Name
Abstract | ||
|---|---|---|
This article covers implementation and testing of sensor data fusion for robot localization. System is capable of finding robot in known environment using LIDAR, odometry and RFID tags. The localization algorithm is based on the particle filter implemented in NVIDIA CUDA. It fuses 3D LIDAR, odometry and RFID data. The experimental setup was created to verify potential use in the indoor environments. Quantitative benchmark was performed using popular robotics simulation framework. The benchmark on low-energy CUDA enabled device is performed. Current study shows the advantage of data fusion for robot localization and demonstrates that current approach can efficiently solve the problem of mobile robot deployment in known environments. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SSRR.2019.8848930 | 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) |
Keywords | Field | DocType |
sensor data fusion,robot localization,odometry,RFID tags,localization algorithm,particle filter,NVIDIA CUDA,3D LIDAR,RFID data,indoor environments,quantitative benchmark,low-energy CUDA,mobile robot deployment | Computer vision,Computer science,CUDA,Particle filter,Odometry,Sensor fusion,Artificial intelligence,Robot,Fuse (electrical),Mobile robot,Robotics | Conference |
ISSN | ISBN | Citations |
2374-3247 | 978-1-7281-0779-0 | 0 |
PageRank | References | Authors |
0.34 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Pelka | 1 | 0 | 0.68 |
| Karol Majek | 2 | 0 | 0.68 |
| Jakub Ratajczak | 3 | 0 | 0.68 |
| Janusz Bedkowski | 4 | 29 | 6.55 |
| Andrzej Maslowski | 5 | 0 | 0.34 |