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.loadObstacleModel ("iai_maps", "kitchen_area", "kitchen")
ps.selectPathValidation ("Dichotomy", 0)
import datetime as dt
totalTime = dt.timedelta (0)
totalNumberNodes = 0
N = 20
for i in range (N):
ps.clearRoadmap ()
ps.resetGoalConfigs ()
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
t1 = dt.datetime.now ()
ps.solve ()
t2 = dt.datetime.now ()
totalTime += t2 - t1
print (t2-t1)
n = len (ps.client.problem.nodes ())
totalNumberNodes += n
print ("Number nodes: " + str(n))
print ("Average time: " + str ((totalTime.seconds+1e-6*totalTime.microseconds)/float (N)))
print ("Average number nodes: " + str (totalNumberNodes/float (N)))
r = vf.createViewer(); r (q_init)
-0.418879, 0.0, 0.0, 0.0, -0.453786, 0.872665, -0.418879, 0.0
]
res = ps.applyConstraints(q2)
if res[0]:
q2proj = res[1]
else:
raise RuntimeError("Failed to apply constraint.")
ps.selectPathOptimizer("None")
import datetime as dt
totalTime = dt.timedelta(0)
totalNumberNodes = 0
for i in range(20):
ps.client.problem.clearRoadmap()
ps.resetGoalConfigs()
ps.setInitialConfig(q1proj)
ps.addGoalConfig(q2proj)
t1 = dt.datetime.now()
ps.solve()
t2 = dt.datetime.now()
totalTime += t2 - t1
print(t2 - t1)
n = len(ps.client.problem.nodes())
totalNumberNodes += n
print("Number nodes: " + str(n))
print("Average time: " +
str((totalTime.seconds + 1e-6 * totalTime.microseconds) / 20.))
print("Average number nodes: " + str(totalNumberNodes / 20.))
qt = [0, 0, 0, math.sqrt (1/3.), math.sqrt (1/3.), 0.0, math.sqrt (1/3.)]
qt2 = [0, 0, 0, math.sqrt (1 - 0.95**2), 0.95, 0.0, 0.0]
Q.append (qt)
Q.append (qt2)
Q.append ( [0, 0, 0, 0.99, 0.14003571, 0.013, 0.011]) # to remove
r(Q[0])
for i in range(0, len(Q)):
r(Q[i])
time.sleep (0.5)
#robot.isConfigValid(Q[0])
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)
robot.setJointBounds('base_joint_xyz', [xStone-2, xStone+2, yEmu-1, yEmu+2, zEmu-0.5, zEmu+0.5])
# List of configs
q1 = [xStone+2, yEmu+0, zEmu, 1.0, 0.0, 0.0, 0.0]
q2 = [xStone+1.5, yEmu+0.8, zEmu, 0.707106781, 0, 0, 0.707106781]
q3 = [xStone+1, yEmu+1.4, zEmu, 0, 0, 0, 1]
q4 = [xStone+0.5, yEmu+1.7, zEmu, -0.707106781, 0, 0, 0.707106781]
#q5 = [xStone+0, yEmu+2, zEmu, -1, 0, 0, 0]
q5 = [xStone+0, yEmu+2, zEmu, -0.99, 0.14003571, 0.013, 0.011]
q6 = [xStone-0.5, yEmu+1.7, zEmu, -0.707106781, 0, 0, -0.707106781]
q7 = [xStone-1, yEmu+1.4, zEmu, 0, 0, 0, -1]
q8 = [xStone-1.5, yEmu+0.8, zEmu, 0.707106781, 0, 0, -0.707106781]
q9 = [xStone-2, yEmu+0, zEmu, 1, 0, 0, 0]
r(q1)
robot.isConfigValid(q1)
ps.setInitialConfig (q1); ps.addGoalConfig (q2); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q2); ps.addGoalConfig (q3); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q3); ps.addGoalConfig (q4); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q4); ps.addGoalConfig (q5); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q5); ps.addGoalConfig (q6); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q6); ps.addGoalConfig (q7); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q7); ps.addGoalConfig (q8); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q8); ps.addGoalConfig (q9); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q1); ps.addGoalConfig (q9); ps.solve (); ps.resetGoalConfigs ()
nInitialPath = ps.numberPaths()-1 #8
ps.pathLength(nInitialPath)
#ps.addPathOptimizer('RandomShortcut') #9
#ps.optimizePath (nInitialPath)
#ps.pathLength(ps.numberPaths()-1)
ps = ProblemSolver (robot)
cl = robot.client
cl.obstacle.loadObstacleModel('robot_2d_description','cylinder_obstacle','')
# q = [x, y] # limits in URDF file
"""
q1 = [-2, 0]; q2 = [-0.2, 2]; q3 = [0.2, 2]; q4 = [2, 0]
ps.setInitialConfig (q1); ps.addGoalConfig (q2); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q2); ps.addGoalConfig (q3); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q3); ps.addGoalConfig (q4); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q1); ps.addGoalConfig (q4); ps.solve (); #3
"""
q1 = [-2, 0]; q2 = [-1, 1]; q3 = [-1.2, 1.8]; q4 = [-0.2, 1.2]; q5 = [0.5, 1.9]
q6 = [2, 1.5]; q7 = [1, 0.5]; q8 = [2, 0]
ps.setInitialConfig (q1); ps.addGoalConfig (q2); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q2); ps.addGoalConfig (q3); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q3); ps.addGoalConfig (q4); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q4); ps.addGoalConfig (q5); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q5); ps.addGoalConfig (q6); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q6); ps.addGoalConfig (q7); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q7); ps.addGoalConfig (q8); ps.solve (); ps.resetGoalConfigs ()
ps.setInitialConfig (q1); ps.addGoalConfig (q8); ps.solve (); # 7
nInitialPath = ps.numberPaths()-1 #8
ps.pathLength(nInitialPath)
ps.addPathOptimizer("GradientBased")
#ps.addPathOptimizer("Prune")
#ps.addPathOptimizer("PartialRandomShortcut")
import time
robot = Robot ('puzzle_robot') # object5
robot.setJointBounds('base_joint_xyz', [-0.1, 0.1, -0.1, 0.1, -0.1, 0.1])
ps = ProblemSolver (robot)
r = Viewer (ps)
cl = robot.client
pp = PathPlayer (cl, r)
# Patchwork of path
q1 = [0, 0, 0, 1, 0, 0, 0]
q2 = [0, 0, 0, 0.707106781, 0, 0, 0.707106781]
# equivalent to : [0, 0, 0, -0.707106781, 0, 0, -0.707106781] q7
ps.setInitialConfig (q1); ps.addGoalConfig (q2)
ps.solve (); ps.resetGoalConfigs ()
q3 = [0, 0, 0, 0, 0, 0, 1]
# equivalent to : [0, 0, 0, 0, 0, 0, -1] q8
ps.setInitialConfig (q2); ps.addGoalConfig (q3)
ps.solve (); ps.resetGoalConfigs ()
q4 = [0, 0, 0, -0.707106781, 0, 0, 0.707106781]
# equivalent to : [0, 0, 0, 0.707106781, 0, 0, -0.707106781] q9
ps.setInitialConfig (q3); ps.addGoalConfig (q4)
ps.solve (); ps.resetGoalConfigs ()
q5 = [0, 0, 0, -1, 0, 0, 0]
# equivalent to : [0, 0, 0, 1, 0, 0, 0] q1, q10
ps.setInitialConfig (q4); ps.addGoalConfig (q5)
ps.solve (); ps.resetGoalConfigs ()
import time
from hpp.corbaserver.motion_prior.client import Client as MPClient
import rospy
import sys
#from hrp2_irreducible import Robot
from hrp2 import Robot
robot = Robot ()
robot.setJointBounds ("base_joint_xyz", [-1, 1, -3, 3, 0, 2])
from hpp_ros import ScenePublisher, PathPlayer
publisher = ScenePublisher(robot)
from hpp.corbaserver import ProblemSolver
solver = ProblemSolver (robot)
solver.resetGoalConfigs()
#robot.setTranslationBounds (-0.5, 0.5, -3, 3, 0, 1)
#robot.setJointBounds ("base_link", [-0.5, 0.5])
#names = robot.getJointNames()
#q_init = robot.getInitialConfig ()
#print q_init
#q_goal = q_init [::]
#zfloor = 0.648
#q_init[0:3] = [-0.2, 0.5, zfloor]
#q_goal[0:3] = [0.3, 0.8, zfloor]
#original from antonio
zfloor=0.64870180180254433111
#zfloor=0.74970180180254433111
#q1=[0,1.5,zfloor,0.9249114088877176,0,0,-0.38018270043406405,0,0,0,0,0.26179900000000000393,0.1745299999999999907,0,-0.52359900000000003661,0,0,0.1745319999999999927,-0.1745319999999999927,0.1745319999999999927,-0.1745319999999999927,0.1745319999999999927,-0.1745319999999999927,0.26179900000000000393,-0.1745299999999999907,0,-0.52359900000000003661,0,0,0.1745319999999999927,-0.1745319999999999927,0.1745319999999999927,-0.1745319999999999927,0.1745319999999999927,-0.1745319999999999927,0,0,-0.45378600000000002268,0.87266500000000002402,-0.41887900000000000134,0,0,0,-0.45378600000000002268,0.87266500000000002402,-0.41887900000000000134,0]