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The recent adoption of the Robot Operating System (ROS) as a software standard in robotics has contributed to novel solutions for several problems on the area. One such problem is known as Simultaneous Localization and Mapping (SLAM), for which a number of algorithms from different classes are available as ROS packages ready to be used on any compatible robot. Considering that there is often a need...
In this paper, we introduce a heterogeneous stereo sensing system that aim to solve the real life difficulties in vision based autonomous navigation. The common practice for vision autonomous robotics navigation is to concatenate camera(s), SLAM and path planning modules. We observe an dilemma where visual SLAM demand wide angle cameras to perform robust tracking and path planning require sensor to...
Up to the present day, GPS signals are the key component in almost all outdoor navigation tasks of robotic platforms. To obtain the platform pose, comprising the position as well as the orientation, and receive information at a higher frequency, the GPS signals are commonly used in a GPS-corrected inertial navigation system (INS). The GPS is a critical single point of failure, especially for autonomous...
This paper presents a new line based 6-DOF monocular algorithm that uses the iSAM2, a point-based Graph SLAM approach. We extend iSAM2 to minimize the reprojection error of the line features to solve the line-based SLAM problem. A specific line representation is exploited that combines the Plücker Coordinates and the Cayley representation. The Plücker Coordinates are used for the 3D line projection...
ORB-SLAM2 is one of the better-known open source SLAM implementations available. However, the dependence of visual features causes it to fail in featureless environments. With the present work, we propose a new technique to improve visual odometry results given by ORB-SLAM2 using a tightly Sensor Fusion approach to integrate camera and odometer data. In this work, we use odometer readings to improve...
This paper presents a fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads. We build multiple vision-based maps and use them at the same time in localization phase. For the mapping phase, visual maps are built by employing ORB-SLAM and accurate metric positioning from LiDAR-based NDT scan matching. This external positioning is utilized to correct...
A method that optimizes visual odometry, especially using visual odometry in the scene with absence of features is proposed in this paper. First, in order to estimate the pose of camera when the effect of using feature-based method is not good enough, direct method is implemented as the solution. Second, comparing with traditional visual odometry method, this method takes the environment restriction...
There are many methods for 3D simultaneous localization and mapping(SLAM) such like ORB-SLAM, LSD-SLAM and so on when we use camera as sensor. However for laser range finder, there are few algorithms for SLAM, especially for 3DSLAM. Besides, the accuracy and robustness of 3D SLAM is still not enough by using conventional methods for laser range finder. A very famous algorithm for using laser range...
We propose a novel diminished reality method which is able to (i) automatically recognize the region to be diminished, (ii) work with a single RGB-D sensor, and (iii) work without pre-processing to generate a 3D model of the target scene by utilizing SLAM, segmentation, and recognition framework. Especially, regarding the recognition of the area to be diminished, our method is able to maintain high...
In Augmented Reality (AR) environment, realistic interactions between the virtual and real objects play a crucial role in user experience. Much of recent advances in AR has been largely focused on developing geometry-aware environment, but little has been done in dealing with interactions at the semantic level. High-level scene understanding and semantic descriptions in AR would allow effective design...
Feature extraction is a key component of a Monocular Simultaneous Localization and Mapping (Monocular SLAM) system which permits to extract features and can also reliably track them over frames. In this paper, a novel approach for Monocular SLAM is proposed. This approach uses the information on the camera displacement and image saliency to adequately extract stable and suitable features, ones that...
Camera pose estimation is a fundamental problem of Augmented Reality and 3D reconstruction systems. Recently, despite the new better performing direct methods being developed, state-of-the-art methods are still estimating erroneous poses due to sensor noise, environmental conditions and challenging trajectories. Adding a back-end mapping process, SLAM systems achieve better performance and are more...
Monocular ORB-SLAM has been proved to be one of the best open-source SLAM method. However, it is still unsatisfying especially in low illumination indoor environment, which is caused by scale recovery and wrong feature matching. In this paper, we proposed a vehicle model based monocular ORBSLAM method supplemented by April-Tag to improve the performance of original algorithm. This approach is practical...
This paper proposes a moving object detection algorithm which can handle videos taken by a moving camera in the presence of pronounced parallax. The paper considers the idea that objects in a image can be considered to be spatially distributed across multiple planes, the movement of each of which can be estimated using a Visual Odometry (VO) algorithm. For each plane, a Homography matrix between consecutive...
This paper proposes a method that realizes moving object detection (MOD) and static obstacle detection (SOD) in real time utilizing the fisheye cameras of the around viewing system (AVM). The topview of the AVM is used to calculate the vehicles movement between two frames using homograph estimation. Image features are detected and tracked evenly using cell detection technique. Then the features are...
In this article, we focus on how to fuse two systems between SLAM and UAV. The main contribution is that using the UAV attitude controller provides a reliable initial value for the SLAM system, which makes the direct method of SLAM more quickly and effective converge. The UAV position controller increases the stability by receiving the exact local information from SLAM. That allows two independent...
Monocular visual odometry algorithm has been widely used to estimate the pose of aerial robots in GPS denied environments. However, the pure visual system usually has poor robustness in large scale environments. This paper presents a pose estimation algorithm which fuses monocular visual and inertial data using the monocular ORB-SLAM algorithm as the visual framework. Firstly, the scale estimation...
Loop closure detection is important in simultaneous localization and mapping (SLAM) systems. In this paper, Generative Adversarial Networks (GAN), an unsupervised deep architecture is employed to detect the loop closure for vision-based SLAM systems. Instead of extracting handcrafted features like SIFT, SURF or ORB. Generative Adversarial Networks are based on image features. Similar to the task about...
A fast method for mobile robot 3D SLAM (simultaneous localization and mapping) is presented to address the problem of 3D modeling in complex indoor environment. According to the camera calibration model and the image feature extraction and matching procedure, the association between two 3D point clouds can be established. On the basis of the RANSAC (random sample consensus) algorithm, the correspondence...
This paper presents a novel strategy addressing visual SLAM with enhancement of data association method. Hyper graph theory and transformation was incorporated within cooperative visual SLAM. The research presented a synthetic approach to fulfill a cooperative data association and fusion strategy for multiple UAVs equipped with stereo vision cameras encountered with indistinct imaging, where conventional...
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