Mapping and Exploration of Complex Environments Using Persistent 3D Model

Fournier, Jonathan; Ricard, Benoit; Laurendeau, Denis

doi:10.1109/crv.2007.45

Cited by 23 publications

(13 citation statements)

References 10 publications

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“…Payeur et al (1997) used octrees to adapt occupancy grid mapping from 2D to 3D and thereby introduced a probabilistic way of modeling occupied and free space. A similar approach was used by Fournier et al (2007) and Pathak et al (2007). In contrast to the approach presented in this paper, however, the authors did not explicitly address the issues of map compression or bounded confidence in the map.…”

Section: Related Workmentioning

confidence: 86%

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

et al. 2013

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Three-dimensional models provide a volumetric representation of space which is important for a variety of robotic applications including flying robots and robots that are equipped with manipulators. In this paper, we present an open-source framework to generate volumetric 3D environment models. Our mapping approach is based on octrees and uses probabilistic occupancy estimation. It explicitly represents not only occupied space, but also free and unknown areas. Furthermore, we propose an octree map compression method that keeps the 3D models compact. Our framework is available as an open-source C++ library and has already been successfully applied in several robotics projects. We present a series of experimental results carried out with real robots and on publicly available real-world datasets. The results demonstrate that our approach is able to update the representation efficiently and models the data consistently while keeping the memory requirement at a minimum.

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Section: Related Workmentioning

confidence: 86%

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

et al. 2013

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“…In particular, Yguel et al proposed the use of sparse wavelets to model a 3D environment from range data [24], and Fournier et al use an octree representation to efficiently represent a 3D world model [3]. …”

Section: Related Workmentioning

confidence: 99%

Accurate rough terrain estimation with space-carving kernels

Hadsell¹,

Bagnell²,

Huber³

et al. 2009

Robotics: Science and Systems V

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Abstract-Accurate terrain estimation is critical for autonomous offroad navigation. Reconstruction of a 3D surface allows rough and hilly ground to be represented, yielding faster driving and better planning and control. However, data from a 3D sensor samples the terrain unevenly, quickly becoming sparse at longer ranges and containing large voids because of occlusions and inclines. The proposed approach uses online kernel-based learning to estimate a continuous surface over the area of interest while providing upper and lower bounds on that surface. Unlike other approaches, visibility information is exploited to constrain the terrain surface and increase precision, and an efficient gradient-based optimization allows for realtime implementation.

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“…However, generalizing a robot's map and localization techniques to three dimensions presents significant challenges in limiting memory consumption and required processing power. One approach to mitigate these issues involves the use of an octree based map representation [2,3,4,5,6,7]. This approach is able to accurately map large spaces with efficient memory usage.…”

Section: Introductionmentioning

confidence: 99%

Merging of octree based 3D occupancy grid maps

Jessup

Givigi

Beaulieu

2014

2014 IEEE International Systems Conference Proceedings

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A technique for merging 3D octree based occupancy grid maps is proposed and implemented. Octrees are a memory efficient way to represent a 3D environment by recursively subdividing space at multiple depths in a tree structure. The use of of an octree representation of a 3D environment allows large environments to be mapped while limiting the amount of memory used in comparison to other techniques. When multiple robots are used to map an environment a more accurate map of a larger space can be produced in less time. In this paper, the problem of merging octree based occupancy grid maps from independent robots into one global map of their environment is explored.Techniques are introduced to address information from sources coming from multiple depths in the map as well as relative transformations between maps that are not axis aligned. These techniques allow the octree representation of an environment to be extended to multiple robots. The application of these techniques is demonstrated by merging maps built by robots in a simulated environment. The contribution of this work lies in the introduction of a feasible method of merging memory efficient maps of a 3D environment. The results obtained in this paper demonstrate that the proposed strategies for octree based map mergers are valid.

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Mapping and Exploration of Complex Environments Using Persistent 3D Model

Cited by 23 publications

References 10 publications

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

OctoMap: an efficient probabilistic 3D mapping framework based on octrees

Accurate rough terrain estimation with space-carving kernels

Merging of octree based 3D occupancy grid maps

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