import numpy as np import pyrr from collections import defaultdict def getRay(x, y): direc = [y[0] - x[0], y[1] - x[1], y[2] - x[2]] return np.array([x, direc]) def getDist(pos1, pos2): return np.sqrt(sum([(pos1[0] - pos2[0]) ** 2, (pos1[1] - pos2[1]) ** 2, (pos1[2] - pos2[2]) ** 2])) def getManDist(pos1, pos2): return sum([abs(pos1[0] - pos2[0]),abs(pos1[1] - pos2[1]),abs(pos1[2] - pos2[2])]) def getNearest(Space,pt): '''get the nearest point on the grid''' mindis,minpt = 1000,None for pts in Space: dis = getDist(pts,pt) if dis < mindis: mindis,minpt = dis,pts return minpt def Heuristic(Space,t): '''Max norm distance''' h = {} for k in Space.keys(): h[k] = max(abs(np.array([t[0]-k[0],t[1]-k[1],t[2]-k[2]]))) return h def hash3D(x): return str(x[0])+' '+str(x[1])+' '+str(x[2]) def dehash(x): return np.array([float(i) for i in x.split(' ')]) 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 isinball(i, x): if getDist(i[0:3], x) <= i[3]: 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 P = [(p0[0] + p1[0]) / 2, (p0[1] + p1[1]) / 2, (p0[2] + p1[2]) / 2] # mid point D = [(p1[0] - p0[0]) / dist, (p1[1] - p0[1]) / dist, (p1[2] - p0[2]) / dist] # unit direction t = dist / 2 # radius # TODO: implement this def StateSpace(env, factor = 0): boundary = env.boundary resolution = env.resolution xmin,xmax = boundary[0]+factor*resolution,boundary[3]-factor*resolution ymin,ymax = boundary[1]+factor*resolution,boundary[4]-factor*resolution zmin,zmax = boundary[2]+factor*resolution,boundary[5]-factor*resolution xarr = np.arange(xmin,xmax,resolution).astype(float) yarr = np.arange(ymin,ymax,resolution).astype(float) zarr = np.arange(zmin,zmax,resolution).astype(float) Space = set() for x in xarr: for y in yarr: for z in zarr: Space.add((x,y,z)) return Space def g_Space(initparams): '''This function is used to get nodes and discretize the space. State space is by x*y*z,3 where each 3 is a point in 3D.''' g = {} Space = StateSpace(initparams.env) for v in Space: g[v] = np.inf # this hashmap initialize all g values at inf return g def isCollide(initparams, x, child): '''see if line intersects obstacle''' ray , dist = getRay(x, child) , getDist(x, child) if not isinbound(initparams.env.boundary,child): return True, dist for i in initparams.env.AABB: shot = pyrr.geometric_tests.ray_intersect_aabb(ray, i) if shot is not None: dist_wall = getDist(x, shot) if dist_wall <= dist: # collide return True, dist for i in initparams.env.balls: if isinball(i, child): return True, dist # shot = pyrr.geometric_tests.ray_intersect_sphere(ray, i) # if shot != []: # dists_ball = [getDist(x, j) for j in shot] # if all(dists_ball <= dist): # collide # return True, dist if lineSphere(x, child, i): return True, dist return False, dist def children(initparams, x): # get the neighbor of a specific state allchild = [] resolution = initparams.env.resolution for direc in initparams.Alldirec: child = tuple(map(np.add,x,np.multiply(direc,resolution))) if isinbound(initparams.env.boundary,child): allchild.append(child) return allchild def obstacleFree(initparams,x): for i in initparams.env.blocks: if isinbound(i,x): return False for i in initparams.env.balls: if isinball(i,x): return False return True def cost(initparams, i,j,settings=0): collide, dist = isCollide(initparams,i,j) if settings == 0: if collide: return np.inf else: return dist if settings == 1: if collide: return np.inf else: return getManDist(i,j) def initcost(initparams): # initialize cost dictionary, could be modifed lateron c = defaultdict(lambda: defaultdict(dict)) # two key dicionary for xi in initparams.X: cdren = children(initparams, xi) for child in cdren: c[xi][child] = cost(initparams, xi, child) return c if __name__ == "__main__": a = [10,2.5,1,1] lineAABB([0,0,0],[1,1,1],)