Real-Time Photometric Calibrated Monocular Direct Visual SLAM

Liu, Peixin; Yuan, Xianfeng; Zhang, Chengjin; Song, Yong; Chuanzheng, Liu; Li, Ziyan

doi:10.3390/s19163604

Cited by 9 publications

(4 citation statements)

References 27 publications

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“… Fault diagnosis of vehicle motion sensors (1): [ 31 ]. Vehicle positioning and path planning (5) Simultaneous Localization and Mapping (1): [ 32 ]. Vehicle localization (3): [ 33 , 34 , 35 ].…”

Section: Special Issue On Intelligent Vehiclesmentioning

confidence: 99%

See 1 more Smart Citation

Sensors and Sensing for Intelligent Vehicles

Llorca

Daza

Hernández

et al. 2020

Sensors

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Over the past decades, both industry and academy have made enormous advancements in the field of intelligent vehicles, and a considerable number of prototypes are now driving our roads, railways, air and sea autonomously. However, there is still a long way to go before a widespread adoption. Among all the scientific and technical problems to be solved by intelligent vehicles, the ability to perceive, interpret, and fully understand the operational environment, as well as to infer future states and potential hazards, represent the most difficult and complex tasks, being probably the main bottlenecks that the scientific community and industry must solve in the coming years to ensure the safe and efficient operation of the vehicles (and, therefore, their future adoption). The great complexity and the almost infinite variety of possible scenarios in which an intelligent vehicle must operate, raise the problem of perception as an "endless" issue that will always be ongoing. As a humble contribution to the advancement of vehicles endowed with intelligence, we organized the Special Issue on Intelligent Vehicles. This work offers a complete analysis of all the mansucripts published, and presents the main conclusions drawn.

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Section: Special Issue On Intelligent Vehiclesmentioning

confidence: 99%

“…In [ 32 ], an enhanced visual SLAM algorithm based on the sparse direct method is proposed to deal with illumination sensitivity problems of mobile ground equipment. The presented procedure can be described as follows.…”

Section: Vehicle Positioning and Path Planningmentioning

confidence: 99%

Sensors and Sensing for Intelligent Vehicles

Llorca

Daza

Hernández

et al. 2020

Sensors

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“…For example, Zhu et al [ 24 ] proposed a photometric transfer net (PTNet), which is trained to pixel-wisely remove brightness discrepancies between two frames without ruining the context information, to overcome the problem of brightness discrepancies. Liu et al [ 25 ] proposed an enhanced visual SLAM algorithm based on the sparse direct method to solve the illumination sensitivity problem. Sheng et al [ 26 ] filtered out the dynamic objects based on the semantic information to improve the positioning accuracy and robustness of DSO [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

A Variable Radius Side Window Direct SLAM Method Based on Semantic Information

Chen

Mutabazi

et al. 2022

Computational Intelligence and Neuroscience

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Simultaneous Localization and Mapping (SLAM) is a challenging and key issue in the mobile robotic fields. In terms of the visual SLAM problem, the direct methods are more suitable for more expansive scenes with many repetitive features or less texture in contrast with the feature-based methods. However, the robustness of the direct methods is weaker than that of the feature-based methods. To deal with this problem, an improved direct sparse odometry with loop closure (LDSO) is proposed, where the performance of the SLAM system under the influence of different imaging disturbances of the camera is focused on. In the proposed method, a method based on the side window strategy is proposed for preprocessing the input images with a multilayer stacked pixel blender. Then, a variable radius side window strategy based on semantic information is proposed to reduce the weight of selected points on semistatic objects, which can reduce the computation and improve the accuracy of the SLAM system based on the direct method. Various experiments are conducted on the KITTI dataset and TUM RGB-D dataset to test the performance of the proposed method under different camera imaging disturbances. The quantitative and qualitative evaluations show that the proposed method has better robustness than the state-of-the-art direct methods in the literature. Finally, a real-world experiment is conducted, and the results prove the effectiveness of the proposed method.

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“…The first idea is to apply feature-based methods (Mouats et al, 2015;Poujol et al, 2016); however, the consistency of feature descriptors cannot be guaranteed in consecutive frames. The second idea is to apply direct methods to raw image data (Papachristos et al, 2017;Shin & Kim, 2019); however, the requirement of photometric consistency is no longer satisfied due to temperature drift, and method, such as photometric compensation (Liu et al, 2019), is difficult to apply.…”

Section: Introductionmentioning

confidence: 99%

EIL‐SLAM: Depth‐enhanced edge‐based infrared‐LiDAR SLAM

Chen

Wang

Chen

et al. 2021

Journal of Field Robotics

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Traditional simultaneous localization and mapping (SLAM) approaches that utilize visible cameras or light detection and rangings (LiDARs) frequently fail in dusty, lowtextured, or completely dark environments. To address this problem, this study proposes a novel approach by tightly coupling perception data from a thermal infrared camera and a LiDAR based on the advantages of the former. However, applying a thermal infrared camera directly to existing SLAM frameworks is difficult because of the sensor differences. Thus, a new infrared-visual odometry method is developed by utilizing edge points as features to ensure the robustness of the state estimation. Furthermore, an edge-based infrared-LiDAR SLAM framework is developed to generate a dense depth map for recovering visual scale and to provide realtime pose estimation at the same time throughout the day. An infrared-visual and LiDAR-integrated place recognition method is also introduced to achieve robust loop closure. Finally, several experiments are performed to illustrate the effectiveness of the proposed approach.

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Real-Time Photometric Calibrated Monocular Direct Visual SLAM

Cited by 9 publications

References 27 publications

Sensors and Sensing for Intelligent Vehicles

Sensors and Sensing for Intelligent Vehicles

A Variable Radius Side Window Direct SLAM Method Based on Semantic Information

EIL‐SLAM: Depth‐enhanced edge‐based infrared‐LiDAR SLAM

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