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移动机器人的同步自定位与地图创建研究进展 总被引:18,自引:2,他引:18
自主移动机器人在未知环境下作业时,首先要解决的基本问题就是其自身的定位问题,而定位问题与环境地图的创建又是相辅相成的.本文从相关理论和关键技术等方面,系统地总结了同步自定位和地图创建的研究现状,着重介绍了基于概率论的方法,分析了目前存在的难题,并指出了未来研究的发展方向. 相似文献
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未知环境下移动机器人同步地图创建与定位研究进展 总被引:3,自引:1,他引:3
移动机器人同步地图创建与定位(SLAM)是移动机器人的核心研究课题.本文对SLAM的最新研究进展和关键技术进行了综述:并从地图创建模型、计算复杂度和算法鲁棒性等方面对现有方法进行了对比分析.最后总结分析了SLAM研究存在的难题,探讨了今后的发展方向. 相似文献
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针对城市环境中全球定位系统(GPS)信号易受到高层建筑遮挡而无法提供准确位置信息的问题,提出了一种基于建筑物竖直侧平面特征及建筑物二维轮廓地图的移动机器人定位方法。该方法利用车载视觉,首先对两视图间的竖直直线特征进行匹配;然后基于匹配的竖直线特征对建筑物的竖直侧平面进行重建;最后,利用建筑物竖直侧平面特征及建筑物二维俯视轮廓地图,设计了一种基于随机采样一致性(RANSAC)的移动机器人视觉定位算法,从而解决了在建筑物方向任意的复杂城市环境中的机器人定位问题。实验结果表明,算法的平均定位误差约为3.6m,可以有效地提高移动机器人在复杂城市环境中自主定位的精度及鲁棒性。 相似文献
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《Robotics and Autonomous Systems》2006,54(2):159-164
In appearance-based robot localization the environment map does not represent geometrical features but consists of an appearance map, which is a collection of robot poses and corresponding sensor observations. In this paper, we describe a concurrent map-building and localization (CML) system based on a multi-hypotheses tracker that is able to build and refine autonomously the appearance map required for localization as the robot moves in the environment. The results included in this paper validate our approach. 相似文献
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对复杂未知环境构建地图是移动机器人面临的一大问题.通常忽略未知环境的几何特征,将其抽象成未知无向连通图,机器人只沿着图的边进行搜索,并将走过每条边的成本看成是1.机器人构建地图的成本用走过的总边数来表示.对于一个完全未知的环境,从一点S出发,限制移动机器人最远能走r(如燃料问题及安全线或通信线等)步(边数)的范围内,基于深度受限剪枝生成子树的方法,结合广度优先搜索和受限的深度优先搜索染色策略,给出了对未知环境构建完整地图的有效算法,该算法的成本为|E|+O|V|,这是目前最优结果. 相似文献
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This paper presents both the theory and the experimental results of a method allowing simultaneous robot localization and
odometry error estimation (both systematic and non-systematic) during the navigation. The estimation of the systematic components
is carried out through an augmented Kalman filter, which estimates a state containing the robot configuration and the parameters
characterizing the systematic component of the odometry error. It uses encoder readings as inputs and the readings from a
laser range finder as observations. In this first filter, the non-systematic error is defined as constant and it is overestimated.
Then, the estimation of the real non-systematic component is carried out through another Kalman filter, where the observations
are obtained by two subsequent robot configurations provided by the previous augmented Kalman filter. There, the systematic
parameters in the model are regularly updated with the values estimated by the first filter. The approach is theoretically
developed for both the synchronous and the differential drive. A first validation is performed through very accurate simulations
where both the drive systems are considered. Then, a series of experiments are carried out in an indoor environment by using
a mobile platform with a differential drive. 相似文献
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Soonyong Park Mignon Park Sung-Kee Park 《International Journal of Control, Automation and Systems》2009,7(4):598-614
This paper presents new object-spatial layout-route based hybrid map representation and global localization approaches using
a stereo camera. By representing objects as high-level features in a map, a robot can deal more effectively with different
contexts such as dynamic environments, human-robot interaction, and semantic information. However, the use of objects alone
for map representation has inherent problems. For example, it is difficult to represent empty spaces for robot navigation,
and objects are limited to readily recognizable things. One way to overcome these problems is to develop a hybrid map that
includes objects and the spatial layout of a local space. The map developed in this research has a hybrid structure that combines
a global topological map and a local hybrid map. The topological map represents the spatial relationships between local spaces.
The local hybrid map combines the spatial layout of the local space with the objects found in that space. Based on the proposed
map, we suggest a novel coarse-to-fine global localization method that uses object recognition, point cloud fitting and probabilistic
scan matching. This approach can accurately estimate robot pose with respect to the correct local space.
Recommended by Editor Jae-Bok Song. This research was performed for the Intelligent Robotics Development Program, one of the
21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea.
Soonyong Park received the B.S. and M.S. degrees from the Department of Mechanical Engineering, Kyunghee University, Seoul, Korea, in 2001
and 2003, respectively. He is currently working toward the Ph.D. degree in the Department of Electrical and Electronic Engineering,
Yonsei University, Seoul, Korea. Since 2001, he has been a student researcher in the Center for Cognitive Robotics Research,
Korea Institute of Science and Technology (KIST), Seoul, Korea. His research interests include mobile robot navigation and
computer vision.
Mignon Park received the B.S. and M.S. degrees in Electronics from Yonsei University, Seoul, Korea, in 1973 and 1977, respectively. He
received the Ph.D. degree in University of Tokyo, Japan, 1982. He was a researcher with the Institute of Biomedical Engineering,
University of Tokyo, Japan, from 1972 to 1982, as well as at the Massachusetts Institute of Technology, Cambridge, and the
University of California Berkeley, in 1982. He was a visiting researcher in Robotics Division, Mechanical Engineering Laboratory,
Ministry of International Trade and Industry, Tsukuba, Japan, from 1986 to 1987. He has been a Professor in the Department
of Electrical and Electronic Engineering in Yonsei University, since 1982. His research interests include fuzzy control and
application, robotics, and fuzzy biomedical system.
Sung-Kee Park is a principal research scientist for Korea Institute of Science and Technology (KIST). He received the B.S. and M.S. degrees
in Mechanical Design and Production Engineering from Seoul National University, Seoul, Korea, in 1987 and 1989, respectively.
He received the Ph.D. degree (2000) from Korea Advanced Institue of Science and Technology (KAIST), Korea, in the area of
computer vision. Since then, he has been working for the center for cognitive robotics research at KIST. During his period
at KIST, he held a visiting position at the Robotics Institute of Carnegie Mellon University in 2005, where he did research
on object recognition. His recent work has been on cognitive visual processing, object recognition, visual navigation, and
human-robot interaction. 相似文献
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提出一种高效的基于全景视觉的室内移动机器人地图构建和定位方法. 该方法充分利用全景视觉系统视野广阔、获取环境信息完整的特点, 根据全景图像生成环境描述子; 利用上述环境描述子描述环境, 创建拓扑地图, 将地图表示为环境描述子的集合. 在此基础上, 提出一种基于贝叶斯理论的定位方法, 根据当前全景摄像头的观测值, 利用已生成的地图完成状态跟踪, 全局定位和“绑架”定位. 最后通过实验验证了该方法的有效性, 并给出了计算成本分析. 相似文献
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《Advanced Robotics》2013,27(4):437-450
This paper presents a methodology for building a high-accuracy environmental map using a mobile robot. The design approach uses low-cost infrared range-finder sensors incorporating with neural networks. To enhance the map quality, the errors occurring from the sensors are corrected. The non-linearity error of the sensors is compensated using a backpropagation neural network and the random error of readings including the uncertainty of the environment is taken into a sensor model as a probabilistic approach. The map is represented by an occupancy grid framework and updated by the Bayesian estimation mechanism. The effectiveness of the proposed method is verified through a series of experiments. 相似文献
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A novel topological map representation as well as an online map construction approach is presented in this paper. By virtue of the topological map whose nodes are represented with the free beams of the laser range finder together with the visual scale-invariant features, the mobile robot can autonomously navigate in unknown, large-scale and indoor environments. Different from the traditional navigation methods that rely on precise global localization, the robot locates itself qualitatively by location recognition rather than calculating its global pose in the world reference frame. By combining the reactive navigational method, Beam Curvature Method (BCM), with the topological map, a smooth, real-time navigation without precise localization can be realized. 相似文献
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同步定位与地图构建(SLAM)是当前机器人定位导航的研究热点,可靠的闭环检测是图优化SLAM的关键。而在大范围的复杂环境下,通过视觉或激光雷达进行闭环检测的可靠性低且计算开销大。针对这一问题,提出了一种基于WiFi指纹序列匹配的图优化SLAM算法。所提算法采用指纹序列进行闭环检测,由于指纹序列中包含多个指纹数据,信息量比单个指纹点对的数据丰富,因此将传统的基于指纹点对的匹配扩展到指纹序列的匹配可以大幅减小闭环误判的几率,从而确保了闭环检测的准确性,满足了SLAM在大范围复杂环境下的算法高精度要求。采用两组实验数据(机器人从不同的起点开始)对所提算法进行验证的结果表明:与高斯相似度的方法相比,所提算法的精度在第一组数据上提高了22.94%;在第二组数据上提高了39.18%。实验结果充分验证了所提算法在提高定位精度、确保闭环检测可靠性方面的优越性。 相似文献
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A. DE LA ESCALERA L. MORENO M. A. SALICHS J. M. ARMINGOL 《International journal of systems science》2013,44(8):771-782
A mobile robot needs to know its position and orientation with accuracy in order to decide the control actions that permit it to finish the entrusted tasks successfully. To obtain this information, dead-reckoning-based systems have been used, and more recently inertial navigation systems. However, these systems have some errors that grow bigger as time goes by, therefore a moment comes when the information provided is useless. Because of this, there should be a periodic process that updates the robot position and orientation of the vehicle. The process to determine the robot position and orientation by using information originated from the external sensors is defined as the mobile robot relocalization. It is obvious that the greater the frequency of this process, the better the knowledge of its position the robot will have, and therefore its movements will be better directed to the point it must reach. The algorithm to achieve this can be classified in two large groups: relocalization through an a priori map of the environment and relocalization through the detection of landmarks present in that environment. The algorithm presented in the paper belongs to the first case. The sensor used is a combination of a laser diode and a CCD camera. The sensorial information is modelled as straight lines that will be matched with an a priori map of the environment. With this, the position of the mobile robot is estimated. The matching process is accomplished within an extended Kalman filter. The algorithm is able to work in real time, and it actualizes the position of the robot in a continuous way. 相似文献
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Real-time map labelling for mobile applications 总被引:1,自引:0,他引:1
It is essential to label roads, landmarks, and other important features on maps for mobile applications to help users to understand their location and the environment. This paper aims to examine real-time map labelling methods suitable for the small screen on mobile devices. A slider method with a continuous search space was proposed to sequentially label both line and point features. The method starts with defining a range box for possible locations of the label. Then a search is performed, and the range box is reduced, if there are any cartographic objects that overlap the range box. Finally, the label is placed, at the best possible position in the reduced range box according to normal cartographic preferences, where it does not obscure any cartographic object. We implemented this method in a Java environment using the open source library JTS Topology Suite. A case study showed sound cartographic results of the labelling and acceptable computational efficiency. 相似文献
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Autonomous mobile robots need environmental maps to navigate to specific destinations, but there are difficulties in generating and acquiring efficient maps for them. Map learning systems and map representation for autonomous robot navigation are highly interrelated and need a total system design that combines these two factors. This study considers a combined simple map representation and map learning system. The proposed map representation includes geometrical relationships between important places and grid maps for these places, but not a total grid map of the environment. In particular, the study focuses on the ability to recognize places based on image features. Successful experiments on autonomous navigation with the proposed map representation using an actual mobile robot are described. 相似文献
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Kaneko Ryutaro Nakamura Yuji Morita Ryosuke Ito Satoshi 《Artificial Life and Robotics》2023,28(2):314-322
Artificial Life and Robotics - When using an autonomous mobile robot, an environmental map should be created in advance. In this study, we propose a method for creating a point cloud data (PCD) map... 相似文献