[wip/ompl] Upgrade to 1.0.0
Changes since 0.14.2
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- Added many new planners:
- Linear Temporal Logical Planner (LTLPlanner): a planner that finds
solutions for kinodynamic motion planning problems where the goal is specified
by a Linear Temporal Logic (LTL) specification.
- Fast Marching Tree algorithm (FMT∗): a new asymptotically optimal
algorithm contributed by Marco Pavone's Autonomous Systems Laboratory at
Stanford.
- Coupled Forest of Random Engrafting Search Trees (CForest): a
meta-planner that runs several instances of asymptotically optimal planners in
different threads. When one thread finds a better solution path, the states
along the path are passed on to the other threads.
- Anytime Path Shortening: a generic wrapper around one or more
geometric motion planners that repeatedly applies shortcutting and
hybridization to a set of solution paths. Any number and combination of
planners can be specified, each is run in a separate thread.
- LazyPRM / LazyPRMstar: not entirely new, but completely re-implemented.
- RRT* has a new option to periodically prune parts of the tree that are
guaranteed not to contain the optimal solution. This idea was introduced in
CForest, but it useful independently of the CForest parallelization. Although
pruning is almost always useful, it is disabled by default to preserve the
original behavior.
- Created consistent behavior across all planners that can optimize paths.
Calls to the solve method of RRT*, PRM*, SPARS, SPARStwo, and LBTRRT will
terminate when (1) the planner termination condition is true or (2) the
optimization objective is satisfied. To make these planners terminate when any
solution is found, you can set the cost threshold for the optimization
objective to, e.g., OptimizationObjective::infiniteCost(). For most of these
planners, asymptotic (approximate) optimality is only guaranteed when using the
PathLengthOptimizationObjective class.
- Most control-based planners can now use steering functions. The user simply
needs to override ompl::control::StatePropagator::steer() and
ompl::control::StatePropagator::canSteer() in a derived class.
- Several improvements to benchmarking functionality:
- Planner Arena has been relaunched and can be used to interactively
visualize benchmark results.
- ompl_benchmark_statistics.py can now also parse MoveIt! benchmark log
files using the flag --moveit.
- Added ompl::tools::PlannerMonitor class, which periodically prints planner
progress properties in a separate thread. Useful for developing / debugging new
planners.
- Updated Py++ toolchain. If you previously installed Py++ and have trouble
generating the OMPL Python bindings, you may need to run "make
installpyplusplus" again.
- Minimum Boost version is now 1.48 and minimum CMake version is now 2.8.7.
- Bug fixes.
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