Adaptive rectangular cuboids for 3D mapping

Khan, Sheraz; Wollherr, Dirk; Buss, Martin

doi:10.1109/icra.2015.7139480

Cited by 11 publications

(10 citation statements)

References 16 publications

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“…They used axis-aligned rectangular cuboids to model the large-scale 3D environment, wherein computational and memory efficiencies were largely reduced compared with those in octree-based 3D maps. Later, in [17], they extended previous works by adding a fusion process that modifies the resolution of grid cells in an incremental manner. Their evaluation results show that the fusion process effectively reduces the number of grid cells required by the occupancy grid.…”

Section: Related Workmentioning

confidence: 99%

Efficient Planar Surface-Based 3D Mapping Method for Mobile Robots Using Stereo Vision

Guo

Dai

et al. 2019

IEEE Access

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Environmental mapping plays an important role in the field of robotics. Conventional voxel-based occupancy grid models largely reduce system mapping efficiency for huge quantities of grid cells. This paper presents an efficient method of 3D grid modeling using stereo vision based on planar surfaces. This method first uses matching key feature points with a multi-random sample consensus algorithm to estimate plane parameters and then clusters pre-processed point cloud data located on the same plane. Next, a split and combining algorithm is used to generate 3D planar grid approximation representations of the environment. The occupancy probabilities of grid cells are estimated and updated by using the Kullback-Leibler divergence. Finally, a series of experiments including map qualitative analysis and performance tests, are adopted to evaluate the presented method in indoor and outdoor environments. The results of the experiments and performance evaluation illustrate the capabilities of our approach in generating efficient 3D maps. INDEX TERMS 3D mapping, planar surface, mobile robots, stereo vision, occupancy grid models.

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Section: Related Workmentioning

confidence: 99%

Efficient Planar Surface-Based 3D Mapping Method for Mobile Robots Using Stereo Vision

Guo

Dai

et al. 2019

IEEE Access

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“…From the robotics community perspective, conventional 3D urban mapping approaches usually propose to use LiDAR or camera separately but a minority has recently exploited both data sources to build dense textured maps (Romanoni et al, 2017). In the literature, both image-based methods (Wu, 2013, Litvinov and Lhuillier, 2014, Romanoni and Matteucci, 2015 and LiDARbased methods (Hornung et al, 2013, Khan et al, 2015 often represent the map as a point cloud or a mesh relying only on Figure 1. The texturing pipeline geometric properties of the scene and discarding interesting photometric cues while a faithful 3D textured mesh representation would be useful for not only navigation and localization but also for photo-realistic accurate modeling and visualization.…”

Section: Related Workmentioning

confidence: 99%

Large Scale Textured Mesh Reconstruction From Mobile Mapping Images and Lidar Scans

Boussaha¹,

Vallet²,

Rives³

2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS). First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points) and photometry (images). Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014) is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17&thinsp;km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.

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“…Finally, 3D mapping approaches have been proposed in order to provide a complete solution to environment representation. A multiresolution cuboid representation, based on the incremental fusion of grid cells, is proposed in [6]- [7]. The Octomap approach proposed by Hornung et al [8], a probabilistic representation based on octrees, allows 3D multiresolution representations and querying.…”

Section: Related Workmentioning

confidence: 99%

HMAPs - Hybrid Height- Voxel Maps for Environment Representation

Garrote

Premebida

David

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents a hybrid 3D-like grid-based mapping approach, that we called HMAP, used as a reliable and efficient 3D representation of the environment surrounding a mobile robot. Considering 3D point-clouds as input data, the proposed mapping approach addresses the representation of height-voxel (HVoxel) elements inside the HMAP, where free and occupied space is modeled through HVoxels, resulting in a reliable method for 3D representation. The proposed method corrects some of the problems inherent to the representation of complex environments based on 2D and 2.5D representations, while keeping an updated grid representation. Additionally, we also propose a complete pipeline for SLAM based on HMAPs. Indoor and outdoor experiments were carried out to validate the proposed representation using data from a Microsoft Kinect One (indoor) and a Velodyne VLP-16 LiDAR (outdoor). The obtained results show that HMAPs can provide a more detailed view of complex elements in a scene when compared to a classic 2.5D representation. Moreover, validation of the proposed SLAM approach was carried out in an outdoor dataset with promising results, which lay a foundation for further research in the topic.

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Adaptive rectangular cuboids for 3D mapping

Cited by 11 publications

References 16 publications

Efficient Planar Surface-Based 3D Mapping Method for Mobile Robots Using Stereo Vision

Efficient Planar Surface-Based 3D Mapping Method for Mobile Robots Using Stereo Vision

Large Scale Textured Mesh Reconstruction From Mobile Mapping Images and Lidar Scans

HMAPs - Hybrid Height- Voxel Maps for Environment Representation

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