afftool = AffordanceTool()
afftool.setAffordanceConfig('Support', [0.5, 0.03, 0.00005])
afftool.loadObstacleModel(packageName, "downSlope", "planning", r)
#r.loadObstacleModel (packageName, "ground", "planning")
afftool.visualiseAffordances('Support', r, [0.25, 0.5, 0.5])
r.addLandmark(r.sceneName, 1)
# Setting initial and goal configurations
q_init = rbprmBuilder.getCurrentConfig()
q_init[3:7] = [0.9659, 0, 0.2588, 0]
q_init[0:3] = [-1.25, 1, 1.7]
r(q_init)
#q_init[3:7] = [0.7071,0,0,0.7071]
#q_init [0:3] = [1, 1, 0.65]
rbprmBuilder.setCurrentConfig(q_init)
q_goal = q_init[::]
#q_goal[3:7] = [0.7071,0,0,0.7071]
#q_goal [0:3] = [1, 5, 0.65]; r(q_goal)
q_goal[3:7] = [1, 0, 0, 0]
q_goal[0:3] = [2, 1, 0.60]
r(q_goal)
#q_goal[3:7] = [0.9659,0,0.2588,0]
#q_goal[7:10] = [vMax,0,-2]
#q_goal [0:3] = [0, 1, 0.8]; r(q_goal)
r(q_goal)
#~ q_goal [0:3] = [-1.5, 0, 0.63]; r (q_goal)
# Choosing a path optimizer
ps.setInitialConfig(q_init)
tested = Builder ()
tested.loadModel(urdfNameTested, urdfNameRoms, rootJointType, meshPackageName, packageName, urdfSuffix, srdfSuffix)
#~ tested.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ tested.setFilter(['hrp2_lleg_rom','hrp2_rleg_rom'])
ps = ProblemSolver( tested )
r = Viewer (ps)
r.loadObstacleModel (packageName, scene, "planning")
tested.setJointBounds ("base_joint_xyz", [-10.,10,-10,10,0,20])
ps.client.problem.selectConFigurationShooter("RbprmShooter")
q_init = tested.getCurrentConfig ();
q_init [0:3] = [-10, -0.82, 1.25]; tested.setCurrentConfig (q_init); r (q_init)
q_goal = q_init [::]
q_goal [0:3] = [-9, -0.65, 1.25]; r (q_goal)
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
t = ps.solve ()
res = {}
x_start = -1.5
y_start = 0
x_max = 2.84
y_max = 2.65
iter_step = 0.01
res = {}
rbprmBuilder.setFilter(['hyq_rhleg_rom', 'hyq_lfleg_rom', 'hyq_rfleg_rom','hyq_lhleg_rom'])
rbprmBuilder.setNormalFilter('hyq_lhleg_rom', [0,0,1], 0.9)
rbprmBuilder.setNormalFilter('hyq_rfleg_rom', [0,0,1], 0.9)
rbprmBuilder.setNormalFilter('hyq_lfleg_rom', [0,0,1], 0.9)
rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.1,0.1,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
q_init = [-6,-3,0.8,1,0,0,0]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
q_goal = [4, 4, 0.8, 1, 0, 0, 0]; r (q_goal)
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.client.problem.selectConFigurationShooter("RbprmShooter")
ps.client.problem.selectPathValidation("RbprmPathValidation",0.01)
r.loadObstacleModel (packageName, name_of_scene, "planning")
r.addLandmark(r.sceneName,1)
#~ ps.solve ()
t = ps.solve ()
if isinstance(t, list):
t = t[0]* 3600000 + t[1] * 60000 + t[2] * 1000 + t[3]
#~ rbprmBuilder.setNormalFilter('hrp2_rarm_rom', [0,0,1], 0.5)
#~ rbprmBuilder.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hrp2_rleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.,0,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [0, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
q_init [0:3] = [0.1, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
#~ q_goal [0:3] = [1.49, -0.65, 1.25]; r (q_goal)
q_goal [0:3] = [2.1, -0.82, 1.0]; r (q_goal)
q_goal [0:3] = [3.1, -0.82, 0.55]; r (q_goal)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
rbprmBuilder.setAffordanceFilter('hyq_lhleg_rom', ['Support',])
rbprmBuilder.setAffordanceFilter('hyq_rfleg_rom', ['Support',])
rbprmBuilder.setAffordanceFilter('hyq_lfleg_rom', ['Support',])
rbprmBuilder.setAffordanceFilter('hyq_rhleg_rom', ['Support', 'Lean'])
# We also bound the rotations of the torso.
rbprmBuilder.boundSO3([-0.4,0.4,-3,3,-3,3])
# Creating an instance of HPP problem solver and the viewer
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
r.loadObstacleModel (packageName, "darpa", "planning")
# Setting initial and goal configurations
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [-2, 0, 0.63]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
q_goal = q_init [::]
q_goal [0:3] = [3, 0, 0.63]; r (q_goal)
# Choosing a path optimizer
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
from hpp.corbaserver.affordance import Client
c = Client ()
c.affordance.analyseAll ()
objs = c.affordance.getAffordancePoints ("Support")
import random
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q0 = rbprmBuilder.getCurrentConfig ();
q_init = rbprmBuilder.getCurrentConfig (); r (q_init)
q_goal = q_init [::]
q_goal [0:3] = [0.19, 0.05, 0.9]; r (q_goal)
#~ fullBody.client.basic.robot.setJointConfig('base_joint_SO3',[0.7316888688738209, 0, -0.6816387600233341, 0]); q_init = rbprmBuilder.getCurrentConfig (); r (q_init)
rbprmBuilder.client.basic.robot.setJointConfig('base_joint_SO3',[0.7316888688738209, 0, 0.6816387600233341, 0]); q_init = rbprmBuilder.getCurrentConfig (); r (q_init)
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [-1, 0.05, 0.4]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_0 [0:3] = [-0.2, 0, 0.3]; r (q_0)
q_goal [0:3] = [0.13, 0.05, 0.8]; r (q_goal)
#~ q_init [0:6] = [0.0, -2.2, 2.0, 0.7316888688738209, 0.0, 0.6816387600233341];
#~ rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
from hpp.corbaserver.affordance.affordance import AffordanceTool
afftool = AffordanceTool ()
#~ rbprmBuilder.setNormalFilter('hrp2_rarm_rom', [0,0,1], 0.5)
#~ rbprmBuilder.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hrp2_rleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.,0,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [0, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
q_init [0:3] = [0.1, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal [0:3] = [1.49, -0.65, 1.25]; r (q_goal)
#~ q_goal [0:3] = [1.2, -0.65, 1.1]; r (q_goal)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.client.problem.selectConFigurationShooter("RbprmShooter")
#~ rbprmBuilder.setNormalFilter('hrp2_rarm_rom', [0,0,1], 0.5)
#~ rbprmBuilder.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hrp2_rleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.,0,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [-0., 0, 0.58]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0.2, 0, 0.48]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
#~ q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
#~ [0.8, -0.82, -0.32, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
q_goal [0:3] = [0.8, 0, -0.07,];
q_goal [0:3] = [0.8, 0, 0.27,];
#~ q_goal [0:3] = [2.0, 0, 0.58,];
#~ [2.0, 0, 0.58, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
#~ q_goal [0:3] = [0.8, 0, 0.17,];
#~ q_goal [0:3] = [1.2, -0.65, 1.1]; r (q_goal)
tested = Builder ()
tested.loadModel(urdfNameTested, urdfNameRoms, rootJointType, meshPackageName, packageName, urdfSuffix, srdfSuffix)
#~ tested.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ tested.setFilter(['hrp2_lleg_rom','hrp2_rleg_rom'])
ps = ProblemSolver( tested )
r = Viewer (ps)
r.loadObstacleModel (packageName, scene, "planning")
tested.setJointBounds ("base_joint_xyz", [-10.,10,-10,10,0,20])
ps.client.problem.selectConFigurationShooter("RbprmShooter")
q_init = tested.getCurrentConfig ();
q_init [0:3] = [-10, -0.82, 1.25]; tested.setCurrentConfig (q_init); r (q_init)
q_goal = q_init [::]
q_goal [0:3] = [-9, -0.65, 1.25]; r (q_goal)
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
t = ps.solve ()
res = {}
x_start = 0
y_start = 0
x_max = 2
y_max = 1.64
iter_step = 0.01
res = {}
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q0 = rbprmBuilder.getCurrentConfig ();
q_init = rbprmBuilder.getCurrentConfig (); r (q_init)
q_goal = q_init [::]
q_init = rbprmBuilder.getCurrentConfig ();
q_init[0:3] = [0.15, -0.45, 0.8]; r(q_init)
rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_goal[0:3] = [1.2,-1,0.5]; r(q_goal)
q_goal[0:3] = [0.2,-1.1,0.58]; r(q_goal)
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.client.problem.selectConFigurationShooter("RbprmShooter")
ps.client.problem.selectPathValidation("RbprmPathValidation",0.01)
r.loadObstacleModel (packageName, "car", "planning")
t = ps.solve ()
print (t)
if isinstance(t, list):
t = t[0]* 3600000 + t[1] * 60000 + t[2] * 1000 + t[3]
f = open('log.txt', 'a')
#~ rbprmBuilder.setNormalFilter('hrp2_rarm_rom', [0,0,1], 0.5)
#~ rbprmBuilder.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hrp2_rleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.,0,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
q_init [0:3] = [1.49, -0.65, 1.25]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, 0, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
q_init [3:7] = [0, 0, 0, 1 ]
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
#~ q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal [0:3] = [0, 0, 0.648702]; r (q_goal)
#~ q_goal [0:3] = [1.2, -0.65, 1.1]; r (q_goal)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
rbprmBuilder.setAffordanceFilter('SpidermanLFootSphere', affordanceTypeHand)
rbprmBuilder.setAffordanceFilter('SpidermanRFootSphere', affordanceTypeHand)
rbprmBuilder.setAffordanceFilter('SpidermanLHandSphere', affordanceTypeHand)
rbprmBuilder.setAffordanceFilter('SpidermanRHandSphere', affordanceTypeHand)
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_init [0:3] = [-0.05, -0.82, 1]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0.1, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
#~ q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal [0:3] = [-0.05, -0.82, 4.4]; rbprmBuilder.setCurrentConfig (q_goal); r (q_goal)
#~ q_goal [0:3] = [3, -0.82, 6]; r(q_goal)
#~ q_goal [0:3] = [1.2, -0.65, 1.1]; r (q_goal)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
tested = Builder()
tested.loadModel(urdfNameTested, urdfNameRoms, rootJointType, meshPackageName,
packageName, urdfSuffix, srdfSuffix)
#~ tested.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ tested.setFilter(['hrp2_lleg_rom','hrp2_rleg_rom'])
ps = ProblemSolver(tested)
r = Viewer(ps)
r.loadObstacleModel(packageName, scene, "planning")
tested.setJointBounds("base_joint_xyz", [-10., 10, -10, 10, 0, 20])
ps.client.problem.selectConFigurationShooter("RbprmShooter")
q_init = tested.getCurrentConfig()
q_init[0:3] = [-10, -0.82, 1.25]
tested.setCurrentConfig(q_init)
r(q_init)
q_goal = q_init[::]
q_goal[0:3] = [-9, -0.65, 1.25]
r(q_goal)
ps.setInitialConfig(q_init)
ps.addGoalConfig(q_goal)
t = ps.solve()
res = {}
x_start = 0
y_start = 0
x_max = 2
y_max = 1.64
iter_step = 0.01
#~ rbprmBuilder.setNormalFilter('hrp2_lleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hrp2_rleg_rom', [0,0,1], 0.9)
#~ rbprmBuilder.setNormalFilter('hyq_rhleg_rom', [0,0,1], 0.9)
rbprmBuilder.boundSO3([-0.,0,-1,1,-1,1])
#~ from hpp.corbaserver.rbprm. import ProblemSolver
from hpp.corbaserver.rbprm.problem_solver import ProblemSolver
ps = ProblemSolver( rbprmBuilder )
r = Viewer (ps)
q_init = rbprmBuilder.getCurrentConfig ();
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_init [0:3] = [-0.05, -0.82, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0.1, -0.82, 0.648702]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [0:3] = [0, -0.63, 0.6]; rbprmBuilder.setCurrentConfig (q_init); r (q_init)
#~ q_init [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal = q_init [::]
#~ q_goal [3:7] = [ 0.98877108, 0. , 0.14943813, 0. ]
q_goal [0:3] =[-0.5,-0.82,0.55]; r (q_goal)
#~ q_goal [0:3] = [3, -0.82, 6]; r(q_goal)
#~ q_goal [0:3] = [1.2, -0.65, 1.1]; r (q_goal)
#~ ps.addPathOptimizer("GradientBased")
ps.addPathOptimizer("RandomShortcut")
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
