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RRTStar

python_motion_planning.global_planner.sample_search.rrt_star.RRTStar

Bases: RRT

Class for RRT-Star motion planning.

Parameters:

Name Type Description Default
start tuple

start point coordinate

required
goal tuple

goal point coordinate

required
env Env

environment

required
max_dist float

Maximum expansion distance one step

0.5
sample_num int

Maximum number of sample points

10000
r float

optimization radius

10.0
goal_sample_rate float

heuristic sample

0.05

Examples:

Python Console Session
>>> import python_motion_planning as pmp
>>> planner = pmp.RRTStar((5, 5), (45, 25), pmp.Map(51, 31))
>>> cost, path, expand = planner.plan()     # planning results only
>>> planner.plot.animation(path, str(planner), cost, expand)  # animation
>>> planner.run()       # run both planning and animation
References

[1] Sampling-based algorithms for optimal motion planning

getNearest(node_list, node)

Get the node from node_list that is nearest to node with optimization.

Parameters:

Name Type Description Default
node_list list

exploring list

required
node Node

currently generated node

required

Returns:

Name Type Description
node Node

nearest node