Journal ArticleDOI
CoSLAM: Collaborative Visual SLAM in Dynamic Environments
Danping Zou,Ping Tan +1 more
Reads0
Chats0
TLDR
Experimental results demonstrate that the vision-based simultaneous localization and mapping in dynamic environments with multiple cameras can work robustly in highly dynamic environments and produce more accurate results in static environments.Abstract:
This paper studies the problem of vision-based simultaneous localization and mapping (SLAM) in dynamic environments with multiple cameras. These cameras move independently and can be mounted on different platforms. All cameras work together to build a global map, including 3D positions of static background points and trajectories of moving foreground points. We introduce intercamera pose estimation and intercamera mapping to deal with dynamic objects in the localization and mapping process. To further enhance the system robustness, we maintain the position uncertainty of each map point. To facilitate intercamera operations, we cluster cameras into groups according to their view overlap, and manage the split and merge of camera groups in real time. Experimental results demonstrate that our system can work robustly in highly dynamic environments and produce more accurate results in static environments.read more
Citations
More filters
Posted Content
RGB-D SLAM in Dynamic Environments Using Point Correlations.
TL;DR: In this paper, a sparse graph is first created using Delaunay triangulation from all map points, and each edge represents the correlation between adjacent points and motion estimation is performed using only these points.
Journal ArticleDOI
Tracking 3-D Motion of Dynamic Objects Using Monocular Visual-Inertial Sensing
TL;DR: This paper proposes a novel method to resolve the object scale ambiguity in monocular vision in a geometric manner based on correlation analysis that enables accurate metric three-dimensional tracking of arbitrary objects without requiring any prior knowledge about the object shape or size.
Proceedings ArticleDOI
Collaborative localization and formation flying using distributed stereo-vision
TL;DR: This paper considers collaborative stereo-vision as a mean of localization for a fleet of micro-air vehicles (MAV) equipped with monocular cameras, inertial measurement units and sonar sensors.
Posted Content
MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System.
Steffen Urban,Stefan Hinz +1 more
TL;DR: This paper extends and improve upon a state-of-the-art SLAM to make it applicable to arbitrary, rigidly coupled multi-camera systems (MCS) using the MultiCol model and compares the robustness of the proposed method to a single camera version of the SLAM system.
Journal ArticleDOI
Real-Time Active SLAM and Obstacle Avoidance for an Autonomous Robot Based on Stereo Vision
TL;DR: A modified version of the so-called cognitive-based adaptive optimization algorithm is introduced for the robot to successfully complete its tasks in real time and avoid any local minima entrapment.
References
More filters
Proceedings ArticleDOI
Good features to track
Jianbo Shi,Tomasi +1 more
TL;DR: A feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world are proposed.
Proceedings ArticleDOI
Parallel Tracking and Mapping for Small AR Workspaces
Georg Klein,David W. Murray +1 more
TL;DR: A system specifically designed to track a hand-held camera in a small AR workspace, processed in parallel threads on a dual-core computer, that produces detailed maps with thousands of landmarks which can be tracked at frame-rate with accuracy and robustness rivalling that of state-of-the-art model-based systems.
Journal ArticleDOI
MonoSLAM: Real-Time Single Camera SLAM
TL;DR: The first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches is presented.
Journal ArticleDOI
Simultaneous localization and mapping: part I
TL;DR: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method.
Proceedings ArticleDOI
Real-time simultaneous localisation and mapping with a single camera
TL;DR: This work presents a top-down Bayesian framework for single-camera localisation via mapping of a sparse set of natural features using motion modelling and an information-guided active measurement strategy, in particular addressing the difficult issue of real-time feature initialisation via a factored sampling approach.