SThetaStar

python_motion_planning.global_planner.graph_search.s_theta_star.SThetaStar

Bases: ThetaStar

Class for S-Theta* motion planning.

Parameters:

Name	Type	Description	Default
start	tuple	start point coordinate	required
goal	tuple	goal point coordinate	required
env	Env	environment	required
heuristic_type	str	heuristic function type	'euclidean'

Examples:

Python Console Session

>>> import python_motion_planning as pmp
>>> planner = pmp.SThetaStar((5, 5), (45, 25), pmp.Grid(51, 31))
>>> cost, path, expand = planner.plan()
>>> planner.plot.animation(path, str(planner), cost, expand)  # animation
>>> planner.run()       # run both planning and animation

References

[1] S-Theta*: low steering path-planning algorithm

getAlpha(node_p, node_c)

α(t) represents the deviation in the trajectory to reach the goal node g through the node t in relation to the straight-line distance between the parent of its predecessor (t ∈ succ(p) and parent(p) = q) and the goal node.

Parameters:

Name	Type	Description	Default
node_p	Node	parent node	required
node_c	Node	current node	required

Returns:

Name	Type	Description
alpha	float	alpha angle

plan()

S-Theta* motion plan function.

Returns:

Name	Type	Description
cost	float	path cost
path	list	planning path
expand	list	all nodes that planner has searched

updateVertex(node_p, node_c, alpha)

Update extend node information with current node's parent node.

Parameters:

Name	Type	Description	Default
node_p	Node	parent node	required
node_c	Node	current node	required
alpha	float	alpha angle	required