OMPL 0.10 released

We are happy to announce a new release of OMPL, version 0.10. All OMPL users are recommended to update to the new version. It includes the following changes:

• Windows support
• Added a primer on sampling-based motion planning and OMPL.
• Added an implementation of SyCLoP, a new multi-layered meta-planner that combines discrete search with a sampling-based motion planner. Implementations of Syclop with RRT and EST as the low-level planners are provided.
• Added an implementation of EST for planning with controls.
• New generic interface for parameter settings for almost anything that is user-configurable. This was done to simplify reading parameters from an input file (see next bullet).
• New benchmark program that allows one to easily specify benchmark problems with simple configuration files.
• New state spaces for Dubins vehicles and Reeds-Shepp vehicles. This allows one to use any geometric planner to compute feasible paths for such vehicles. See the demo program demo_GeometricCarPlanning.
• Added state serialization, deserialization, state space signatures.
• Added the notion of DirectedControlSampler.
• Added path hybridization, a technique for combining several solutions to a motion planning query to form a better bath. We also introduced a utility class called ParallelPlan that runs several planner instances in parallel and (optionally) uses path hybridization.
• Added a more advanced path shortcutting method.
• Added support for FCL collision checking library. PQP is actually still faster, and is therefore still the default.
• All versions of EST and SBL use the new PDF class to sample more efficiently from empirical probability distribution functions.
• Added a wrapper for boost::numeric::odeint to support high-order numerical integration of ordinary differential equations.
• Added support for multiple solution paths in a Goal datastructure.
• Added StateSpace::getValueAddressAtLocation() to allow faster indexing in states using state space names.

Point your browser to http://ompl.kavrakilab.org/download.html to download the latest version.