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Proceedings ArticleDOI

3D simultaneous localization and modeling from stereo vision

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TLDR
This work presents a new algorithm for determining the trajectory of a mobile robot and, simultaneously, creating a detailed volumetric 3D model of its workspace, which exclusively utilizes information provided by a single stereo vision system.
Abstract
This work presents a new algorithm for determining the trajectory of a mobile robot and, simultaneously, creating a detailed volumetric 3D model of its workspace. The algorithm exclusively utilizes information provided by a single stereo vision system, avoiding thus the use both of more costly laser systems and error-prone odometry. Six-degrees-of-freedom egomotion is directly estimated from images acquired at relatively close positions along the robot's path. Thus, the algorithm can deal with both planar and uneven terrain in a natural way, without requiring extra processing stages or additional orientation sensors. The 3D model is based on an octree that encapsulates clouds of 3D points obtained through stereo vision, which are integrated after each egomotion stage. Every point has three spatial coordinates referred to a single frame, as well as true-color components. The spatial location of those points is continuously improved as new images are acquired and integrated into the model.

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Citations
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Proceedings ArticleDOI

Stereo-Based Ego-Motion Estimation Using Pixel Tracking and Iterative Closest Point

TL;DR: A stereovision algorithm for real-time 6DoF ego-motion estimation, which integrates image intensity information and 3D stereo data in the well-known Iterative Closest Point (ICP) scheme, proving the method to be as accurate as effective for autonomous navigation purposes.
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Distributed metric calibration of ad hoc camera networks

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Robust 3D SLAM with a stereo camera based on an edge-point ICP algorithm

TL;DR: The proposed method estimates camera poses and builds detailed 3D maps robustly by aligning edge points between frames using the ICP algorithm and in indoor experiments, the method successfully built detailed3D maps even under noisy condition.
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Coverage algorithms for visual sensor networks

TL;DR: This work develops a distributed algorithm that outperforms the existing distributed algorithm with lower communication overhead, at the cost of coverage accuracy, and proposes a hierarchical algorithm where cameras are decomposed into neighborhoods that coordinate their coverage using an elected local coordinator.
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Evaluation of Navigation Sensors in Fire Smoke Environments

TL;DR: In this article, an experimental study was performed to quantify the performance of eleven common robotic navigation rangefinding technologies and camera systems in fire smoke environments, including IR cameras, two visible cameras and two sonar systems.
References
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Journal ArticleDOI

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TL;DR: The paper proves that a solution to the SLAM problem is indeed possible and discusses a number of key issues raised by the solution including suboptimal map-building algorithms and map management.
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.
Book ChapterDOI

Estimating uncertain spatial relationships in robotics

TL;DR: A representation for spatial information, called the stochastic map, and associated procedures for building it, reading information from it, and revising it incrementally as new information is obtained, providing a general solution to the problem of estimating uncertain relative spatial relationships.