DStar

python_motion_planning.global_planner.graph_search.d_star.DStar

Bases: GraphSearcher

Class for D* motion planning.

Parameters:

Name	Type	Description	Default
start	tuple	start point coordinate	required
goal	tuple	goal point coordinate	required
env	Env	environment	required

Examples:

Python Console Session

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

References

[1]Optimal and Efficient Path Planning for Partially-Known Environments

min_k: float property

Choose the minimum k value for nodes in OPEN list.

min_state: DNode property

Choose the node with the minimum k value in OPEN list.

OnPress(event)

Mouse button callback function.

Parameters:

Name	Type	Description	Default
event	MouseEvent	mouse event	required

delete(node)

Delete node from OPEN list.

Parameters:

Name	Type	Description	Default
node	DNode	the node to delete	required

extractPath(closed_list)

Extract the path based on the CLOSED list.

Parameters:

Name	Type	Description	Default
closed_list	dict	CLOSED list	required

Returns:

Name	Type	Description
cost	float	the cost of planning path
path	list	the planning path

getNeighbor(node)

Find neighbors of node.

Parameters:

Name	Type	Description	Default
node	DNode	current node	required

Returns:

Name	Type	Description
neighbors	list	neighbors of current node

insert(node, h_new)

Insert node into OPEN list.

Parameters:

Name	Type	Description	Default
node	DNode	the node to insert	required
h_new	float	new or better cost to come value	required

modify(node, node_parent)

Start processing from node.

Parameters:

Name	Type	Description	Default
node	DNode	the node to modify	required
node_parent	DNode	the parent node of node	required

plan()

D* static motion planning function.

Returns:

Name	Type	Description
cost	float	path cost
path	list	planning path
_	None	None

processState()

Broadcast dynamic obstacle information.

Returns:

Name	Type	Description
min_k	float	minimum k value of map

run()

Running both plannig and animation.