Salvato in:
| Autori principali: | , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2409.09816 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915168744636416 |
|---|---|
| author | Pastorelli, Patrick Dagnino, Simone Saccon, Enrico Frego, Marco Palopoli, Luigi |
| author_facet | Pastorelli, Patrick Dagnino, Simone Saccon, Enrico Frego, Marco Palopoli, Luigi |
| contents | In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature. In the paper, we show that the generated path: 1) has minimal length, 2) is $G^1$ continuous, and 3) is collision-free by construction, if the hypotheses are respected. We compare our solution with the state-of.the-art and show its convenience both in terms of computation time and of length of the compute path. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_09816 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fast Shortest Path Polyline Smoothing With $G^1$ Continuity and Bounded Curvature Pastorelli, Patrick Dagnino, Simone Saccon, Enrico Frego, Marco Palopoli, Luigi Robotics In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature. In the paper, we show that the generated path: 1) has minimal length, 2) is $G^1$ continuous, and 3) is collision-free by construction, if the hypotheses are respected. We compare our solution with the state-of.the-art and show its convenience both in terms of computation time and of length of the compute path. |
| title | Fast Shortest Path Polyline Smoothing With $G^1$ Continuity and Bounded Curvature |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.09816 |