Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects

Kriegel, Simon; Rink, Christian; Bodenmüller, Tim; Suppa, Michael

doi:10.1007/s11554-013-0386-6

Cited by 140 publications

(144 citation statements)

References 24 publications

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“…We then apply primitive-fitting and finally find a feasible solution by comparing against a high-resolution 3D model and checking scene constraints and more complex cases, consisting of an extension of our scene description language with the option to define a 3D model for the fitted shapes. We acquired a 3D mesh of the base station object through the automatic 3D modeling system described in [42]. This highly accurate model is then placed in all possible positions overlapping the fitted model to generate a set of 6D pose hypotheses.…”

Section: Object Pose Estimationmentioning

confidence: 99%

Towards Autonomous Planetary Exploration

Schuster

Brunner

Bussmann

et al. 2017

J Intell Robot Syst

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Planetary exploration poses many challenges for a robot system: From weight and size constraints to extraterrestrial environment conditions, which constrain the suitable sensors and actuators. As the distance to other planets introduces a significant communication delay, the efficient operation of a robot system requires a high level of autonomy. In this work, we present our Lightweight Rover Unit (LRU), a small and agile rover prototype that we designed for the challenges of planetary exploration. Its locomotion system with individually steered wheels allows for high maneuverability in rough terrain and stereo cameras as its main sensors ensure the applicability to space missions. We implemented software components for self-localization This work was supported by the Helmholtz Association, project alliance ROBEX (contract number HA-304) and partially funded by the DLR Space Administration. Electronic supplementary materialThe online version of this article (https://doi.org/10.1007/s10846-017-0680-9) contains supplementary material, which is available to authorized users. in GPS-denied environments, autonomous exploration and mapping as well as computer vision, planning and control modules for the autonomous localization, pickup and assembly of objects with its manipulator. Additional high-level mission control components facilitate both autonomous behavior and remote monitoring of the system state over a delayed communication link. We successfully demonstrated the autonomous capabilities of our LRU at the SpaceBotCamp challenge, a national robotics contest with focus on autonomous planetary exploration. A robot had to autonomously explore an unknown Moon-like rough terrain, locate and collect two objects and assemble them after transport to a third object -which the LRU did on its first try, in half of the time and fully autonomously. The next milestone for our ongoing LRU development is an upcoming planetary exploration analogue mission to perform scientific experiments at a Moon analogue site located on a volcano.

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Section: Object Pose Estimationmentioning

confidence: 99%

Towards Autonomous Planetary Exploration

Schuster

Brunner

Bussmann

et al. 2017

J Intell Robot Syst

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“…Direct triangle mesh generation [24,25,32,43] from point clouds has been popular in 3D reconstruction systems [4,37]. Its strengths are its exceedingly fast operation and simplicity.…”

Section: Proposed Systemmentioning

confidence: 99%

Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras

Meerits

Nozick

Saitō

2017

J Real-Time Image Proc

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We present a novel 3D reconstruction system that can generate a stable triangle mesh using data from multiple RGB-D sensors in real time for dynamic scenes. The first part of the system uses moving least squares (MLS) point set surfaces to smooth and filter point clouds acquired from RGB-D sensors. The second part of the system generates triangle meshes from point clouds. The whole pipeline is executed on the GPU and is tailored to scale linearly with the size of the input data. Our contributions include changes to the MLS method for improving meshing, a fast triangle mesh generation method and GPU implementations of all parts of the pipeline.

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“…Therefore, it is necessary to estimate the original centroid of P on the object for translation. The boundary points located nearby missing part can be detected through the geometric relationship with the support plane and using a set of connected edges that satisfy two requirements, in which all edges have a similar orientation and each edge lacks an assigned triangle, either on the left or on the right side [7] (as shown in Figure 3 (c)). Then, the RANSAC algorithm [16] is used to fit a mathematical model to the boundary points in each subdivided box of the OBB (The total number of subdivided boxes in the OBB is m = k 1 x 1 x 1).…”

Section: Definition Of Translation Matrixmentioning

confidence: 99%

“…However, the effectiveness of this scanning method highly depends on the skills of the user and the scanning process is generally time consuming. To enhance the efficiency, the 6-axis robot arm integrated with 3-D imaging scanners has recently emerged as a technical developing trend for 3-D surface scanning for objects having arbitrary or complex geometry [5][6][7]. Both Callieri [5] and Larsson [6] presented a system for automated 3-D modeling consisting of a 3-D laser scanner, an industrial six axis robot and a turntable.…”

Section: Introductionmentioning

confidence: 99%

“…The advantage of this system is that it automatically achieves the shape of the object from initial scanning and thus, if possible will scan the object using an orientation of the scanner which gives the most accurate result. Meanwhile, an autonomous 3-D modeling system, consisting of an industrial robot and a laser striper, for efficient surface reconstruction of unknown objects was proposed by Simon Kriegel [7]. The system iteratively searches for possible scan paths in the local surface model and selects a next-best-scan (NBS) in its volumetric model.…”

Section: Introductionmentioning

confidence: 99%

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Development of Registration methodology to 3-D Point Clouds in Robot Scanning

et al. 2016

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Abstract. The problem of multi-view 3-D point clouds registration is investigated and effectively resolved by the developed methodology. A registration method is proposed to register two series of scans into an object model by using the proposed oriented-bounding-box (OBB) regional area-based descriptor. Robot 3-D scanning is often employed to generate set of point clouds of physical objects. The automated operation has to successively digitize view-dependent area-scanned point clouds from complex shaped objects by multi-view point clouds registration. To achieve this, the OBB regional area-based descriptor is employed to determine an initial transformation matrix and is then refined employing iterative closest point (ICP) algorithm. The developed method can be used to resolve the commonly encountered difficulty in accurately merging two neighbouring area-scanned images when no coordinate reference exists. The developed method has been verified through some experimental tests for its registration accuracy. Experimental results have preliminarily demonstrated the feasibility of the developed method.

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Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects

Cited by 140 publications

References 24 publications

Towards Autonomous Planetary Exploration

Towards Autonomous Planetary Exploration

Real-time scene reconstruction and triangle mesh generation using multiple RGB-D cameras

Development of Registration methodology to 3-D Point Clouds in Robot Scanning

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