Fuzzy modeling of natural terrain elevation from a 3D scanner point cloud

Mandow, Anthony; Cantador, Tomás J.; García-Cerezo, Alfonso J.; Reina, Antonio J.; Martínez, Jorge L.; Morales, José

doi:10.1109/wisp.2011.6051705

Cited by 7 publications

(22 citation statements)

References 15 publications

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“…The reason for sub-sampling is twofold: improving the speed of fuzzy identification and homogenizing the spatial distribution of training data. In [23], sub-sampling was performed by selecting the highest point within grid cells of a sufficiently high resolution. This approach provides a representative set of points for a smooth terrain but is not so effective to model salient obstacles, such as tree trunks or rocks, which can be filtered by the fuzzy identification method when represented by a small number of samples.…”

Section: Point Sub-samplingmentioning

confidence: 99%

“…This conflict can be coped with by considering that higher detail is more important for the regions that are closest to the robot. Thus, an uneven membership function distribution can provide an appropriate fuzzy structure if the density of MFs for variables x and y is specified depending on the distance to the sensor [23].…”

Section: Neuro-fuzzy Trainingmentioning

confidence: 99%

“…Furthermore, the order of Sugeno inference affects training time as well as the number of rule parameters. In [23], first-order consequents G i were considered for every rule i as:…”

Section: Neuro-fuzzy Trainingmentioning

confidence: 99%

“…Adaptive Network-based Fuzzy Inference Systems (ANFIS) [21] has been employed to recognize objects like trees and buildings from aerial stereo images [22]. Moreover, ANFIS was preliminarily proposed to obtain fuzzy elevation maps of natural terrain from ground-based 3D data [23]. These elevation maps have been already employed for assessing traversability and local path planning [24].…”

Section: Introductionmentioning

confidence: 99%

“…The main contribution of this paper is extending [23] to improve computational speed and performance. To this end, two major modifications have been introduced: i ) spherical sub-sampling [25] is used to select proper training data from a raw point cloud, and ii ) rule parameters have been systematically defined by considering triangular sets with standard fuzzy partition [26] as well as zero order Sugeno-type inference.…”

Section: Introductionmentioning

confidence: 99%

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Building Fuzzy Elevation Maps from a Ground-Based 3D Laser Scan for Outdoor Mobile Robots

Mandow

Cantador

Reina

et al. 2015

Advances in Intelligent Systems and Computing

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-The paper addresses terrain modeling for mobile robots with fuzzy elevation maps by improving computational speed and performance over previous work on fuzzy terrain identification from a three-dimensional (3D) scan. To this end, spherical sub-sampling of the raw scan is proposed to select training data that does not filter out salient obstacles. Besides, rule structure is systematically defined by considering triangular sets with an unevenly distributed standard fuzzy partition and zero order Sugeno-type consequents. This structure, which favors a faster training time and reduces the number of rule parameters, also serves to compute a fuzzy reliability mask for the continuous fuzzy surface. The paper offers a case study using a Hokuyo-based 3D rangefinder to model terrain with and without outstanding obstacles. Performance regarding error and model size is compared favorably with respect to a solution that uses quadric-based surface simplification (QSlim). Keywords: Elevation maps, mobile robots, 3D scanners, fuzzy modeling ___________________________________________________________________________________________________This is a self-archiving copy of the author's accepted manuscript. The final publication is available at Springer via http://link.springer.com/book/10.1007/978-3-319-27149-1. Abstract. The paper addresses terrain modeling for mobile robots with fuzzy elevation maps by improving computational speed and performance over previous work on fuzzy terrain identification from a threedimensional (3D) scan. To this end, spherical sub-sampling of the raw scan is proposed to select training data that does not filter out salient obstacles. Besides, rule structure is systematically defined by considering triangular sets with an unevenly distributed standard fuzzy partition and zero order Sugeno-type consequents. This structure, which favors a faster training time and reduces the number of rule parameters, also serves to compute a fuzzy reliability mask for the continuous fuzzy surface. The paper offers a case study using a Hokuyo-based 3D rangefinder to model terrain with and without outstanding obstacles. Performance regarding error and model size are compared favorably with respect to a solution that uses quadric-based surface simplification (QSlim).

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Section: Point Sub-samplingmentioning

confidence: 99%

Section: Neuro-fuzzy Trainingmentioning

confidence: 99%

“…Furthermore, the order of Sugeno inference affects training time as well as the number of rule parameters. In [23], first-order consequents G i were considered for every rule i as:…”

Section: Neuro-fuzzy Trainingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Building Fuzzy Elevation Maps from a Ground-Based 3D Laser Scan for Outdoor Mobile Robots

Mandow

Cantador

Reina

et al. 2015

Advances in Intelligent Systems and Computing

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Responsive navigation of a biped robot that takes into account terrain, foot-reachability and capturability

Yamamoto

Sugihara

2021

Advanced Robotics

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A control architecture for robust biped navigation that takes into account traversability on terrain, foot-reachability, and capturability all at once in dynamic situations is proposed. It consists of online mapping of terrain and quick decision of foot placement. A grid map with elevation, normal direction and the standard deviation of measurement is proposed for the former and is named the stochastic Elevation-and-Normal Grid (ENG) map. It is incrementally updated as depth sensor information comes in every cycle. The traversability of each grid can be easily checked based on the associated information. The latter stands upon the canonical biped track (CBT), which is a pair of continuous paths that the feet track. It is drawn along a nominal collision-free path on the ENG map. The most efficient foot placement at the next step from the viewpoint of the foot-reachability is chosen on them as the initial candidate, around which a feasible placement accommodated with traversability and capturability is found by the breadth-first search. An autonomous biped locomotion system is completed by combining the above architecture with a foot-guided controller based on the terminal capturability. The efficacy of the proposed method was validated through some computer simulations.

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Collapsible cubes: Removing overhangs from 3D point clouds to build local navigable elevation maps

Reina

Martínez

Mandow

et al. 2014

2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Elevation maps offer a compact 2 1 2 dimensional model of terrain surface for navigation in field mobile robotics. However, building these maps from 3D raw point clouds containing overhangs, such as tree canopy or tunnels, can produce useless results. This paper proposes a simple processing of a ground-based point cloud that identifies and removes overhang points that do not constitute an obstacle for navigation while keeping vertical structures such as walls or tree trunks. The procedure uses efficient data structures to collapse unsupported 3D cubes down to the ground. This method has been successfully applied to 3D laser scans taken from a mobile robot in outdoor environments in order to build local elevation maps for navigation. Computation times show an improvement with respect to a previous point-based solution to this problem.

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Fuzzy modeling of natural terrain elevation from a 3D scanner point cloud

Cited by 7 publications

References 15 publications

Building Fuzzy Elevation Maps from a Ground-Based 3D Laser Scan for Outdoor Mobile Robots

Building Fuzzy Elevation Maps from a Ground-Based 3D Laser Scan for Outdoor Mobile Robots

Responsive navigation of a biped robot that takes into account terrain, foot-reachability and capturability

Collapsible cubes: Removing overhangs from 3D point clouds to build local navigable elevation maps

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