Files
PathPlanning/Sampling-based Planning/rrt_3D/utils3D.py
T
2020-07-26 01:23:46 -07:00

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Python

import numpy as np
from numpy.matlib import repmat
import pyrr as pyrr
import os
import sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../../Sampling-based Planning/")
from rrt_3D.plot_util3D import visualization
def getRay(x, y):
direc = [y[0] - x[0], y[1] - x[1], y[2] - x[2]]
return np.array([x, direc])
def getAABB(blocks):
AABB = []
for i in blocks:
AABB.append(np.array([np.add(i[0:3], -0), np.add(i[3:6], 0)])) # make AABBs alittle bit of larger
return AABB
def getDist(pos1, pos2):
return np.sqrt(sum([(pos1[0] - pos2[0]) ** 2, (pos1[1] - pos2[1]) ** 2, (pos1[2] - pos2[2]) ** 2]))
''' The following utils can be used for rrt or rrt*,
required param initparams should have
env, environement generated from env3D
V, node set
E, edge set
i, nodes added
maxiter, maximum iteration allowed
stepsize, leaf growth restriction
'''
def sampleFree(initparams):
'''biased sampling'''
x = np.random.uniform(initparams.env.boundary[0:3], initparams.env.boundary[3:6])
i = np.random.random()
if isinside(initparams, x):
return sampleFree(initparams)
else:
if i < 0.1:
return initparams.env.goal + 1
else:
return x
return x
# ---------------------- Collision checking algorithms
def isinside(initparams, x):
'''see if inside obstacle'''
for i in initparams.env.blocks:
if i[0] <= x[0] < i[3] and i[1] <= x[1] < i[4] and i[2] <= x[2] < i[5]:
return True
return False
def isinbound(i, x):
if i[0] <= x[0] < i[3] and i[1] <= x[1] < i[4] and i[2] <= x[2] < i[5]:
return True
return False
def lineSphere(p0, p1, ball):
# https://cseweb.ucsd.edu/classes/sp19/cse291-d/Files/CSE291_13_CollisionDetection.pdf
c, r = ball[0:3], ball[-1]
line = [p1[0] - p0[0], p1[1] - p0[1], p1[2] - p0[2]]
d1 = [c[0] - p0[0], c[1] - p0[1], c[2] - p0[2]]
t = (1 / (line[0] * line[0] + line[1] * line[1] + line[2] * line[2])) * (
line[0] * d1[0] + line[1] * d1[1] + line[2] * d1[2])
if t <= 0:
if (d1[0] * d1[0] + d1[1] * d1[1] + d1[2] * d1[2]) <= r ** 2: return True
elif t >= 1:
d2 = [c[0] - p1[0], c[1] - p1[1], c[2] - p1[2]]
if (d2[0] * d2[0] + d2[1] * d2[1] + d2[2] * d2[2]) <= r ** 2: return True
elif 0 < t < 1:
x = [p0[0] + t * line[0], p0[1] + t * line[1], p0[2] + t * line[2]]
k = [c[0] - x[0], c[1] - x[1], c[2] - x[2]]
if (k[0] * k[0] + k[1] * k[1] + k[2] * k[2]) <= r ** 2: return True
return False
def lineAABB(p0, p1, dist, aabb):
# https://www.gamasutra.com/view/feature/131790/simple_intersection_tests_for_games.php?print=1
# aabb should have the attributes of P, E as center point and extents
mid = [(p0[0] + p1[0]) / 2, (p0[1] + p1[1]) / 2, (p0[2] + p1[2]) / 2] # mid point
I = [(p1[0] - p0[0]) / dist, (p1[1] - p0[1]) / dist, (p1[2] - p0[2]) / dist] # unit direction
hl = dist / 2 # radius
T = [aabb.P[0] - mid[0], aabb.P[1] - mid[1], aabb.P[2] - mid[2]]
# do any of the principal axis form a separting axis?
if abs(T[0]) > (aabb.E[0] + hl * abs(I[0])): return False
if abs(T[1]) > (aabb.E[1] + hl * abs(I[1])): return False
if abs(T[2]) > (aabb.E[2] + hl * abs(I[2])): return False
# I.cross(x axis) ?
r = aabb.E[1] * abs(I[2]) + aabb.E[2] * abs(I[1])
if abs(T[1] * I[2] - T[2] * I[1]) > r: return False
# I.cross(y axis) ?
r = aabb.E[0] * abs(I[2]) + aabb.E[2] * abs(I[0])
if abs(T[2] * I[0] - T[0] * I[2]) > r: return False
# I.cross(z axis) ?
r = aabb.E[0] * abs(I[1]) + aabb.E[1] * abs(I[0])
if abs(T[0] * I[1] - T[1] * I[0]) > r: return False
return True
def lineOBB(p0, p1, dist, obb):
# transform points to obb frame
res = obb.T@np.column_stack([np.array([p0,p1]),[1,1]]).T
# record old position and set the position to origin
oldP, obb.P= obb.P, [0,0,0]
# calculate segment-AABB testing
ans = lineAABB(res[0:3,0],res[0:3,1],dist,obb)
# reset the position
obb.P = oldP
return ans
def isCollide(initparams, x, child, dist=None):
'''see if line intersects obstacle'''
'''specified for expansion in A* 3D lookup table'''
if dist==None:
dist = getDist(x, child)
# check in bound
if not isinbound(initparams.env.boundary, child):
return True, dist
# check collision in AABB
for i in range(len(initparams.env.AABB)):
if lineAABB(x, child, dist, initparams.env.AABB[i]):
return True, dist
# check collision in ball
for i in initparams.env.balls:
if lineSphere(x, child, i):
return True, dist
# check collision with obb
for i in initparams.env.OBB:
if lineOBB(x, child, dist, i):
return True, dist
return False, dist
# ---------------------- leaf node extending algorithms
def nearest(initparams, x):
V = np.array(initparams.V)
if initparams.i == 0:
return initparams.V[0]
xr = repmat(x, len(V), 1)
dists = np.linalg.norm(xr - V, axis=1)
return tuple(initparams.V[np.argmin(dists)])
def near(initparams, x):
x = np.array(x)
V = np.array(initparams.V)
cardV = len(initparams.V)
eta = initparams.eta
gamma = initparams.gamma
r = min(gamma * (np.log(cardV) / cardV), eta)
if initparams.done:
r = 1
if initparams.i == 0:
return [initparams.V[0]]
xr = repmat(x, len(V), 1)
inside = np.linalg.norm(xr - V, axis=1) < r
nearpoints = V[inside]
return np.array(nearpoints)
def steer(initparams, x, y):
dist, step = getDist(y, x), initparams.stepsize
increment = ((y[0] - x[0]) / dist * step, (y[1] - x[1]) / dist * step, (y[2] - x[2]) / dist * step)
xnew = (x[0] + increment[0], x[1] + increment[1], x[2] + increment[2])
# direc = (y - x) / np.linalg.norm(y - x)
# xnew = x + initparams.stepsize * direc
return xnew
def cost(initparams, x):
'''here use the additive recursive cost function'''
if x == tuple(initparams.env.start):
return 0
xparent = initparams.Parent[x]
return cost(initparams, xparent) + getDist(x, xparent)
def path(initparams, Path=[], dist=0):
x = tuple(initparams.env.goal)
while x != tuple(initparams.env.start):
x2 = initparams.Parent[x]
Path.append(np.array([x, x2]))
dist += getDist(x, x2)
x = x2
return Path, dist
class edgeset(object):
def __init__(self):
self.E = {}
def add_edge(self, edge):
x, y = edge[0], edge[1]
if x in self.E:
self.E[x].add(y)
else:
self.E[x] = set()
self.E[x].add(y)
def remove_edge(self, edge):
x, y = edge[0], edge[1]
self.E[x].remove(y)
def get_edge(self):
edges = []
for v in self.E:
for n in self.E[v]:
# if (n,v) not in edges:
edges.append((v, n))
return edges