change DStar animation

Author: AtsushiSakai

PathPlanning/DStar/dstar.py

@@ -63,7 +63,7 @@ def init_map(self):
             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 @@ def process_state(self):
         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 @@ def run(self, start, end):
             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)
@@ -226,14 +226,15 @@ 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]]
     dstar = Dstar(m)
     rx, ry = dstar.run(start, end)
 
     if show_animation:
-        plt.plot(rx, ry)
+        plt.plot(rx, ry, "-r")
         plt.show()
 
 

README.md

@@ -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.
 

docs/modules/path_planning.rst

@@ -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