共查询到20条相似文献,搜索用时 31 毫秒
1.
2.
移动机器人地图创建中的不确定传感信息处理 总被引:15,自引:1,他引:14
该文研究移动机器人自主创建地图中的不确定传感信息处理问题,基于灰色系统理论
提出了一种新的对传感信息进行解释和融合的方法用于声纳信息的处理,并以此建立环境的栅
格地图.声纳的传感信息存在较大的不确定性,这里引入灰数的概念来表示和处理这种不确定
性,对于机器人在不同位置的测量结果,根据灰色系统理论对信息的理解方式设计融合方法,得
到一个对环境的整体表示.通过仿真环境和真实机器人平台上进行的创建地图实验,表明这种
方法具有良好的鲁棒性和准确度. 相似文献
3.
4.
This paper presents a novel approach to the vision based grid map building and localization problem that works in a complex
indoor environment with a single forward viewing camera. Most existing visual SLAM has been limited to the feature-based method
and only a few researchers have proposed visual SLAM methods for building a grid map using a stereo vision system which has
not been popular in practical application. In this paper, we estimate the planar depth by applying a simple visual sonar ranging
technique to the single camera image and then associating sequential scans through our own pseudo dense adaptive scan matching
algorithm reducing the processing time compared to the standard point-to-point correspondence based algorithm and finally
produce a grid map. To this end, we construct a Pseudo Dense Scan (PDS) which is an odometry based temporal accumulation of
the visual sonar readings emulating omni-directional sensing in order to overcome the sparseness of the visual sonar. Moreover,
in order to obtain a much more refined map, we further correct the slight trajectory error incurred in the PDS construction
step using Sequential Quadratic Programming (SQP) which is a well-known optimization scheme. Experimental results show that
our method can obtain an accurate grid map using a single camera without the need for a high price range sensors or stereo
camera.
相似文献
Se-Young OhEmail: |
5.
《Advanced Robotics》2013,27(12-13):1601-1616
This study introduces a method of general feature extraction for building a map and localization of a mobile robot using only sparsely sampled sonar data. Sonar data are acquired by using a general fixed-type sensor ring that frequently provides false returns on the locations of objects. We first suggest a data association filter that can classify sets of sonar data that are associated with the same hypothesized feature into one group. A feature extraction method is then introduced to decide the exact geometric parameters of the hypothesized feature in the group. We also show the possibility of extracting a circle feature consistently as well as a line or a point feature by using the proposed filter. These features are then assembled to build a global map and applied to extended Kalman filter-based localization of the robot. We demonstrate the validity of the proposed filter with the results of mapping and localization produced by real experiments. 相似文献
6.
7.
Masamichi Miyake Hiroyuki Takai Keihachiro Tachibana 《Artificial Life and Robotics》2009,14(3):401-404
In recent years, multiple robot systems that perform team operations have been developed. These robot systems are expected to execute complicated tasks smoothly in a given congested workspace. In this article, we propose a workspace mapping algorithm using ultrasonic stereo sonar and an image sensor in order to operate the mobile robots among obstacles. This workspace mapping algorithm involves two steps: (1) the position detection of obstacles using ultrasonic stereo sonar, and (2) the shape detection of obstacles using an image sensor. While each robot moves around in the given workspace, the two steps of the mapping algorithm are repeated and sensor data are collected. The robot measures the distance and the direction of obstacles using ultrasonic stereo sonar. The shape of obstacles is also captured using an onboard image sensor. A workspace map is created based on the sensor data accumulated from the proposed method, and successful results are also obtained through experiments. 相似文献
8.
Joong-Tae Park Jae-Bok Song Se-Jin Lee Munsang Kim 《Journal of Intelligent and Robotic Systems》2011,63(3-4):465-480
This paper describes a sonar sensor-based exploration method. To build an accurate map in an unknown environment during exploration, a simultaneous localization and mapping problem must be solved. Therefore, a new type of sonar feature called a ??sonar salient feature?? (SS-feature), is proposed for robust data association. The key concept of an SS-feature is to extract circle feature clouds on salient convex objects from environments by associating sets of sonar data. The SS-feature is used as an observation in the extended Kalman filter (EKF)-based SLAM framework. A suitable strategy is needed to efficiently explore the environment. We used utilities of driving cost, expected information about an unknown area, and localization quality. Through this strategy, the exploration method can greatly reduce behavior that leads a robot to explore a previously visited place, and thus shorten the exploration distance. A robot can select a favorable path for localization by localization gain during exploration. Thus, the robot can estimate its pose more robustly than other methods that do not consider localizability during exploration. This proposed exploration method was verified by various experiments, and it ensures that a robot can build an accurate map fully autonomously with sonar sensors in various home environments. 相似文献
9.
Effective Maximum Likelihood Grid Map With Conflict Evaluation Filter Using Sonar Sensors 总被引:1,自引:0,他引:1
《Robotics, IEEE Transactions on》2009,25(4):887-901
10.
11.
12.
Kao-Shing Hwang Yu-Jen Chen Hai-Chun Hong 《Journal of Intelligent and Robotic Systems》2004,39(3):307-331
An autonomous exploring system for a mobile robot is presented in this article. The system consists of an ultrasonic range sensor (URS) module and a novel method for building a map from exploration of an environment. Instead of random exploration, the proposed approach provides a systematic and efficient strategy to build the map by means of some preferential points. Taking a multitude of observations or measurements by sonar sensors, a mobile robot derives a virtual polygonal map from a set of regressed segments, partial prior known environmental information, and some inference rules for vertices. Additionally, the concept of safe zones is also introduced in the system to keep the mobile robot safe during exploration. Based on the identified virtual map, a searching method is used to select a next best observation to collect the most sufficient information. Several experiments are given to demonstrate the performance of this proposed approach. 相似文献
13.
Simultaneous Localization and Map building (SLAM) is referred to as the ability of an Autonomous Mobile Robot (AMR) to incrementally extract the surrounding features for estimating its pose in an unknown location and unknown environment. In this paper, we propose a new technique for extraction of significant map features from standard Polaroid sonar sensors to address the SLAM problem. The proposed algorithm explicitly initializes and tracks the line (or wall) features from a comparison between two overlapping sensor measurements buffers. The experimental studies on a Pioneer 2DX mobile robot equipped with sonar sensors suggest that SLAM problem can be solved by the proposed algorithm. The estimated trajectory of AMR from the standard model based on Extended Kalman Filter (EKF) localization for the same experiment is also provided for comparison. 相似文献
14.
针对移动机器人探测动态未知环境的问题,引入了一种由贝叶斯理论和Dempster-Shafer证据理论(DST)扩展而来的新的信息融合方法——Dezert-Smarandache理论(DSmT).采用栅格地图,并根据声纳的物理特性,在DSmT框架下建立了声纳的数学模型.运用DSmT中的高级模型,即混合DSm模型,构造了一组基本信度赋值函数(gbbaf),用以处理动态环境下声纳获取的不确定和不精确信息,甚至于高冲突信息.借助Pioneer2-Dxe移动机器人分别进行了混合DSm模型和DST两种算法的地图构建实验,并绘制了相应的二维基本信度赋值地图.将由混合DSm模型与DST构建出的环境地图进行了比较,充分验证了混合DSm模型在未知动态环境下的有效性,为处理动态高冲突信息提供了有力的理论依据. 相似文献
15.
This study presents a building extraction strategy from High-resolution satellite stereo images (HRSSI) using 2D and 3D information fusion. In the 2D processing strategy, a visible vegetation index (VVI) is generated. In the 3D processing, a disparity map is generated using semi-global matching (SGM). To remove defects from the disparity map, an object-based approach is proposed by using mean-shift image segmentation and extracting rectangles. By removing terrain effects, a normalized disparity map (nDM) is produced. In the next step, vegetation pixels are removed from nDM and an initial building mask is generated. As nDM does not have precise building boundaries, hybrid segmentation by the kernel graph cut (KGC) is applied to the feature space including the RGB, nDM, and VVI and the results are used in a decision level fusion step. By this methodology, segments that are highly intersected with initial building mask are classified as buildings. Finally, a building boundary refinement (BBR) algorithm is applied to buildings for removing the remaining defects. The proposed method is applied to two pairs of GeoEye-1 stereo images including residential and industrial test areas. Evaluation results show the completeness and correctness level of higher than 90% for the two test areas. Further evaluations show that the quality metric has significantly changed after decision level fusion using the KGC. 相似文献
16.
In this paper, we address the problem of building a grid map as accurately as possible using inexpensive and error-prone sonar sensors. In this research area, incorrect sonar measurements, which fail to detect the nearest obstacle in their beamwidth, generally have been dealt with in the same manner as correct measurements or have been excluded from the mapping. In the former case, the map quality may be severely degraded. In the latter case, the resulting map may have insufficient information after the incorrect measurements are removed because only correct measurements are frequently insufficient to cover the whole environment. We propose an efficient grid-mapping approach that incorporates incorrect measurements in a specialized manner to build a better map; we call this the enhanced maximum likelihood (eML) approach. The eML approach fuses the correct and incorrect measurements into a map based on sub-maps generated from each set of measurements. We also propose the maximal sound pressure (mSP) method to detect incorrect sonar readings using the sound pressure of the waves from sonar sensors. In several indoor experiments, integrating the eML approach with the mSP method achieved the best results in terms of map quality among various mapping approaches. We call this the maximum likelihood based on sub-maps (MLS) approach. The MLS map created using only two sonar sensors exhibited similar accuracy to the reference map, which was an accurate representation of the environment. 相似文献
17.
This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach. 相似文献
18.
Much research mainly focuses on the batch processing method (e.g. maximum likelihood method) when bearings-only multiple targets tracking of bistatic sonar system is considered. In this paper, the idea of recursive processing method is presented and employed, and corresponding data association algorithms, i.e. a multi-objective ant-colony-based optimization algorithm and an easy fast assignment algorithm are developed to solve the measurements-to-measurements and measurements-to-tracks data association problems of bistatic sonar system, respectively. Monte-Carlo simulations are induced to evaluate the effectiveness of the proposed methods. 相似文献
19.
Bozma O. Kuc R. 《IEEE transactions on pattern analysis and machine intelligence》1991,13(12):1260-1269
The physical properties of acoustic sensors are exploited to obtain information about the environment for sonar map building. A theoretical formulation for interpreting the sensor databases on the physical principles of acoustic propagation and reflection is presented. A characterization of the sonar scan that allows the differentiation of planes, corners, and edges in a specular environment is described. A single sensor mounted on an autonomous vehicle in a laboratory verifies the technique. The implications for sonar map building and the limitations of differentiating elements with one sensor are discussed 相似文献
20.
Autonomous topological modeling of a home environment and topological localization using a sonar grid map 总被引:1,自引:0,他引:1
This paper presents a method of autonomous topological modeling and localization in a home environment using only low-cost
sonar sensors. The topological model is extracted from a grid map using cell decomposition and normalized graph cut. The autonomous
topological modeling involves the incremental extraction of a subregion without predefining the number of subregions. A method
of topological localization based on this topological model is proposed wherein a current local grid map is compared with
the original grid map. The localization is accomplished by obtaining a node probability from a relative motion model and rotational
invariant grid-map matching. The proposed method extracts a well-structured topological model of the environment, and the
localization provides reliable node probability even when presented with sparse and uncertain sonar data. Experimental results
demonstrate the performance of the proposed topological modeling and localization in a real home environment. 相似文献