github/PythonRobotics
1
1
Fork 0
mirror of https://github.com/AtsushiSakai/PythonRobotics.git synced 2026-01-13 04:28:04 -05:00
Code Issues Packages Projects Releases Wiki Activity

change DStar animation

Browse Source
This commit is contained in:
Atsushi Sakai
2021-05-15 15:21:15 +09:00
parent 2cf4f6f001
commit 1de0ffddb1
3 changed files with 9 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

13
PathPlanning/DStar/dstar.py
View File

@@ -63,7 +63,7 @@ class Map:
map_list.append(tmp)
return map_list
def get_neighbers(self, state):
def get_neighbors(self, state):
state_list = []
for i in [-1, 0, 1]:
for j in [-1, 0, 1]:
@@ -99,18 +99,18 @@ class Dstar:
self.remove(x)
if k_old < x.h:
for y in self.map.get_neighbers(x):
for y in self.map.get_neighbors(x):
if y.h <= k_old and x.h > y.h + x.cost(y):
x.parent = y
x.h = y.h + x.cost(y)
elif k_old == x.h:
for y in self.map.get_neighbers(x):
for y in self.map.get_neighbors(x):
if y.t == "new" or y.parent == x and y.h != x.h + x.cost(y) \
or y.parent != x and y.h > x.h + x.cost(y):
y.parent = x
self.insert(y, x.h + x.cost(y))
else:
for y in self.map.get_neighbers(x):
for y in self.map.get_neighbors(x):
if y.t == "new" or y.parent == x and y.h != x.h + x.cost(y):
y.parent = x
self.insert(y, x.h + x.cost(y))
@@ -178,7 +178,7 @@ class Dstar:
rx.append(tmp.x)
ry.append(tmp.y)
if show_animation:
plt.plot(rx, ry)
plt.plot(rx, ry, "-r")
plt.pause(0.01)
if tmp.parent.state == "#":
self.modify(tmp)
@@ -226,6 +226,7 @@ def main():
plt.plot(ox, oy, ".k")
plt.plot(start[0], start[1], "og")
plt.plot(goal[0], goal[1], "xb")
plt.axis("equal")
start = m.map[start[0]][start[1]]
end = m.map[goal[0]][goal[1]]
@@ -233,7 +234,7 @@ def main():
rx, ry = dstar.run(start, end)
if show_animation:
plt.plot(rx, ry)
plt.plot(rx, ry, "-r")
plt.show()

2
README.md
View File

@@ -306,7 +306,7 @@ Its heuristic is 2D Euclid distance.
This is a 2D grid based the shortest path planning with D star algorithm.
![figure at master · nirnayroy/intelligentrobotics](https://github.com/nirnayroy/intelligent-robotics/blob/main/dstar.gif)
![figure at master · nirnayroy/intelligentrobotics](https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/DStar/animation.gif)
The animation shows a robot finding its path avoiding an obstacle using the D* search algorithm.

2
docs/modules/path_planning.rst
View File

@@ -442,7 +442,7 @@ Ref:
.. |DWA| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/DynamicWindowApproach/animation.gif
.. |Dijkstra| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/Dijkstra/animation.gif
.. |astar| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/AStar/animation.gif
.. |dstar| image:: https://github.com/nirnayroy/intelligent-robotics/blob/main/dstar.gif
.. |dstar| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/DStar/animation.gif
.. |PotentialField| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/PotentialFieldPlanning/animation.gif
.. |4| image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/ModelPredictiveTrajectoryGenerator/kn05animation.gif
.. |5| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/PathPlanning/ModelPredictiveTrajectoryGenerator/lookuptable.png?raw=True