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Article
Computer Science, Artificial Intelligence
Xieyuanli Chen et al.
Summary: The paper introduces a modified Siamese network for estimating the similarity between pairs of LiDAR scans, which can be used for loop closing in SLAM and global localization in autonomous systems. The approach utilizes a deep neural network to exploit cues generated from LiDAR data, demonstrating superior performance and generalization in different environments. The method effectively detects loop closures and reliably localizes vehicles globally in urban environments using LiDAR data collected in various seasons.
Article
Computer Science, Information Systems
Jeff Johnson et al.
Summary: This paper addresses the issue of better utilizing GPUs for similarity search tasks, proposing a novel design for k-selection which outperforms existing approaches by large margins. The implementation achieves up to 55 percent of theoretical peak performance and enables significantly faster nearest neighbor implementations on GPU. It also allows for the construction of high accuracy k-NN graphs on large datasets in a fraction of the time compared to prior methods.
IEEE TRANSACTIONS ON BIG DATA
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Le Hui et al.
Summary: This paper proposes a Pyramid Point Cloud Transformer Network (PPT-Net) to learn discriminative global descriptors from point clouds for efficient retrieval. By developing a pyramid point transformer module and a pyramid VLAD module, the method extracts discriminative local features and aggregates multi-scale feature maps to achieve state-of-the-art results in point cloud based place recognition task.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Kavisha Vidanapathirana et al.
Summary: Place Recognition enables the estimation of a globally consistent map and trajectory by providing non-local constraints in SLAM. The proposed method, Locus, uses 3D LiDAR point clouds in large-scale environments and outperforms state-of-the-art methods on the KITTI dataset. It demonstrates robustness in challenging situations such as occlusions and viewpoint changes in 3D LiDAR point clouds.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Zhicheng Zhou et al.
Summary: This paper introduces a novel approach named NDT-Transformer for real-time and large-scale place recognition using 3D point clouds. By utilizing the NDT representation and NDT-Transformer network, the learned global descriptors are enriched with geometrical and contextual information, achieving significant improvements in place recognition performance.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Xieyuanli Chen et al.
Summary: In this paper, range images from 3D LiDAR scans are utilized for accurate localization in large-scale outdoor environments. The proposed observation model integrated into a Monte Carlo localization framework achieves better performance and generalization ability in tracking vehicle pose online at the LiDAR sensor frame rate across different environments.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Proceedings Paper
Automation & Control Systems
Andrei Cramariuc et al.
Summary: This paper presents a method that combines color and semantic data for mapping and localization, improving accuracy and robustness. The fusion approach demonstrated advantages over traditional methods, enabling more high-accuracy global localizations and accurate real-time pose estimates.
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2021)
Proceedings Paper
Automation & Control Systems
Lin Li et al.
Summary: The study proposes a novel place recognition method that uses semantics to represent scenes more effectively, while also considering translation between point clouds to improve matching accuracy.
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Stephen Hausler et al.
Summary: Visual Place Recognition is a challenging task that requires dealing with appearance and viewpoint changes in a changing world. Patch-NetVLAD introduces a novel approach that combines local and global descriptor methods to achieve superior performance and computational efficiency, making it suitable for enhancing both stand-alone place recognition capabilities and SLAM systems.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Yan Xia et al.
Summary: This paper introduces a novel self-attention and orientation encoding network (SOE-Net) for handling place recognition from point cloud data, achieving superior performance by fully exploring the relationship between points and incorporating long-range context into point-wise local descriptors. Additionally, a new loss function called HPHN quadruplet is proposed, which outperforms commonly used metric learning losses.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Jacek Komorowski Warsaw
Summary: The paper introduces a learning-based method, MinkLoc3D, for computing discriminative 3D point cloud descriptors for place recognition. The method utilizes sparse voxelized point cloud representation and sparse 3D convolutions to achieve improved performance, outperforming current state-of-the-art methods in standard benchmarks.
2021 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2021)
(2021)
Article
Computer Science, Artificial Intelligence
Xinyu Huang et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2020)
Proceedings Paper
Automation & Control Systems
Han Wang et al.
2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2020)
Article
Robotics
Olga Vysotska et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Zhe Liu et al.
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Mikaela Angelina Uy et al.
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)
(2018)
Article
Robotics
Stephanie Lowry et al.
IEEE TRANSACTIONS ON ROBOTICS
(2016)
Article
Robotics
Olga Vysotska et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2016)
Article
Robotics
Gaurav Pandey et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2011)
