Neural-network-driven method for optimal path planning via high-accuracy region prediction
Sampling-based path planning algorithms suffer from heavy reliance on uniform sampling, which accounts for unreliable and time-consuming performance, especially in complex environments. Recently, neural-network-driven methods predict regions as sampling domains to realize a non-uniform sampling and...
Saved in:
| Published in: | Artificial life and robotics Vol. 29; no. 1; pp. 12 - 21 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Tokyo
Springer Japan
01.02.2024
Springer Nature B.V |
| Subjects: | |
| ISSN: | 1433-5298, 1614-7456 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!