Results 31 to 40 of about 162,677 (314)
A Robust and Efficient Loop Closure Detection Approach for Hybrid Ground/Aerial Vehicles
Frequent and dramatic viewpoint changes make loop closure detection of hybrid ground/aerial vehicles extremely challenging. To address this issue, we present a robust and efficient loop closure detection approach based on the state-of-the-art ...
Yutong Wang +3 more
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Loop Closure Detection Based on Differentiable Manifold
Loop closure detection is an important part of SLAM (simultaneous location and mapping), which can effectively reduce the cumulative error of the system after long period of exploration. The existing loop closure detection methods are mainly to evenly distribute the accumulated error in the robot trajectory, but the motion error of the actual robot is ...
Tianzhen Dong +5 more
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Simultaneous localization and mapping (SLAM) plays a crucial role in the field of intelligent mobile robots. However, the traditional Visual SLAM (VSLAM) framework is based on strong assumptions about static environments, which are not applicable to ...
Yang Wang +5 more
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This paper proposes a novel approach for appearance-based loop closure detection using incremental Bag of Words (BoW) with gradient orientation histograms.
Yuni Li, Wu Wei, Honglei Zhu
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In simultaneous localization and mapping (SLAM), loop closure detection is a significant yet still open problem. It contributes to construct a globally consistent and accurate map.
Haodong Xiang +5 more
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Detecting Loop Closure with Scene Sequences
This paper is concerned with "loop closing" for mobile robots. Loop closing is the problem of correctly asserting that a robot has returned to a previously visited area. It is a particularly hard but important component of the Simultaneous Localization and Mapping (SLAM) problem.
Ho, K, Newman, P
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Learning to detect loop closure from range data
Despite significant developments in the Simultaneous Localisation and Mapping (SLAM) problem, loop closure detection is still challenging in large scale unstructured environments. Current solutions rely on heuristics that lack generalisation properties, in particular when range sensors are the only source of information about the robot's surrounding ...
Granström, Karl +3 more
openaire +5 more sources
Humans maintain good memory and recognition capability of previous environments when they are learning about new ones. Thus humans are able to continually learn and increase their experience. It is also obvious importance for autonomous mobile robot. The
Shilang Chen +4 more
doaj +1 more source
Loop Closure Detection Based on Multi-Scale Deep Feature Fusion
Loop closure detection plays a very important role in the mobile robot navigation field. It is useful in achieving accurate navigation in complex environments and reducing the cumulative error of the robot’s pose estimation.
Baifan Chen +3 more
doaj +1 more source
Word ordering and document adjacency for large loop closure detection in 2D laser maps [PDF]
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Andrade-Cetto, Juan +2 more
core +2 more sources

