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Lightweight Object-level Topological Semantic Mapping and Long-term Global Localization based on Graph Matching [article]

Fan Wang, Chaofan Zhang, Fulin Tang, Hongkui Jiang, Yihong Wu, Yong Liu
2022 arXiv   pre-print
Based on the proposed map, the robust localization is achieved by constructing a novel local semantic scene graph descriptor, and performing multi-constraint graph matching to compare scene similarity.  ...  In this paper, we present a novel lightweight object-level mapping and localization method with high accuracy and robustness.  ...  robust localization based on semantic graph description of the local scene, we calls it an Object-level Topological Semantic Map(OLTSM).  ... 
arXiv:2201.05977v1 fatcat:od6y7drcnncxncdgfjjsaum64a

Object-Based Reliable Visual Navigation for Mobile Robot

Fan Wang, Chaofan Zhang, Wen Zhang, Cuiyun Fang, Yingwei Xia, Yong Liu, Hao Dong
2022 Sensors  
Firstly, a lightweight object-level topological semantic map is constructed to release the dependence on the precise metric map, where the semantic associations between objects are stored via graph memory  ...  Then, we propose an object-based heuristic graph search method to select the global topological path with the optimal and shortest characteristics.  ...  Gibson License: /assets/GDS_agreement.pdf (accessed on 10 January 2022).  ... 
doi:10.3390/s22062387 pmid:35336558 pmcid:PMC8949785 fatcat:qszzhukvwbeublsqqexi6trnda

Fast hybrid relocation in large scale metric-topologic-semantic map

Romain Drouilly, Patrick Rives, Benoit Morisset
2014 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems  
It consists of local sub-maps connected through two topological layers at metric and semantic levels. Semantic information is used to build concise local graph-based descriptions of sub-maps.  ...  We present a new hybrid metric-topological-semantic map structure, called MTS-map, that allows a fine metric-based navigation and fast coarse query-based localisation.  ...  Vision-based localization is studied for a long time and the use of omni-images dates back to early 90's [11] .  ... 
doi:10.1109/iros.2014.6942804 dblp:conf/iros/DrouillyRM14 fatcat:phep3udr3nebxgpm3hovug4ueq

Semantic Graph Based Place Recognition for 3D Point Clouds [article]

Xin Kong, Xuemeng Yang, Guangyao Zhai, Xiangrui Zhao, Xianfang Zeng, Mengmeng Wang, Yong Liu, Wanlong Li, Feng Wen
2020 arXiv   pre-print
Unlike most of the existing methods that focus on extracting local, global, and statistical features of raw point clouds, our method aims at the semantic level that can be superior in terms of robustness  ...  Inspired by the perspective of humans, who recognize scenes through identifying semantic objects and capturing their relations, this paper presents a novel semantic graph based approach for place recognition  ...  Robustness Test Occlusion: In a real scenario, dynamic objects (person, vehicle, etc.) inevitably occur during long-term localization, which brings occlusion in LiDAR point clouds.  ... 
arXiv:2008.11459v1 fatcat:fcnzohqpmzfizjcgmi2n3wdtk4

A survey of image semantics-based visual simultaneous localization and mapping: Application-oriented solutions to autonomous navigation of mobile robots

Linlin Xia, Jiashuo Cui, Ran Shen, Xun Xu, Yiping Gao, Xinying Li
2020 International Journal of Advanced Robotic Systems  
We argue that multiscaled map representation, object simultaneous localization and mapping system, and deep neural network-based simultaneous localization and mapping pipeline design could be effective  ...  By contrast, the semantic simultaneous localization and mapping that is characterized by high-level environmental perception has apparently opened the door to apply image semantics to efficiently estimate  ...  Thus, we believe the introduction of time-varying semantic maps helps for both long-term and dynamic localization.  ... 
doi:10.1177/1729881420919185 fatcat:zatdrexf2zdydihx7smi4gmlvi

Robust Loop Closure Detection Integrating Visual–Spatial–Semantic Information via Topological Graphs and CNN Features

Yuwei Wang, Yuanying Qiu, Peitao Cheng, Xuechao Duan
2020 Remote Sensing  
the topological graphs for graph matching.  ...  Loop closure detection is a key module for visual simultaneous localization and mapping (SLAM).  ...  We are also very grateful for the dataset provided by the open source map service of Mapillary. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12233890 fatcat:mjlzmdsoqbak7f5aq6rhheqoqi

From SLAM to Situational Awareness: Challenges and Survey [article]

Hriday Bavle, Jose Luis Sanchez-Lopez, Eduardo F. Schmidt, Holger Voos
2021 arXiv   pre-print
ideas such as sensing, perception, sensor fusion, state estimation, localization and mapping, spatial AI, etc.  ...  We see this as an opportunity, and provide our vision for future research on robotic situational awareness.  ...  Object-based Metric-Semantic SLAM build a map of the instances of the different detected object classes on the given input measurements.  ... 
arXiv:2110.00273v2 fatcat:kiimumlvnnhfjkgiegvf66m6ji

Visual Localizer: Outdoor Localization Based on ConvNet Descriptor and Global Optimization for Visually Impaired Pedestrians

Shufei Lin, Ruiqi Cheng, Kaiwei Wang, Kailun Yang
2018 Sensors  
To further improve the robustness of image matching, we utilize the network flow model as a global optimization of image matching.  ...  Facing these practical challenges, we propose Visual Localizer, which is composed of ConvNet descriptor and global optimization, to achieve robust visual localization for assisted navigation.  ...  Global Optimization of Image Matching Network flow model based on data association graph was used to achieve robust visual localization across seasons [23] .  ... 
doi:10.3390/s18082476 pmid:30065208 fatcat:apw2i5yzcrgd5kolmh5zh4e464

A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks [article]

Baichuan Huang, Jun Zhao, Jingbin Liu
2020 arXiv   pre-print
Simultaneous Localization and Mapping (SLAM) achieves the purpose of simultaneous positioning and map construction based on self-perception.  ...  For Lidar or visual SLAM, the survey illustrates the basic type and product of sensors, open source system in sort and history, deep learning embedded, the challenge and future.  ...  X-View [221] leverages semantic graph descriptor matching for global localization, enabling localization under drastically different view-points.  ... 
arXiv:1909.05214v4 fatcat:itnluvkewfd6fel7x65wdgig3e

Feature-based visual simultaneous localization and mapping: a survey

Rana Azzam, Tarek Taha, Shoudong Huang, Yahya Zweiri
2020 SN Applied Sciences  
Visual features can be seen at different levels; low-level features like points and edges, middle-level features like planes and blobs, and high-level features like semantically labeled objects.  ...  Visual simultaneous localization and mapping (SLAM) has attracted high attention over the past few years.  ...  For instance, localization methods based on observation of low-level features have achieved a high level of maturity in terms of accuracy and efficiency.  ... 
doi:10.1007/s42452-020-2001-3 fatcat:g7445is2cbdmdmllewkyp7giby

Role of Deep Learning in Loop Closure Detection for Visual and Lidar SLAM: A Survey

Saba Arshad, Gon-Woo Kim
2021 Sensors  
global map.  ...  Based on those challenges, deep learning-based methods were reviewed where the identified challenges are tackled focusing on the methods providing long-term autonomy in various conditions such as changing  ...  Object-level semantic information is extracted using Faster R-CNN [130] , pretrained on the COCO dataset [131] .  ... 
doi:10.3390/s21041243 pmid:33578695 pmcid:PMC7916334 fatcat:25xo5gtxnfb43modwzuncytqj4

The Revisiting Problem in Simultaneous Localization and Mapping: A Survey on Visual Loop Closure Detection [article]

Konstantinos A. Tsintotas, Loukas Bampis, Antonios Gasteratos
2022 arXiv   pre-print
This problem has long been acknowledged for its challenging nature in simultaneous localization and mapping (SLAM), wherein the robot needs to correctly associate the incoming sensory data to the database  ...  In this article, visual loop closure detection, which formulates a solution based solely on appearance input data, is surveyed.  ...  Detecting and dealing with dynamic objects is a requisite to estimate stable maps, useful for long-term applications.  ... 
arXiv:2204.12831v1 fatcat:x7rmwmzhwfbwhhyxg6e6k5aq5u

Grid resource discovery based on semantically linked virtual organizations

Juan Li
2010 Future generations computer systems  
Specifically, we use a semantics-aware topology construction method to group similar nodes to form a semantic smallworld.  ...  With the small-world topology constructed, resource-discovery queries will be propagated only between semantically related nodes, which greatly improves the efficiency and accuracy of resource discovery  ...  Our semantic topology construction is based on this idea. In our system, a node distinguishes three kinds of neighbors based on their semantic similarity.  ... 
doi:10.1016/j.future.2009.07.011 fatcat:m3cfvenygbeyxoiqwsycf2mqb4

Deep Learning on Point Clouds and Its Application: A Survey

Weiping Liu, Jia Sun, Wanyi Li, Ting Hu, Peng Wang
2019 Sensors  
The applications related to point cloud feature learning, including 3D object classification, semantic segmentation, and 3D object detection, are introduced, and the datasets and evaluation metrics are  ...  Being unordered and irregular, many researchers focused on the feature engineering of the point cloud.  ...  ., local-based, global-based, and hybrid-based. Garcia et al. 2017 [40] The semantic segmentation methods based on deep learning.  ... 
doi:10.3390/s19194188 fatcat:s64jm5t5xbhzjk7jxgrodehucu

Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs [article]

Antoni Rosinol, Andrew Violette, Marcus Abate, Nathan Hughes, Yun Chang, Jingnan Shi, Arjun Gupta, Luca Carlone
2021 arXiv   pre-print
Kimera includes state-of-the-art techniques for visual-inertial SLAM, metric-semantic 3D reconstruction, object localization, human pose and shape estimation, and scene parsing.  ...  This mental model captures geometric and semantic aspects of the scene, describes the environment at multiple levels of abstractions (e.g., objects, rooms, buildings), includes static and dynamic entities  ...  Long-term Autonomy. DSGs provide a natural way to "forget" or retain information in long-term autonomy.  ... 
arXiv:2101.06894v3 fatcat:56ovm7auwbbc3fkqewfhilog54
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