Partner: Michał Pelka

Institute of Mathematical Machines (PL)

Conference papers
1.Będkowski J., Pelka M., Majek K., Fitri T., Naruniec J., Open source robotic 3D mapping framework with ROS - Robot Operating System, PCL - Point Cloud Library and Cloud Compare, 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS, 2015-08-10/08-11, Legian-Bali (ID), DOI: 10.1109/ICEEI.2015.7352578, pp.644-649, 2015
Abstract:

We propose an open source robotic 3D mapping framework based on Robot Operating System, Point Cloud Library and Cloud Compare software extended by functionality of importing and exporting datasets. The added value is an integrated solution for robotic 3D mapping and new publicly available datasets (accurate 3D maps with geodetic precision) for evaluation purpose Datasets were gathered by mobile robot in stop scan fashion. Presented results are a variety of tools for working with such datasets, for task such as: preprocessing (filtering, down sampling), data registration (ICP, NDT), graph optimization (ELCH, LUM), tools for validation (comparison of 3D maps and trajectories), performance evaluation (plots of various outputs of algorithms). The tools form a complete pipeline for 3D data processing. We use this framework as a reference methodology in recent work on SLAM algorithms.

Keywords:

Three-dimensional displays, Robot kinematics, Cameras, Mobile communication, Robot sensing systems, XML

Affiliations:
Będkowski J.-other affiliation
Pelka M.-Institute of Mathematical Machines (PL)
Majek K.-Institute of Mathematical Machines (PL)
Fitri T.-Institute of Mathematical Machines (PL)
Naruniec J.-Warsaw University of Technology (PL)
2.Musialik P., Majek K., Majek P., Pelka M., Będkowski J., Masłowski A., Typiak A., Accurate 3D mapping and immersive visualization for Search and Rescue, RoMoCo 2015, 10th International Workshop on Robot Motion and Control, 2015-07-06/07-08, Poznań (PL), DOI: 10.1109/RoMoCo.2015.7219728, pp.153-158, 2015
Abstract:

This paper concentrates on the topic of gathering, processing and presenting 3D data for use in Search and Rescue operations. The data are gathered by unmanned ground platforms, in form of 3D point clouds. The clouds are matched and transformed into a consistent, highly accurate 3D model. The paper describes the pipeline for such matching based on Iterative Closest Point algorithm supported by loop closing done with LUM method. The pipeline was implemented for parallel computation with Nvidia CUDA, which leads to higher matching accuracy and lower computation time. An analysis of performance for multiple GPUs is presented. The second problem discussed in the paper is immersive visualization of 3d data for search and rescue personnel. Five strategies are discussed: plain 3D point cloud, hypsometry, normal vectors, space descriptors and an approach based on light simulation through the use of NVIDIA OptiX Ray Tracing Engine. The results from each strategy were shown to end users for validation. The paper discusses the feedback given. The results of the research are used in the development of a support module for ICARUS project.

Keywords:

Three-dimensional displays, Data visualization, Graphics processing units, Image color analysis, Computational modeling, Solid modeling, Pipelines

Affiliations:
Musialik P.-Institute of Mathematical Machines (PL)
Majek K.-Institute of Mathematical Machines (PL)
Majek P.-Institute of Mathematical Machines (PL)
Pelka M.-Institute of Mathematical Machines (PL)
Będkowski J.-other affiliation
Masłowski A.-other affiliation
Typiak A.-other affiliation