6D SLAM—3D mapping outdoor environments

Nüchter, Andreas; Lingemann, Kai; Hertzberg, Joachim; Surmann, Hartmut

doi:10.1002/rob.20209

Cited by 395 publications

(250 citation statements)

References 26 publications

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“…The occupied space in the environment is then modeled by the 3D point clouds returned by range sensors such as laser range finders or stereo cameras. This point cloud approach has been used in several 3D SLAM systems such as those presented by Cole and Newman (2006) as well as in the SLAM approach of Nüchter et al (2007). The drawbacks of this method are that neither free space nor unknown areas are modeled and that sensor noise and dynamic objects cannot be dealt with directly.…”

Section: Related Workmentioning

confidence: 99%

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: 99%

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

et al. 2013

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“…[9]) where there are physical, man-made structures that assist in the registration of 3d scans, improving the quality of the resulting maps. Other examples include mapping solutions for off-road autonomous car driving [13], mining operations [5] and autonomous road inspection [8].…”

Section: Related Workmentioning

confidence: 99%

Evaluation of Laser Range-Finder Mapping for Agricultural Spraying Vehicles

Moreno

Cielniak

Duckett

2014

Towards Autonomous Robotic Systems

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Abstract. In this paper, we present a new application of laser rangefinder sensing to agricultural spraying vehicles. The current generation of spraying vehicles use automatic controllers to maintain the height of the sprayer booms above the crop. However, these control systems are typically based on ultrasonic sensors mounted on the booms, which limits the accuracy of the measurements and the response of the controller to changes in the terrain, resulting in a sub-optimal spraying process. To overcome these limitations, we propose to use a laser scanner, attached to the front of the sprayer's cabin, to scan the ground surface in front of the vehicle and to build a scrolling 3d map of the terrain. We evaluate the proposed solution in a series of field tests, demonstrating that the approach provides a more detailed and accurate representation of the environment than the current sonar-based solution, and which can lead to the development of more efficient boom control systems.

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“…Approximately, each two consecutive poses are separated by 40 meters. For this experiment, a ground truth is available as it includes pose files calculated using 6D SLAM Andreas Nüchter and Surmann (2007). Comparing the trajectory obtained using the method presented in this paper with the ground truth, we get a root mean square (RMS) error of 0.89 meters in translation and 1.271 degrees in rotation.…”

Section: Bremen Data Setmentioning

confidence: 99%

A robust and fast method for 6DoF motion estimation from generalized 3D data

Viejo

Cazorla

2013

Auton Robot

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Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six Degrees of Freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

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6D SLAM—3D mapping outdoor environments

Cited by 395 publications

References 26 publications

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

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

Evaluation of Laser Range-Finder Mapping for Agricultural Spraying Vehicles

A robust and fast method for 6DoF motion estimation from generalized 3D data

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