Proceedings ArticleDOI
Collaborative monocular SLAM with multiple Micro Aerial Vehicles
Christian Forster,Simon Lynen,Laurent Kneip,Davide Scaramuzza +3 more
- pp 3962-3970
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TLDR
This paper presents a framework for collaborative localization and mapping with multiple Micro Aerial Vehicles (MAVs) in unknown environments using an onboard, monocular visual odometry algorithm and is the first work on real-time collaborative monocular SLAM, which has also been applied to MAVs.Abstract:
This paper presents a framework for collaborative localization and mapping with multiple Micro Aerial Vehicles (MAVs) in unknown environments. Each MAV estimates its motion individually using an onboard, monocular visual odometry algorithm. The system of MAVs acts as a distributed preprocessor that streams only features of selected keyframes and relative-pose estimates to a centralized ground station. The ground station creates an individual map for each MAV and merges them together whenever it detects overlaps. This allows the MAVs to express their position in a common, global coordinate frame. The key to real-time performance is the design of data-structures and processes that allow multiple threads to concurrently read and modify the same map. The presented framework is tested in both indoor and outdoor environments with up to three MAVs. To the best of our knowledge, this is the first work on real-time collaborative monocular SLAM, which has also been applied to MAVs.read more
Citations
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Journal ArticleDOI
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José L. Neira,Ian Reid,John J. Leonard +7 more
TL;DR: What is now the de-facto standard formulation for SLAM is presented, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers.
Proceedings ArticleDOI
SVO: Fast semi-direct monocular visual odometry
TL;DR: A semi-direct monocular visual odometry algorithm that is precise, robust, and faster than current state-of-the-art methods and applied to micro-aerial-vehicle state-estimation in GPS-denied environments is proposed.
Journal ArticleDOI
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
TL;DR: This article presents ORB-SLAM3, the first system able to perform visual, visual-inertial and multimap SLAM with monocular, stereo and RGB-D cameras, using pin-hole and fisheye lens models, resulting in real-time robust operation in small and large, indoor and outdoor environments.
Journal ArticleDOI
A Survey on Aerial Swarm Robotics
TL;DR: The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping, and dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing.
Posted Content
Simultaneous Localization And Mapping: Present, Future, and the Robust-Perception Age.
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José L. Neira,Ian Reid,John J. Leonard +7 more
TL;DR: What is now the de-facto standard formulation for SLAM is presented, and a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers are reviewed.
References
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Journal ArticleDOI
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Proceedings ArticleDOI
Video Google: a text retrieval approach to object matching in videos
TL;DR: An approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video, represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion.
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.
Proceedings ArticleDOI
BRISK: Binary Robust invariant scalable keypoints
TL;DR: A comprehensive evaluation on benchmark datasets reveals BRISK's adaptive, high quality performance as in state-of-the-art algorithms, albeit at a dramatically lower computational cost (an order of magnitude faster than SURF in cases).
Proceedings ArticleDOI
G 2 o: A general framework for graph optimization
TL;DR: G2o, an open-source C++ framework for optimizing graph-based nonlinear error functions, is presented and demonstrated that while being general g2o offers a performance comparable to implementations of state-of-the-art approaches for the specific problems.