本文整理汇总了Python中hpp.corbaserver.ProblemSolver.addPathOptimizer方法的典型用法代码示例。如果您正苦于以下问题：Python ProblemSolver.addPathOptimizer方法的具体用法？Python ProblemSolver.addPathOptimizer怎么用？Python ProblemSolver.addPathOptimizer使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类hpp.corbaserver.ProblemSolver的用法示例。
在下文中一共展示了ProblemSolver.addPathOptimizer方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: range
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import addPathOptimizer [as 别名]
for i in range(0, len(Q)-1):
ps.setInitialConfig (Q[i]); ps.addGoalConfig (Q[i+1]); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (Q[0]); ps.addGoalConfig (Q[len(Q)-1]); ps.solve ();
nInitialPath = ps.numberPaths()-1 #8
ps.pathLength(nInitialPath)
#ps.addPathOptimizer('RandomShortcut') #9
#ps.optimizePath (nInitialPath)
#ps.pathLength(ps.numberPaths()-1)
#ps.clearPathOptimizers()
ps.addPathOptimizer("GradientBased")
ps.optimizePath (nInitialPath)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
pp(ps.numberPaths()-1)
ps.configAtParam(2,0.5)
r(ps.configAtParam(0,2))
ps.getWaypoints (0)
ps.getWaypoints (ps.numberPaths()-1)
# plot paths
import numpy as np
dt = 0.1示例2: vf
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import addPathOptimizer [as 别名]
vf (q_init)
q_goal [0:2] = [-3.2, -4]
rank = robot.rankInConfiguration ['l_shoulder_lift_joint']
q_goal [rank] = 0.5
rank = robot.rankInConfiguration ['l_elbow_flex_joint']
q_goal [rank] = -0.5
rank = robot.rankInConfiguration ['r_shoulder_lift_joint']
q_goal [rank] = 0.5
rank = robot.rankInConfiguration ['r_elbow_flex_joint']
q_goal [rank] = -0.5
vf (q_goal)
vf.loadObstacleModel ("iai_maps", "kitchen_area", "kitchen")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.addPathOptimizer ("RandomShortcut")
# print (ps.solve ())
## Uncomment this to connect to a viewer server and play solution paths
#
# v = vf.createViewer()
# from hpp.gepetto import PathPlayer
# pp = PathPlayer (v)
# pp (0)
# pp (1)
示例3: len
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import addPathOptimizer [as 别名]
#ps.readRoadmap ('/local/mcampana/devel/hpp/data/puzzle_easy_RRT.rdm')
#ps.readRoadmap ('/local/mcampana/devel/hpp/data/puzzle_easy_PRM1.rdm') # srand # problem ?
#ps.readRoadmap ('/local/mcampana/devel/hpp/data/puzzle_easy_PRM1.rdm') # srand 1453110445(909sec) [COLL!]
#ps.readRoadmap ('/local/mcampana/devel/hpp/data/puzzle_easy_PRM2.rdm') # srand # just after solve, GB OK. But after readroadmap+solve, segfault quaternions....
ps.readRoadmap ('/local/mcampana/devel/hpp/data/puzzle_easy_PRM_test1.rdm') #srand 1454520599 working0.05
# srand 1454521537 (no RM saved) works 7 -> 5, best 0.2
ps.solve ()
ps.pathLength(0)
len(ps.getWaypoints (0))
r(q1)
import numpy as np
"""
ps.addPathOptimizer("Prune")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
len(ps.getWaypoints (ps.numberPaths()-1))
"""
ps.clearPathOptimizers()
cl.problem.setAlphaInit (0.05)
ps.addPathOptimizer("GradientBased")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
tGB = cl.problem.getTimeGB ()
timeValuesGB = cl.problem.getTimeValues ()示例4:
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import addPathOptimizer [as 别名]
q2hard = [7.60, -2.41, 0.545, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.8, 0.0, -0.4, -0.55, 0.0, -0.6, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -2.8, 0.0, 0.1, -0.2, -0.1, 0.4, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -0.2, 0.6, -0.1, 1.2, -0.4, 0.2, -0.3, 0.0, -0.4, 0.2, 0.7, 0.0]
robot.isConfigValid(q1)
robot.isConfigValid(q2)
# qf should be invalid
qf = [1, -3, 3, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.2, 1.0, -0.4, -1.0, 0.0, -0.2, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -1.5, -0.2, 0.1, -0.3, 0.1, 0.1, 0.174532, -0.174532, 0.174532, -0.174532, 0.174532, -0.174532, -0.2, 0.6, -0.453786, 0.872665, -0.418879, 0.2, -0.4, 0.0, -0.453786, 0.1, 0.7, 0.0]
robot.isConfigValid(qf)
ps.setInitialConfig (q1); ps.addGoalConfig (q2); ps.solve ()
ps.solve ()
ps.pathLength(0)
ps.addPathOptimizer('RandomShortcut')
ps.optimizePath (0)
ps.pathLength(1)
ps.clearPathOptimizers()
ps.addPathOptimizer("GradientBased")
ps.optimizePath (0)
ps.numberPaths()
ps.pathLength(ps.numberPaths()-1)
pp(ps.numberPaths()-1)
r(ps.configAtParam(0,2))
ps.getWaypoints (0)
示例5: range
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import addPathOptimizer [as 别名]
import datetime as dt
totalSolveTime = dt.timedelta (0)
totalOptimTime = dt.timedelta (0)
totalNumberNodes = 0
N = 20
for i in range (N):
ps.clearPathOptimizers()
ps.clearRoadmap ()
ps.resetGoalConfigs ()
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
t1 = dt.datetime.now ()
ps.solve ()
t2 = dt.datetime.now ()
ps.addPathOptimizer ("SplineGradientBased_bezier3")
ps.optimizePath (ps.numberPaths() - 1)
t3 = dt.datetime.now ()
totalSolveTime += t2 - t1
totalOptimTime += t3 - t2
print "Solve:", t2-t1
print "Optim:", t3-t2
n = len (ps.client.problem.nodes ())
totalNumberNodes += n
print ("Number nodes: " + str(n))
print ("Average solve time: " + str ((totalSolveTime.seconds+1e-6*totalSolveTime.microseconds)/float (N)))
print ("Average optim time: " + str ((totalOptimTime.seconds+1e-6*totalOptimTime.microseconds)/float (N)))
print ("Average number nodes: " + str (totalNumberNodes/float (N)))