Name
Abstract | ||
|---|---|---|
We make full use of the pre-known knowledge of environment, and establish a hierarchical semantic map offline for large-scale outdoor environment. The map contains semantic information which is more stable than the commonly used feature points. And the description and recognition methods of locations based on semantic information are similar to human habits. Experiment results show that the all parts of the map working together can achieve path planning, location recognition and relative pose estimation to complete the robot navigation task. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/RCAR52367.2021.9517476 | 2021 IEEE International Conference on Real-time Computing and Robotics (RCAR) |
Keywords | DocType | ISBN |
large-scale outdoor environment,hierarchical semantic map offline,semantic information,commonly used feature points,location recognition | Conference | 978-1-6654-3679-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||