Synonyms
Introduction
It is already a decade since massive parallel computing with CUDA (Compute Unified Device Architecture) was introduced by NVIDIA. Since that moment many researchers were focused on incorporating parallel approach into mobile robot applications. Recent advances show that GPGPUs (general-purpose graphics processing units) can be efficiently applied in multidomain robotics (air, ground, surface, underwater, underground). It is important to emphasize the fact that the development of sensors (cameras, 3D lasers, RGB-D cameras like Kinect) opened new research directions. Thus, new programming techniques had to be developed for reaching high performance assuming low power consumption. Moreover it is crucial for the robotic application the power consumed by processing units. For this reason it is evident that the parallel algorithms have to be adapted for the available hardware in robotics. GPGPUs can solve many algorithmic problems; thus, GPU...
This is a preview of subscription content, log in via an institution to check access.
References
(2016a) CUDA C Best Practices Guide. http://docs.nvidia.com/cuda/cuda-c-best-practices-guide/
(2016b) NVIDIA CUDA C Programming Guide 7.5. https://docs.nvidia.com/cuda/cuda-c-programming- guide/
(2017) https://github.com/JanuszBedkowski/gpu_compu ting_in_robotics
(2017) http://www.nvidia.com/object/embedded-systems- dev-kits-modules.html
Balta H, Bedkowski J, Govindaraj S, Majek K, Musialik P, Serrano D, Alexis K, Siegwart R, de Cubber G (2016) Integrated data management for a fleet of search-and-rescue robots. J Field Robot 34(3):539–582
Bedkowski J (2011) Data registration module – a component of semantic simulation engine. In: Proceedings of 5th European conference on mobile robots ECMR, pp 133–138
Bedkowski J, Majek K, Nüchter A (2013) General purpose computing on graphics processing units for robotic applications. J Softw Eng Robot 4(1):23–33
Bedkowski J, Maslowski A (2012) GPGPU computation in mobile robot applications. Int J Electr Eng Inform 4(1):15–26
Bedkowski J, Maslowski A, de Cubber G (2012) Real time 3D localization and mapping for USAR robotic application. Ind Robot 39(5):464–474
Nüchter A, Feyzabadi S, Qiu D, May S (2011) SLAM – la carte – GPGPU for globally consistent scan matching. In: Proceedings of the 4th European conference on mobile robots (ECMR ’11), Örebro
Qiu D, May S, Nüchter A (2009) GPU-accelerated nearest neighbor search for 3D registration. In: Proceedings of the 7th international conference on computer vision systems, ICVS09. Springer, Berlin/Heidelberg, pp 194–203
Satish N, Harris M, Garland M (2009) Designing efficient sorting algorithms for manycore gpus. In: Proceedings of the 2009 IEEE international symposium on parallel & distributed processing, Washington, DC. IEEE Computer Society, pp 1–10
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2020 Springer-Verlag GmbH Germany, part of Springer Nature
About this entry
Cite this entry
Bedkowski, J. (2020). GPU Computing in Robotics. In: Ang, M., Khatib, O., Siciliano, B. (eds) Encyclopedia of Robotics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41610-1_5-1
Download citation
DOI: https://doi.org/10.1007/978-3-642-41610-1_5-1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41610-1
Online ISBN: 978-3-642-41610-1
eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering