This software finds the shortest paths between configurations for the Dubins' car [Dubins57], the forward only car-like vehicle with a constrained turning radius. A good description of the equations and basic strategies for doing this are described in section 15.3.1 "Dubins Curves" of the book "Planning Algorithms" [LaValle06].
The approach used to find paths is based on the algebraic solutions published in [Shkel01]. However, rather than using angular symmetries to improve performance, the simpler approach to test all possible solutions is used here.
This code is primarily a Cython wrapper of https://github.com/AndrewWalker/Dubins-Curves
You can install the latest stable version from PyPI
$ pip install dubins
Or, you can install the latest development version from GitHub
$ pip install git+git://github.com/AndrewWalker/pydubins.git
Sampling of a Dubin's path at finite size sizes
import dubins
q0 = (x0, y0, theta0)
q1 = (x1, y1, theta1)
turning_radius = 1.0
step_size = 0.5
qs, _ = dubins.path_sample(q0, q1, turning_radius, step_size)
This work was completed as part of [Walker11].
- Francis Valentinis
- Royce Smart - who tested early versions of this code while completing his PhD thesis [Smart08].
[Dubins57] | Dubins, L. E. (July 1957). "On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents". American Journal of Mathematics 79 (3): 497โ516 |
[LaValle06] | LaValle, S. M. (2006). "Planning Algorithms". Cambridge University Press |
[Shkel01] | Shkel, A. M. and Lumelsky, V. (2001). "Classification of the Dubins set". Robotics and Autonomous Systems 34 (2001) 179โ202 |
[Walker11] | Walker, A. (2011). "Hard Real-Time Motion Planning for Autonomous Vehicles", PhD thesis, Swinburne University. |
[Smart08] | Royce, S. (2008). "Evolutionary Control of Autonomous Underwater Vehicles". PhD thesis, RMIT |