相对导航技术的必要性进行了阐述.首先总结了非合作航天器自主相对导航技术的内涵与研究现状;随后分析梳理了非合作航天器自主相对导航过程涉及到的光学敏感器、位姿测量、导航滤波器以及地面实验等关键技术.最后根据研究现状和关键技术的分析指出了非合作航天器自主相对导航目前存在的主要问题并给出后续发展的建议.     

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。     

非确定环境的表示与推理

鉴于复杂（野外）地形建模中存在各种非确定及主观因素，本文提出了关于非确定环境的表示与推理方法，并针对自主车在该类环境中的导航，提出了相应的决策函数和搜索策略，最后给出在ＰＣ－３８６计算机上的仿真结果。     

用于室外移动机器人实时自主导航的2.5维角度势场法

本文提出了一种针对装备有激光测距仪的地面移动机器人系统的实时自主导航算法.与现有的专为解决2维导航问题所设计的算法不同,新算法在导航过程中引入了障碍物的高度信息,并且使用2.5维角度势场法来满足在复杂的户外地形条件下的自主导航要求.首先,一幅激光测距仪扫描地图被划分为两种不同的功能扇区:导航扇区和监测扇区.然后,在充分利用障碍物高度信息的条件下,对导航扇区和监测扇区进行重构,从而获得一幅虚拟的2维激光扫描地图.最后,传统的角度势场法被进行了适当的改进,以便能够顺利的作用到虚拟的2维激光扫描地图上,产生恰当的导航指令.新算法在履带型地面移动机器人上进行了测试,实验结果充分的证明了其有效性和可实现性.     

自主机器人在自然地形中的一种越野导航规划算法

在致力于自然地形中实施自主导航的机器人研究中,人们发现:导航规划是自主机器人所有控制和推理任务的基础,当前虽然人工智能、机器人领域的研究者们开发了许多路径规划算法,但是所有这些算法都是针对结构化环境这样一种简单地形,并且在将这种地图形成地形数据结构时,都是由人工键入到计算机中去的。这样,为表达一个简单环境,常常需要花费很大的代价,并且当地形比较复杂时,无法人工去描述,即使可以描述,算法的效率也很成问题。现在,机器人研究的重心已开始倾向于自主移动机器人,但没有一个有效、快速的越野规划算法,要使自主机器人在野外实施自主行驶是不可能的。因此,自然地形中     

基于地形特征知识的自适应地形线性化

地形线性化技术防是地形辅助导航的关键技术外，也是数字地形分析的研究内容之一。针对地形辅助导航系统中现有地形线性化方法存在的问题及其对地形辅助导航性能的影响，本文提出在线性化的方法中应同时考虑地形特征知识和卡尔曼滤波器提供的不确定性影响，提出并发展了一套基于地形特征知识的自适应地形线性化方法，并根据置信水平，提出了自适应选取线性化批合区域的方法，实验与仿真结果证明了本方法的有效性。     

基于视觉的移动机器人可通行区域识别研究综述

实现实时准确的可通行区域识别,是户外环境下移动机器人导航的重要组成部分。对基于视觉的移动机器人可通行区域识别研究进行了综述,首先介绍了移动机器人视觉导航常用的视觉系统,并从障碍物检测、地形分类两个方面介绍了该问题研究的进展,最后对该领域的技术发展趋势进行了探讨。     

基于改进粒子滤波的AUV海底地形辅助定位方法

针对自主式水下无人航行器的地形辅助导航问题,提出一种基于粒子滤波的地形辅助定位方法。为了解决粒子滤波的“粒子贫化”问题,引入了辅助采样,提出一种基于辅助采样粒子滤波的海底地形辅助定位方法,减小了由于重采样带来的粒子多样性的损失。基于半物理测试平台的仿真实验表明:本文所提出方法的精度较高,可适应不同地形特征下的地形辅助定位,可满足水下无人航行器(autonomous underwater vehicle, AUV) 水下导航定位的需求。     

Fuzzy-based speed estimation for navigation of unmanned robots

This study presents a framework for assessing the navigation speed of unmanned robots by combining information extracted from the 3D world model of natural terrain with regional traversability based on the fuzzy technique. The proposed method divides the world model into several patches, extracts the slope and roughness of each terrain patch along four heading directions, and then uses them to evaluate the level of difficulty associated with the traversal. The slope is estimated through curved surface fitting, and roughness is obtained using fractal-based analysis together with another two RMS metrics. As navigation systems can cope with the imprecision and uncertainty of input data, we modify the Seraji’s fuzzy-based measure to assess the traversability and navigation speed of each patch for path planning. The proposed method is tested on both fractal and real terrain to verify its effectiveness.     

Navigating a mobile robot by a traversability field histogram.

This paper presents an autonomous terrain navigation system for a mobile robot. The system employs a two-dimensional laser range finder (LRF) for terrain mapping. A so-called "traversability field histogram" (TFH) method is proposed to guide the robot. The TFH method first transforms a local terrain map surrounding the robot's momentary position into a traversability map by extracting the slope and roughness of a terrain patch through least-squares plane fitting. It then computes a so-called "polar traversability index" (PTI) that represents the overall difficulty of traveling along the corresponding direction. The PTIs are represented in a form of histogram. Based on this histogram, the velocity and steering commands of the robot are determined. The concept of a virtual valley and an exit condition are proposed and used to direct the robot such that it can reach the target with a finite-length path. The algorithm is verified by simulation and experimental results.     

基于地形预测与修正的搜救机器人可通过度

针对搜救机器人的自主导航问题,提出了一种新的可通过度计算算法．文中定义的可通过度包含预测 可通过度和实时可通过度两个部分．通过图像处理的方法计算前方地面的粗糙度和起伏度从而得到预测可通过度, 机器人向可通过度最大的区域运动,在运动过程中通过测量车体的姿态变化率和履带与地面的打滑度来修正预测可 通过度对机器人的导引带来的偏差,并通过旋转式超声测距数据获取距离信息,去除障碍物对纹理信息的干扰．野 外条件下的实际运行实验证明了该导航算法的有效性．     

Vision‐based terrain characterization and traversability assessment

This article presents novel techniques for real‐time terrain characterization and assessment of terrain traversability for a field mobile robot using a vision system and artificial neural networks. The key terrain traversability characteristics are identified as roughness, slope, discontinuity, and hardness. These characteristics are extracted from imagery data obtained from cameras mounted on the robot and are represented in a fuzzy logic framework using perceptual, linguistic fuzzy sets. The approach adopted is highly robust and tolerant to imprecision and uncertainty inherent in sensing and perception of natural environments. The four traversability characteristics are combined to form a single Fuzzy Traversability Index, which quantifies the ease‐of‐traversal of the terrain by the mobile robot. Experimental results are presented to demonstrate the capability of the proposed approach for classification of different terrain segments based on their traversability. © 2001 John Wiley & Sons, Inc.     

A KNOWLEDGE-BASED NAVIGATION SCHEME FOR AUTONOMOUS LAND VEHICLES

A knowledge-based navigation system for autonomous land vehicles (ALVs) has been developed which can successfully negotiate an obstacle and threat-laden terrain, even if nothing is known beforehand about the terrain. The ALV stores new information in its memory as it travels, has the ability to backtrack out of unexpected dead ends, and performs spontaneous decision making in the field based on local sensor readings. The optimal global route of the ALV journey is obtained using dynamic programming, and decision making is accomplished via a production rule-based system. Execution examples demonstrate the power of the prototype system to solve navigation problems. This establishes the feasibility of constructing a valid ALV by combining search techniques with artificial intelligence tools such as production rule-based systems.     

New Traversability Indices and Traversability Grid for Integrated Sensor/Map‐Based Navigation

This paper presents new measures of terrain traversability at short range and long range of a mobile robot; namely, local and global traversability indices. The sensor‐based local traversability index is related by a set of linguistic rules to large obstacles and surface softness within a short range of the robot measured by on‐board sensors. The map‐based global traversability index is obtained from the terrain topographic map, and is based on major surface features such as hills and lakes within a long range of the robot. These traversability indices complement the mid‐range sensor‐based regional traversability index introduced earlier. Each traversability index is represented by four fuzzy sets with the linguistic labels {POOR, LOW, MODERATE, HIGH}, corresponding to surfaces that are unsafe, moderately‐unsafe, moderately‐safe, and safe for traversal, respectively. The global terrain analysis also leads to the new concepts of traversability map and traversability grid for representation of terrain quality based on the global map information. The traversability indices are used in two sensor‐based traverse‐local and traverse‐regional behaviors and one map‐based traverse‐global behavior. These behaviors are integrated with a map‐based seek‐goal behavior to ensure that the mobile robot reaches its goal safely while avoiding both sensed and mapped terrain hazards. This provides a unified system in which the two independent sources of terrain quality information, i.e., prior maps and on‐board sensors, are integrated together for reactive robot navigation. The paper is concluded by a graphical simulation study. © 2003 Wiley Periodicals, Inc.     

Normal Distributions Transform Traversability Maps: LIDAR‐Only Approach for Traversability Mapping in Outdoor Environments

Safe and reliable autonomous navigation in unstructured environments remains a challenge for field robots. In particular, operating on vegetated terrain is problematic, because simple purely geometric traversability analysis methods typically classify dense foliage as nontraversable. As traversing through vegetated terrain is often possible and even preferable in some cases (e.g., to avoid executing longer paths), more complex multimodal traversability analysis methods are necessary. In this article, we propose a three‐dimensional (3D) traversability mapping algorithm for outdoor environments, able to classify sparsely vegetated areas as traversable, without compromising accuracy on other terrain types. The proposed normal distributions transform traversability mapping (NDT‐TM) representation exploits 3D LIDAR sensor data to incrementally expand normal distributions transform occupancy (NDT‐OM) maps. In addition to geometrical information, we propose to augment the NDT‐OM representation with statistical data of the permeability and reflectivity of each cell. Using these additional features, we train a support‐vector machine classifier to discriminate between traversable and nondrivable areas of the NDT‐TM maps. We evaluate classifier performance on a set of challenging outdoor environments and note improvements over previous purely geometrical traversability analysis approaches.     

基于差分进化支持向量机的移动机器人可通过度预测

提出了一种移动机器人可通过度预测方法.给出了基于相对震动强度的可通度描述.通过提取典型地表图像的色彩和纹理特征并测量机器人通过该地表的相对震动强度建立训练样本集.使用差分进化算法优化支持向量机模型参数形成差分进化支持向量机对训练样本和相对震动强度进行拟合.在移动机器人运行过程中,线性分割前方地表图像形成预测子区域,通过...     

自主车仿真系统中场景建模与视觉仿真实现

提出了自主车仿真系统的基本思想,并针对视觉导航的需求建立了自主车行驶的虚拟环境及典型障碍物模型;根据自主车和云台的运动学特性,实现了自主车场景漫游及云台控制功能,同时结合车体及云台位姿解算完成地形匹配及车载摄像机位姿确定;最后,对实际摄像机参数及成像噪声特性进行分析,进而给出了相应的视觉传感器仿真部分的实现.实验结果表明,该视觉仿真部分具有良好的真实感和实时性.