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Symbolic Trajectory Description in Mobile Robotics 总被引:1,自引:0,他引:1
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《Advanced Robotics》2013,27(7):749-762
This paper proposes a method of robot navigation in outdoor environments based upon panoramic view and Global Positioning System (GPS) information. Our system is equipped with a GPS navigator and a camera. The route scene can be described by three-dimensional objects extracted as landmarks from panoramic representations. For an environment having limited routes, a two-dimensional map can be made based upon routes scenes, assuming that the topological relation of routes at intersections is known. By using GPS information, the global position of a mobile robot can be known, and a coarse-to-fine method is used to generate an outdoor environment map and locate a mobile robot. First, a robot finds its approximate position based on the GPS information. Then, it identifies its location from the image information. Experimental results in outdoor environments are given. 相似文献
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Maximilian Beinhofer Jörg Müller Wolfram Burgard 《Robotics and Autonomous Systems》2013,61(10):1060-1069
Being able to navigate accurately is one of the fundamental capabilities of a mobile robot to effectively execute a variety of tasks including docking, transportation, and manipulation. As real-world environments often contain changing or ambiguous areas, existing features can be insufficient for mobile robots to establish a robust navigation behavior. A popular approach to overcome this problem and to achieve accurate localization is to use artificial landmarks. In this paper, we consider the problem of optimally placing such artificial landmarks for mobile robots that repeatedly have to carry out certain navigation tasks. Our method aims at finding the minimum number of landmarks for which a bound on the maximum deviation of the robot from its desired trajectory can be guaranteed with high confidence. The proposed approach incrementally places landmarks utilizing linearized versions of the system dynamics of the robot, thus allowing for an efficient computation of the deviation guarantee. We evaluate our approach in extensive experiments carried out both in simulations and with real robots. The experiments demonstrate that our method outperforms other approaches and is suitable for long-term operation of mobile robots. 相似文献
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We have built a mobile robotic platform that features an Active Robotic Head (ARH) with two high-resolution cameras that can
be switched during robot operation between two configurations that produce respectively panoramic and stereoscopic images.
Image disparity is used for improving the quality of the texture. The robot head switches dynamically, based on robot operation
between the stereoscopic configuration and the panoramic configuration.
相似文献
Massimo BergamascoEmail: |
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《Robotics and Autonomous Systems》2014,62(4):456-473
This work studies the interaction of non-holonomic and visibility constraints using a Differential Drive Robot (DDR) that has to keep static landmarks in sight in an environment with obstacles. The robot has a limited sensor, namely, it has a restricted field of view and bounded sensing range (e.g. a video camera). Here, we mean by visibility that a clear line of sight can be thrown between the landmark and the sensor mounted on the DDR. We first determine the necessary and sufficient conditions for the existence of a path such that our system is able to maintain one given landmark visibility in the presence of obstacles. This is done through a recursive, complete algorithm that uses motion primitives exhibiting local optimality, as they are locally shortest-lengths paths. Then, we extend this result to the problem of planning paths guaranteeing visibility among a set of landmarks, e.g. to observe a given sequence of landmarks or to observe at each point of the path at least one element of the landmarks set. We also provide a procedure that computes the robot controls yielding such a path.1 相似文献
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Mobile Robot Self-Localization without Explicit Landmarks 总被引:3,自引:0,他引:3
Localization is the process of determining the robot's location within its environment. More precisely, it is a procedure which takes
as input a geometric map, a current estimate of the robot's pose, and sensor readings, and produces as output an improved
estimate of the robot's current pose (position and orientation). We describe a combinatorially precise algorithm which performs
mobile robot localization using a geometric model of the world and a point-and-shoot ranging device. We also describe a rasterized
version of this algorithm which we have implemented on a real mobile robot equipped with a laser rangefinder we designed.
Both versions of the algorithm allow for uncertainty in the data returned by the range sensor. We also present experimental
results for the rasterized algorithm, obtained using our mobile robots at Cornell.
Received November 15, 1996; revised January 13, 1998. 相似文献
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This paper addresses the problem of localization and map construction by a mobile robot in an indoor environment. Instead
of trying to build high-fidelity geometric maps, we focus on constructing topological maps as they are less sensitive to poor
odometry estimates and position errors. We propose a modification to the standard SLAM algorithm in which the assumption that
the robots can obtain metric distance/bearing information to landmarks is relaxed. Instead, the robot registers a distinctive
sensor “signature”, based on its current location, which is used to match robot positions. In our formulation of this non-linear
estimation problem, we infer implicit position measurements from an image recognition algorithm. We propose a method for incrementally
building topological maps for a robot which uses a panoramic camera to obtain images at various locations along its path and
uses the features it tracks in the images to update the topological map. The method is very general and does not require the
environment to have uniquely distinctive features. Two algorithms are implemented to address this problem. The Iterated form
of the Extended Kalman Filter (IEKF) and a batch-processed linearized ML estimator are compared under various odometric noise
models.
相似文献
Paul E. RybskiEmail: |
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In landmark-based navigation systems for mobile robots, sensory perceptions (e.g., laser or sonar scans) are used to identify the robot’s current location or to construct internal representations, maps, of the robot’s environment. Being based on an external frame of reference (which is not subject to incorrigible drift errors such as those occurring in odometry-based systems), landmark-based robot navigation systems are now widely used in mobile robot applications.The problem that has attracted most attention to date in landmark-based navigation research is the question of how to deal with perceptual aliasing, i.e., perceptual ambiguities. In contrast, what constitutes a good landmark, or how to select landmarks for mapping, is still an open research topic. The usual method of landmark selection is to map perceptions at regular intervals, which has the drawback of being inefficient and possibly missing ‘good’ landmarks that lie between sampling points.In this paper, we present an automatic landmark selection algorithm that allows a mobile robot to select conspicuous landmarks from a continuous stream of sensory perceptions, without any pre-installed knowledge or human intervention during the selection process. This algorithm can be used to make mapping mechanisms more efficient and reliable. Experimental results obtained with two different mobile robots in a range of environments are presented and analysed. 相似文献
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Visual Navigation in Natural Environments: From Range and Color Data to a Landmark-Based Model 总被引:3,自引:0,他引:3
This paper concerns the exploration of a natural environment by a mobile robot equipped with both a video color camera and a stereo-vision system. We focus on the interest of such a multi-sensory system to deal with the navigation of a robot in an a priori unknown environment, including (1) the incremental construction of a landmark-based model, and the use of these landmarks for (2) the 3-D localization of the mobile robot and for (3) a sensor-based navigation mode.For robot localization, a slow process and a fast one are simultaneously executed during the robot motions. In the modeling process (currently 0.1 Hz), the global landmark-based model is incrementally built and the robot situation can be estimated from discriminant landmarks selected amongst the detected objects in the range data. In the tracking process (currently 4 Hz), selected landmarks are tracked in the visual data; the tracking results are used to simplify the matching between landmarks in the modeling process.Finally, a sensor-based visual navigation mode, based on the same landmark selection and tracking, is also presented; in order to navigate during a long robot motion, different landmarks (targets) can be selected as a sequence of sub-goals that the robot must successively reach. 相似文献
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Selecting Landmarks for Localization in Natural Terrain 总被引:1,自引:0,他引:1
Clark F. Olson 《Autonomous Robots》2002,12(2):201-210
We describe techniques to optimally select landmarks for performing mobile robot localization by matching terrain maps. The method is based upon a maximum-likelihood robot localization algorithm that efficiently searches the space of possible robot positions. We use a sensor error model to estimate a probability distribution over the terrain expected to be seen from the current robot position. The estimated distribution is compared to a previously generated map of the terrain and the optimal landmark is selected by minimizing the predicted uncertainty in the localization. This approach has been applied to the generation of a sensor uncertainty field that can be used to plan a robot's movements. Experiments indicate that landmark selection improves not only the localization uncertainty, but also the likelihood of success. Examples of landmark selection are given using real and synthetic data. 相似文献
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Jong Hwan Lim Leonard J.J. 《IEEE transactions on pattern analysis and machine intelligence》2000,22(9):1035-1041
This paper presents a method for relocation of a mobile robot using sonar data. The process of determining the pose of a mobile robot with respect to a global reference frame in situations where no a priori estimate of the robot's location is available is cast as a problem of searching for correspondences between measurements and an a priori map of the environment. A physically-based sonar sensor model is used to characterize the geometric constraints provided by echolocation measurements of different types of objects. Individual range returns are used as data features in a constraint-based search to determine the robot's position. A hypothesize and test technique is employed in which positions of the robot are calculated from all possible combinations of two range returns that satisfy the measurement model. The algorithm determines the positions which provide the best match between the range returns and the environment model. The performance of the approach is demonstrated using data from both a single scanning Polaroid sonar and from a ring of Polaroid sonar sensors 相似文献
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Optimal landmark selection for triangulation of robot position 总被引:4,自引:0,他引:4
A mobile robot can identify its own position relative to a global environment model by using triangulation based on three landmarks in the environment. It is shown that this procedure may be very sensitive to noise depending on spatial landmark configuration, and relative position between robot and landmarks. A general analysis is presented which permits prediction of the uncertainty in the triangulated position.
In addition an algorithm is presented for automatic selection of optimal landmarks. This algorithm enables a robot to continuously base its position computation on the set of available landmarks, which provides the least noise sensitive position estimate. It is demonstrated that using this algorithm can result in more than one order of magnitude reduction in uncertainty. 相似文献
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自定位是自主移动机器人在RoboCup中型组比赛中的一个主要研究任务。本文提出了一种基于场地标志线上白点的中型组机器人自定位算法。该自定位方法采用数字罗盘确定机器人在世界坐标系下的朝向,白色标志线上的点确定机器人在世界坐标系下的坐标值,该算法进一步融合了视觉定位结果和里程计信息,使得定位结果更加鲁棒。 相似文献
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Rapid, safe, and incremental learning of navigation strategies 总被引:1,自引:0,他引:1
Millan J.del.R. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1996,26(3):408-420
In this paper we propose a reinforcement connectionist learning architecture that allows an autonomous robot to acquire efficient navigation strategies in a few trials. Besides rapid learning, the architecture has three further appealing features. First, the robot improves its performance incrementally as it interacts with an initially unknown environment, and it ends up learning to avoid collisions even in those situations in which its sensors cannot detect the obstacles. This is a definite advantage over nonlearning reactive robots. Second, since it learns from basic reflexes, the robot is operational from the very beginning and the learning process is safe. Third, the robot exhibits high tolerance to noisy sensory data and good generalization abilities. All these features make this learning robot's architecture very well suited to real-world applications. We report experimental results obtained with a real mobile robot in an indoor environment that demonstrate the appropriateness of our approach to real autonomous robot control. 相似文献
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全向视觉系统是RoboCup中型组足球机器人最重要的传感器之一。为了实现足球机器人的目标识别与自定位,提示了一种新的足球机器人全向视觉系统的设计与实现,其中在硬件上设计了一种由水平等比镜面和垂直等比镜面组合而成的新型全向反射镜面,其能够采集到较理想的全景图像;软件上则根据该镜面的成像特性实现了一种新颖的基于场地标志线信息的机器人自定位算法,该算法能够获得较准确的机器人自定位值。实验结果表明,该全向视觉系统能够有效地应用于机器人足球赛中。 相似文献
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Jean-Bernard Hayet 《Journal of Intelligent and Robotic Systems》2012,66(1-2):57-74
This paper studies the local nature of the shortest length paths for a differential drive robot, in the presence of two or more landmarks that the robot has to keep in its field of view. Such a system has to satisfy several types of constraint: the non-holonomy, the bounds on the sensor angle and a visibility constraint for the landmarks. We study the shape of the configuration space resulting from these constraints, the particular spiral-like curves (that we call S-curves) resulting from maintaining the sensor angle to its saturation values, and finally we provide a local analysis of the shortest length paths for this system, that involves these S-curves. We give a more general characterization of the shortest length paths for a set of N landmarks to be kept in sight. Finally, we describe a randomized planner that is based on these local primitives and for which we present planning simulations. The main application of this work can be found in the surveillance area, which is of special interest in present days for most Latin American metropolis. 相似文献