Download or read book A Novel Fusion Technique for 2D LIDAR and Stereo Camera Data Using Fuzzy Logic for Improved Depth Perception written by Harsh Saksena and published by . This book was released on 2021 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Obstacle detection, avoidance and path finding for autonomous vehicles requires precise information of the vehicle's system environment for faultless navigation and decision making. As such vision and depth perception sensors have become an integral part of autonomous vehicles in the current research and development of the autonomous industry. The advancements made in vision sensors such as radars, Light Detection And Ranging (LIDAR) sensors and compact high resolution cameras is encouraging, however individual sensors can be prone to error and misinformation due to environmental factors such as scene illumination, object reflectivity and object transparency. The application of sensor fusion in a system, by the utilization of multiple sensors perceiving similar or relatable information over a network, is implemented to provide a more robust and complete system information and minimize the overall perceived error of the system. 3D LIDAR and monocular camera are the most commonly utilized vision sensors for the implementation of sensor fusion. 3D LIDARs boast a high accuracy and resolution for depth capturing for any given environment and have a broad range of applications such as terrain mapping and 3D reconstruction. Despite 3D LIDAR being the superior sensor for depth, the high cost and sensitivity to its environment make it a poor choice for mid-range application such as autonomous rovers, RC cars and robots. 2D LIDARs are more affordable, easily available and have a wider range of applications than 3D LIDARs, making them the more obvious choice for budget projects. The primary objective of this thesis is to implement a smart and robust sensor fusion system using 2D LIDAR and a stereo depth camera to capture depth and color information of an environment. The depth points generated by the LIDAR are fused with the depth map generated by the stereo camera by a Fuzzy system that implements smart fusion and corrects any gaps in the depth information of the stereo camera. The use of Fuzzy system for sensor fusion of 2D LIDAR and stereo camera is a novel approach to the sensor fusion problem and the output of the fuzzy fusion provides higher depth confidence than the individual sensors provide. In this thesis, we will explore the multiple layers of sensor and data fusion that have been applied to the vision system, both on the camera and lidar data individually and in relation to each other. We will go into detail regarding the development and implementation of fuzzy logic based fusion approach, the fuzzification of input data and the method of selection of the fuzzy system for depth specific fusion for the given vision system and how fuzzy logic can be utilized to provide information which is vastly more reliable than the information provided by the camera and LIDAR separately.

Download or read book Stereo Vision and LIDAR Based Dynamic Occupancy Grid Mapping written by You Li and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent vehicles require perception systems with high performances. Usually, perception system consists of multiple sensors, such as cameras, 2D/3D lidars or radars. The works presented in this Ph.D thesis concern several topics on cameras and lidar based perception for understanding dynamic scenes in urban environments. The works are composed of four parts.In the first part, a stereo vision based visual odometry is proposed by comparing several different approaches of image feature detection and feature points association. After a comprehensive comparison, a suitable feature detector and a feature points association approach is selected to achieve better performance of stereo visual odometry. In the second part, independent moving objects are detected and segmented by the results of visual odometry and U-disparity image. Then, spatial features are extracted by a kernel-PCA method and classifiers are trained based on these spatial features to recognize different types of common moving objects e.g. pedestrians, vehicles and cyclists. In the third part, an extrinsic calibration method between a 2D lidar and a stereoscopic system is proposed. This method solves the problem of extrinsic calibration by placing a common calibration chessboard in front of the stereoscopic system and 2D lidar, and by considering the geometric relationship between the cameras of the stereoscopic system. This calibration method integrates also sensor noise models and Mahalanobis distance optimization for more robustness. At last, dynamic occupancy grid mapping is proposed by 3D reconstruction of the environment, obtained from stereovision and Lidar data separately and then conjointly. An improved occupancy grid map is obtained by estimating the pitch angle between ground plane and the stereoscopic system. The moving object detection and recognition results (from the first and second parts) are incorporated into the occupancy grid map to augment the semantic meanings. All the proposed and developed methods are tested and evaluated with simulation and real data acquired by the experimental platform “intelligent vehicle SetCar” of IRTES-SET laboratory.

Download or read book Data Fusion written by Lucien Wald and published by Presses des MINES. This book was released on 2002 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book establishes the fundamentals (particularly definitions and architectures) in data fusion. The second part of the book is devoted to methods for the fusion of images. It offers an in-depth presentation of standard and advanced methods for the fusion of multi-modality images.

Download or read book Improve Monocular and Stereo Depth Estimation with LiDAR Data written by 王尊玄 and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fusion of LIDAR with Stereo Camera Data an Assessment written by Joshua Veitch-Michaelis and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fusion of LIDAR with Stereo Camera Data written by J. L. Veitch-Michaelis and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Improving the Accuracy of Defocus based Depth Estimation Using Fuzzy Logic written by Cassandra Turner Swain and published by . This book was released on 1995 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book LiDAR and Camera Fusion in Autonomous Vehicles written by Jie Zhang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: LiDAR and camera can be an excellent complement to the advantages in an autonomous vehicle system. Various fusion methods have been developed for sensor fusion. Due to information lost, the autonomous driving system cannot navigate complex driving scenarios. When integrating the camera and LiDAR data, to account for loss of some detail of characters when using late fusion, we could choose a convolution neural network to fuse the features. However, the current sensor fusion method has low efficiency for the actual self-driving task due to the complex scenarios. To improve the efficiency and effectiveness of context fusion in high density traffic, we propose a new fusion method and architecture to combine the multi-model information after extracting the features from the LiDAR and camera. This new method is able to pay extra attention to features we want by allocating the weight during the feature extractor level.

Download or read book Feature Level Fusion of Laser Scanner and Video Data for Advanced Driver Assistance Systems written by Nico Kämpchen and published by . This book was released on 2007 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhance SLAM Performance with Tightly coupled Camera and Lidar Fusion written by 周執中 and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fusing Visual Odometry and Depth Completion written by Guilherme Venturelli Cavalheiro and published by . This book was released on 2019 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in technology indicate that autonomous vehicles and self-driving cats in particular may become commonplace in the near future. This thesis contributes to that scenario by studying the problem of depth perception based on sequences of camera images. We start by presenting a sensor fusion framework that achieves state-of-the-art performance when completing depth from sparse LiDAR measurements and a camera. Then, we study how the system performs under a variety of modifications of the sparse input until we ultimately replace LiDAR measurements with triangulations from a typical sparse visual odometry pipeline. We are then able to achieve a small improvement over the single image baseline and chart guidelines to assist in designing a system with even more substantial gains.

Download or read book Fusion for Object Detection written by Pan Wei and published by . This book was released on 2018 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a three-dimensional world, for perception of the objects around us, we not only wish to classify them, but also know where these objects are. The task of object detection combines both classification and localization. In addition to predicting the object category, we also predict where the object is from sensor data. As it is not known ahead of time how many objects that we have interest in are in the sensor data and where are they, the output size of object detection may change, which makes the object detection problem difficult. In this dissertation, I focus on the task of object detection, and use fusion to improve the detection accuracy and robustness. To be more specific, I propose a method to calculate measure of conflict. This method does not need external knowledge about the credibility of each source. Instead, it uses the information from the sources themselves to help assess the credibility of each source. I apply the proposed measure of conflict to fuse independent sources of tracking information from various stereo cameras. Besides, I propose a computational intelligence system for more accurate object detection in real–time. The proposed system uses online image augmentation before the detection stage during testing and fuses the detection results after. The fusion method is computationally intelligent based on the dynamic analysis of agreement among inputs. Comparing with other fusion operations such as average, median and non-maxima suppression, the proposed methods produces more accurate results in real-time. I also propose a multi–sensor fusion system, which incorporates advantages and mitigate disadvantages of each type of sensor (LiDAR and camera). Generally, camera can provide more texture and color information, but it cannot work in low visibility. On the other hand, LiDAR can provide accurate point positions and work at night or in moderate fog or rain. The proposed system uses the advantages of both camera and LiDAR and mitigate their disadvantages. The results show that comparing with LiDAR or camera detection alone, the fused result can extend the detection range up to 40 meters with increased detection accuracy and robustness.

Download or read book Introduction to GPS written by Ahmed El-Rabbany and published by Artech House. This book was released on 2002 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're looking for an up-to-date, easy-to-understand treatment of the GPS (Global Positioning System), this one-of-a-kind resource offers you the knowledge you need for your work, without bogging you down with advanced mathematics. It addresses all aspects of the GPS, emphasizes GPS applications, examines the GPS signal structure, and covers the key types of measurement being utilized in the field today.

Download or read book A Survey on 3D Cameras Metrological Comparison of Time of Flight Structured Light and Active Stereoscopy Technologies written by Silvio Giancola and published by Springer. This book was released on 2018-06-19 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a valuable resource to deeply understand the technology used in 3D cameras. In this book, the authors summarize and compare the specifications of the main 3D cameras available in the mass market. The authors present a deep metrological analysis of the main camera based on the three main technologies: Time-of-Flight, Structured-Light and Active Stereoscopy, and provide qualitative results for any user to understand the underlying technology within 3D camera, as well as practical guidance on how to get the most of them for a given application.

Download or read book Multisensor Data Fusion written by David Hall and published by CRC Press. This book was released on 2001-06-20 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Download or read book Computer Vision Metrics written by Scott Krig and published by Apress. This book was released on 2014-06-14 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more. Rather than providing ‘how-to’ source code examples and shortcuts, this book provides a counterpoint discussion to the many fine opencv community source code resources available for hands-on practitioners.

Download or read book Sensor and Data Fusion for Intelligent Transportation Systems written by Lawrence A. Klein and published by SPIE-International Society for Optical Engineering. This book was released on 2019 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monograph offers detailed descriptions of three of the widely applied data fusion techniques and their relevance to ITS (namely, Bayesian inference, Dempster-Shafer evidential reasoning, and Kalman filtering), and indicates directions for future research in the area of data fusion. The focus is on data fusion algorithms rather than on sensor and data fusion architectures, although the book does summarize factors that influence the selection of a fusion architecture and several architecture frameworks"--