The LEMUR planner works on roadmaps constructed in the robot's configuration space. Each planning invocation requires the roadmap to be specified. The prpy_lemur package includes a roadmaps module, which contains a simple named-tuple interface for constructing such roadmaps.

>>> import prpy_lemur.roadmaps
>>> my_roadmap = prpy_lemur.roadmaps.Halton(num=1000, radius=2.0)
>>> my_roadmap
Halton(num=1000, radius=2.0)

This roadmap specification can then be passed to the LEMUR planner. This can be done either on the planning method:

traj = planner.PlanToConfiguration(robot, q_goal,
   roadmap=my_roadmap, max_batches=1)

Or at planner construction time, so that it is used as the default roadmap for all its planning methods:

planner = prpy_lemur.LEMURPlanner(roadmap=my_roadmap)

These roadmap types are supported by prpy_lemur.roadmaps:

AAGrid(res)
FromFile(filename, root_radius)
Halton(num, radius)
HaltonDens(num_per_batch, radius_first_batch)
HaltonOffDens(num_per_batch, gamma_factor, scaling, seed)
RGG(num, radius, seed)
RGGDens(num_per_batch, radius_first_batch, seed)
RGGDensConst(num_per_batch, radius, seed)

This is the meaning of the various parameters:

filename - the filename to load the roadmap from
num - the number of milestones in the roadmap
num_per_batch - the number of milestones in each batch of the roadmap
res - the resolution (e.g. in radians) between grid vertices
seed - the random seed used for the roadmap
radius - the connection radius used for roadmap edges
gamma_factor - the multiplicative factor to scale gamma
scaling - the radius scaling strategy (log_n, loglog_n, or 1_n)
radius_first_batch - the connection radius used for the first batch of roadmap edges; subsequent radii are shrunk according to the appropriate rule
root_radius - the connection radius used for roadmap edges to root milestones (i.e. at start or goal configurations)

With the exception of FromFile, each roadmap Type also have an associated cached version CachedType. This roadmap type inherits the parameters from its parent type, and also includes the following additional parameter:

is_cache_required - whether the planner should fail if the cache file is not found (False by default)