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Release Notes

OMPL 0.10.2 (March 21, 2012)

  • Created a blog to highlight new features.
  • Bug fixes.

OMPL 0.10.1 (February 27, 2012)

  • Added representation of discrete control spaces.
  • Fixes for XCode 4.3 / clang 3.1svn when compiling the Python bindings.
  • Updates to support Python 3.x in existing demo programs.
  • Bug fixes.

OMPL 0.10.0 (February 16, 2012)

  • Minimum Boost version is now 1.44 (for full functionality).
  • Added a primer on sampling-based motion planning and OMPL.
  • Added an implementation of SyCLoP, a new multilayered 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.
  • 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.
  • 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.
  • Fixed issues with static variables for console.
  • Added RPY sampling to the RNG class.
  • Made some public members protected for GoalState and GoalStates; improvements to GoalLazySamples.
  • Added support for multiple solution paths in a Goal datastructure.
  • Added StateSpace::getValueAddressAtLocation() to allow faster indexing in states using state space names.
  • The C++ code switched to the preferred boost::function syntax. A general method for exposing boost::function objects to Python was added, but this requires a patch to pygccxml.
  • To make installing and patching Py++, pygccml, and gccxml easier there is now a script called installPyPlusPlus.sh that does this. One can call this script after running cmake by typing “make installpyplusplus”.

OMPL 0.9.5 (October 4, 2011)

  • Added control sampler functions that allow specifying an intended direction of propagation
  • Removed pre-generated Python binding code. It turns out that they are dependent on the particular Boost version.
  • Bug fixes.

OMPL 0.9.4 (August 16, 2011)

  • Renamed StateManifold to StateSpace and ControlManifold to ControlSpace
  • Added RRTstar contribution
  • Added GNAT nearest neighbors datastructure
  • Added representation of a discrete state space (DiscreteStateSpace)
  • Added representation of probability density functions (PDF)
  • Replaced the implementation of BasicPRM with PRM. Thanks to James Marble, the new implementation uses BGL.
  • Moved state propagation functionality from ControlSpace to a separate StatePropagator class
  • Added isStraightLinePathValid() to PlannerDefinition
  • Using boost ublas for real vector projections
  • Add sanity checks for state spaces
  • Benchmarked planners are now run in a separate thread (and termination conditions are evaluated separately, to detect crashes)
  • Added getType() for Goal and replaced getType() for planners by getSpecs()
  • Generalized planner termination conditions. The user can now call terminate() at any time to signal a planner it should stop its computation
  • Improvements to control::KPIECE1, so that it considers goal biasing more appropriately
  • Move code for extracting machine properties from util/ to benchmark/
  • Documentation fixes

OMPL 0.9.3 (May 2, 2011)

  • Added path smoothing with splines
  • Added a bi-directional implementation of KPIECE (BKPIECE)
  • Support for computation of clearance and gradients that move away from invalid regions
  • Separate "magic constants" to a separate, visible, location
  • A number of bug fixes

OMPL 0.9.2 (February 21, 2011)

  • Updates to operations on states: indexing in states can be done using state spaces or using integer values
  • Bug fixes for planning with controls
  • Minor doc improvements

OMPL 0.9.1 (December 17, 2010)

  • Minor updates to build system

OMPL 0.9.0 (December 15, 2010; initial release)

  • Implementations of many state-of-the-art sampling-based motion planning algorithms. For purely geometric planning, there are implementations of KPIECE, SBL, RRT, RRT Connect, EST, PRM, Lazy RRT, and others. For planning with differential constraints there are implementations of KPIECE and RRT. Addition of new planners poses very few constraints on the added code.
  • A flexible mechanism for constructing arbitrarily complex configuration spaces and control spaces from simpler ones.
  • A general method of defining goals: as states, as regions in configuration space, or implicitly.
  • Various sampling strategies and an easy way to add other ones.
  • Automatic selection of reasonable default parameters. Performance can be improved by tuning parameters, but solutions can be obtained without setting any parameters.
  • Support for planning with the Open Dynamics Engine, a popular physics simulator.
  • Tools for systematic, large-scale benchmarking.