2021/02/22 by Martin Nievas, Martín Nievas, Claudio Paz +5
Computer Science · Earth and Planetary Sciences · Engineering · Environmental Science · #3D Surveying and Cultural Heritage #Artificial intelligence #Block (permutation group theory) #Cloud computing #Computer engineering #Computer science #Distributed computing #FOS: Computer and information sciences #Grid #Octree #Point cloud #Probabilistic logic #RGB color model #Real-time computing #Remote Sensing and LiDAR Applications #Representation (politics) #Robot #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Subdivision #Task (project management) #cs.RO
paper · pdf · doi:10.48550/arxiv.2102.11084
published in arXiv (Cornell University) (Cornell University) · This is the accepted version of the manuscript that was sent to review to 2020 IEEE Biennial Congress of Argentina (ARGENCON) (ISBN 978-1-7281-5957-7/20). in Spanish
arxiv created 2021/02/22 · openalex publication_date 2021/02/22 · arxiv updated 2021/02/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The exploration of unknown environments using robots is a task that integrates different areas such as location, mapping, and planning. For mapping, there are numerous methods to represent the environments through which a robot can travel, in two and three dimensions. The probabilistic occupation grid, Octomap, and STVL can be mentioned among the most important in recent years. Nowadays, RGB-D cameras are widely used to generate a detailed representation of the environment. RGB-D camera measurements present a large volume of data, which must be reduced in order to be used in platforms with limited computing resources. This work presents an implementation of the point cloud decimation method capable of being executed on platforms with unified memory. It consists of reducing the point cloud iteratively using a subdivision of space. Results were obtained for different sizes of grids, platforms, and scenarios, both real and simulated. The results indicate that in embedded systems it is convenient to have architectures that share memory between CPU and GPU to optimize data block communication processes.