'BITstar'

Sampling_based_Planning/rrt_3D/BIT_star3D.py

@@ -15,6 +15,7 @@ source: Gammell, Jonathan D., Timothy D. Barfoot, and Siddhartha S. Srinivasa.
 
 import numpy as np
 import matplotlib.pyplot as plt
+from numpy.matlib import repmat
 import time
 import copy
 
@@ -24,24 +25,47 @@ import sys
 
 sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../../Sampling_based_Planning/")
 from rrt_3D.env3D import env
-from rrt_3D.utils3D import getDist, sampleFree, nearest, steer, isCollide
+from rrt_3D.utils3D import getDist, sampleFree, nearest, steer, isCollide, isinside
 from rrt_3D.plot_util3D import make_get_proj, draw_block_list, draw_Spheres, draw_obb, draw_line, make_transparent
 from rrt_3D.queue import MinheapPQ
 
-class BIT_star:
+#---------methods to draw ellipse during sampling
+def CreateUnitSphere(r = 1):
+    phi = np.linspace(0,2*np.pi, 256).reshape(256, 1) # the angle of the projection in the xy-plane
+    theta = np.linspace(0, np.pi, 256).reshape(-1, 256) # the angle from the polar axis, ie the polar angle
+    radius = r
 
-    def __init__(self):
+    # Transformation formulae for a spherical coordinate system.
+    x = radius*np.sin(theta)*np.cos(phi)
+    y = radius*np.sin(theta)*np.sin(phi)
+    z = radius*np.cos(theta)
+    return (x, y, z)
+
+def draw_ellipsoid(ax, C, L, xcenter):
+    (xs, ys, zs) = CreateUnitSphere()
+    pts = np.array([xs, ys, zs])
+    pts_in_world_frame = C@L@pts + xcenter
+    ax.plot_surface(pts_in_world_frame[0], pts_in_world_frame[1], pts_in_world_frame[2], alpha=0.05, color="g")
+
+class BIT_star:
+# ---------initialize and run
+    def __init__(self, show_ellipse=False):
         self.env = env()
         self.xstart, self.xgoal = tuple(self.env.start), tuple(self.env.goal)
-        self.maxiter = 1000 # used for determining how many batches needed
+        self.x0, self.xt = tuple(self.env.start), tuple(self.env.goal)
+        self.maxiter = 3000 # used for determining how many batches needed
         # radius calc
-        self.eta = 1 # bigger or equal to 1
-        self.n = 1000
-        self.nn = 1 # TODO
+        self.eta = 20 # bigger or equal to 1
+        self.m = 1000 # number of samples for one time sample
+        self.d = 3 # dimension we work with
+        self.Path = []
         
         self.edgeCost = {} # corresponding to c
         self.heuristic_edgeCost = {} # correspoinding to c_hat
 
+        # draw ellipse
+        self.show_ellipse = show_ellipse
+
     def run(self):
         self.V = {self.xstart}
         self.E = set()
@@ -51,12 +75,16 @@ class BIT_star:
         self.QE = set()
         self.QV = set()
         self.r = np.inf
-        ind = 0
+        self.ind = 0
         while True:
             # for the first round
+            print(self.ind)
+            print(self.r)
+            self.visualization()
+            # print(len(self.V))
             if len(self.QE) == 0 and len(self.QV) == 0:
                 self.Prune(self.g_T(self.xgoal))
-                self.Xsamples = self.Sample(m, self.g_T(self.xgoal)) # sample function
+                self.Xsamples = self.Sample(self.m, self.g_T(self.xgoal)) # sample function
                 self.Vold = copy.deepcopy(self.V)
                 self.QV = copy.deepcopy(self.V)
                 self.r = self.radius(len(self.V) + len(self.Xsamples))
@@ -80,15 +108,63 @@ class BIT_star:
             else:
                 self.QE = set()
                 self.QV = set()
-            ind += 1
-            if ind > self.maxiter:
-                break
-            return self.T
+            self.ind += 1
 
-    def Sample(self, m, cost):
-        # TODO need the informed rrt
-        pass
-    
+            if self.ind > self.maxiter:
+                break
+        return self.T
+
+# ---------IRRT utils
+    def Sample(self, m, cmax, bias = 0.05, xrand = set()):
+        # sample within a eclipse 
+        print('new sample')
+        if cmax < np.inf:
+            cmin = getDist(self.xgoal, self.xstart)
+            xcenter = np.array([(self.xgoal[0] + self.xstart[0]) / 2, (self.xgoal[1] + self.xstart[1]) / 2, (self.xgoal[2] + self.xstart[2]) / 2])
+            C = self.RotationToWorldFrame(self.xstart, self.xgoal)
+            r = np.zeros(3)
+            r[0] = cmax /2
+            for i in range(1,3):
+                r[i] = np.sqrt(cmax**2 - cmin**2) / 2
+            L = np.diag(r) # R3*3 
+            xball = self.SampleUnitBall(m) # np.array
+            x =  (C@L@xball).T + repmat(xcenter, len(xball.T), 1)
+            # x2 = set(map(tuple, x))
+            self.C = C # save to global var
+            self.xcenter = xcenter
+            self.L = L
+            x2 = set(map(tuple, x[np.array([not isinside(self, state) for state in x])])) # intersection with the state space
+            xrand.update(x2)
+            # if there are samples inside obstacle: recursion
+            if len(x2) < m:
+                return self.Sample(m - len(x2), cmax, bias=bias, xrand=xrand)
+        else:
+            for i in range(m):
+                xrand.add(tuple(sampleFree(self, bias = bias)))
+        return xrand
+
+    def SampleUnitBall(self, n):
+        # uniform sampling in spherical coordinate system in 3D
+        # sample radius
+        r = np.random.uniform(0.0, 1.0, size = n)
+        theta = np.random.uniform(0, np.pi, size = n)
+        phi = np.random.uniform(0, 2 * np.pi, size = n)
+        x = r * np.sin(theta) * np.cos(phi)
+        y = r * np.sin(theta) * np.sin(phi)
+        z = r * np.cos(theta)
+        return np.array([x,y,z])
+
+    def RotationToWorldFrame(self, xstart, xgoal):
+        # S0(n): such that the xstart and xgoal are the center points
+        d = getDist(xstart, xgoal)
+        xstart, xgoal = np.array(xstart), np.array(xgoal)
+        a1 = (xgoal - xstart) / d
+        M = np.outer(a1,[1,0,0])
+        U, S, V = np.linalg.svd(M)
+        C = U@np.diag([1, 1, np.linalg.det(U)*np.linalg.det(V)])@V.T
+        return C
+
+#----------BIT_star particular
     def ExpandVertex(self, v):
         self.QV.difference_update({v})
         Xnear = {x for x in self.Xsamples if getDist(x, v) <= self.r}
@@ -108,9 +184,9 @@ class BIT_star:
         self.V.difference_update({v for v in self.V if self.g_T(v) == np.inf})
 
     def radius(self, q):
-        return 2 * self.eta * (1 + 1/self.n) ** (1/self.n) * \
-            (self.Lambda(self.Xf_hat(self.V)) / self.Zeta ) ** (1/self.n) * \
-            (np.log(q) / q) ** (1/self.n)
+        return 2 * self.eta * (1 + 1/self.d) ** (1/self.d) * \
+            (self.Lambda(self.Xf_hat(self.V)) / self.Zeta() ) ** (1/self.d) * \
+            (np.log(q) / q) ** (1/self.d)
 
     def Lambda(self, inputset):
         # lebesgue measure of a set, defined as 
@@ -196,4 +272,56 @@ class BIT_star:
         else:
             return np.inf
          
-    
+    def visualization(self):
+        if self.ind % 20 == 0:
+            V = np.array(list(self.V))
+            edges = list(map(list, self.E))
+            Path = np.array(self.Path)
+            start = self.env.start
+            goal = self.env.goal
+            # edges = E.get_edge()
+            #----------- list structure
+            # edges = []
+            # for i in self.Parent:
+            #     edges.append([i,self.Parent[i]])
+            #----------- end
+            # generate axis objects
+            ax = plt.subplot(111, projection='3d')
+            
+            # ax.view_init(elev=0.+ 0.03*self.ind/(2*np.pi), azim=90 + 0.03*self.ind/(2*np.pi))
+            # ax.view_init(elev=0., azim=90.)
+            ax.view_init(elev=8., azim=90.)
+            # ax.view_init(elev=-8., azim=180)
+            ax.clear()
+            # drawing objects
+            draw_Spheres(ax, self.env.balls)
+            draw_block_list(ax, self.env.blocks)
+            if self.env.OBB is not None:
+                draw_obb(ax, self.env.OBB)
+            draw_block_list(ax, np.array([self.env.boundary]), alpha=0)
+            draw_line(ax, edges, visibility=0.75, color='g')
+            draw_line(ax, Path, color='r')
+            if self.show_ellipse:
+                draw_ellipsoid(ax, self.C, self.L, self.xcenter) # beware, depending on start and goal position, this might be bad for vis
+            if len(V) > 0:
+                ax.scatter3D(V[:, 0], V[:, 1], V[:, 2], s=2, color='g', )
+            ax.plot(start[0:1], start[1:2], start[2:], 'go', markersize=7, markeredgecolor='k')
+            ax.plot(goal[0:1], goal[1:2], goal[2:], 'ro', markersize=7, markeredgecolor='k')
+            # adjust the aspect ratio
+            xmin, xmax = self.env.boundary[0], self.env.boundary[3]
+            ymin, ymax = self.env.boundary[1], self.env.boundary[4]
+            zmin, zmax = self.env.boundary[2], self.env.boundary[5]
+            dx, dy, dz = xmax - xmin, ymax - ymin, zmax - zmin
+            ax.get_proj = make_get_proj(ax, 1 * dx, 1 * dy, 2 * dy)
+            make_transparent(ax)
+            #plt.xlabel('s')
+            #plt.ylabel('y')
+            ax.set_axis_off()
+            plt.pause(0.0001)
+
+
+if __name__ == '__main__':
+    Newprocess = BIT_star()
+    Newprocess.run()
+    # Xsamples = Newprocess.Sample(1000, 140)
+    # print(len(Xsamples))

Sampling_based_Planning/rrt_3D/rrt_star3D.py

@@ -27,8 +27,8 @@ class rrtstar():
 
         self.i = 0
         self.maxiter = 4000 # at least 2000 in this env
-        self.stepsize = 0.5
-        self.gamma = 500
+        self.stepsize = 2
+        self.gamma = 7
         self.eta = self.stepsize
         self.Path = []
         self.done = False

Sampling_based_Planning/rrt_3D/utils3D.py

@@ -183,7 +183,8 @@ def near(initparams, x):
     cardV = len(initparams.V)
     eta = initparams.eta
     gamma = initparams.gamma
-    r = min(gamma * (np.log(cardV) / cardV ** (1/3)), eta)
+    # min{γRRT∗ (log(card (V ))/ card (V ))1/d, η}
+    r = min(gamma * ((np.log(cardV) / cardV) ** (1/3)), eta)
     if initparams.done: 
         r = 1
     xr = repmat(x, len(V), 1)