hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.2498/cit.1001174

Parallel and Cached Scan Matching for Robotic 3D Mapping

Andreas Nuechter

Puni tekst: engleski, pdf (3 MB) str. 51-65 preuzimanja: 655* citiraj
APA 6th Edition
Nuechter, A. (2009). Parallel and Cached Scan Matching for Robotic 3D Mapping. Journal of computing and information technology, 17 (1), 51-65. https://doi.org/10.2498/cit.1001174
MLA 8th Edition
Nuechter, Andreas. "Parallel and Cached Scan Matching for Robotic 3D Mapping." Journal of computing and information technology, vol. 17, br. 1, 2009, str. 51-65. https://doi.org/10.2498/cit.1001174. Citirano 25.07.2021.
Chicago 17th Edition
Nuechter, Andreas. "Parallel and Cached Scan Matching for Robotic 3D Mapping." Journal of computing and information technology 17, br. 1 (2009): 51-65. https://doi.org/10.2498/cit.1001174
Harvard
Nuechter, A. (2009). 'Parallel and Cached Scan Matching for Robotic 3D Mapping', Journal of computing and information technology, 17(1), str. 51-65. https://doi.org/10.2498/cit.1001174
Vancouver
Nuechter A. Parallel and Cached Scan Matching for Robotic 3D Mapping. Journal of computing and information technology [Internet]. 2009 [pristupljeno 25.07.2021.];17(1):51-65. https://doi.org/10.2498/cit.1001174
IEEE
A. Nuechter, "Parallel and Cached Scan Matching for Robotic 3D Mapping", Journal of computing and information technology, vol.17, br. 1, str. 51-65, 2009. [Online]. https://doi.org/10.2498/cit.1001174

Sažetak
Intelligent autonomous acting of mobile robots in unstructured environments requires 3D maps. Since manual mapping is a tedious job, automatization of this job is necessary. Automatic, consistent volumetric modeling of environments requires a solution to the simultaneous localization and map building problem (SLAM problem). In 3D task is computationally expensive, since the environments are sampled with many data points with state of the art sensing technology. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper summarizes our 6D SLAM algorithm and presents novel algorithmic and technical means to reduce computation time, i.e., the data structure cached \\kd~tree and parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics tasks.

Hrčak ID: 44568

URI
https://hrcak.srce.hr/44568

Posjeta: 870 *