Code to generate and manipulate dubins curves
This software finds the shortest paths between configurations for the Dubins’ car [Dubins51], 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].
|[Dubins51]||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): 497–516|
|[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) 179–202|
|[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|