[demos] memmo : maze : add a script with and without constraining the orientation

script/scenarios/memmo/talos_mazeEas_oriented_path.py

+from hpp.corbaserver.rbprm.talos_abstract import Robot
+from hpp.gepetto import Viewer
+from hpp.corbaserver import Client
+from hpp.corbaserver import ProblemSolver
+import time
+from tools.sample_root_config import generate_random_conf_with_orientation
+
+Robot.urdfName += "_large"
+CONFIRM_SAMPLING = False
+vMax = 0.3# linear velocity bound for the root
+aMax = 0.1 # linear acceleration bound for the root
+extraDof = 6
+mu=0.5# coefficient of friction
+# Creating an instance of the helper class, and loading the robot
+rbprmBuilder = Robot()
+# Define bounds for the root : bounding box of the scenario
+root_bounds = [0,18.5,0.,24., 0.98, 0.98]
+rbprmBuilder.setJointBounds ("root_joint", root_bounds)
+# As this scenario only consider walking, we fix the DOF of the torso :
+rbprmBuilder.setJointBounds ('torso_1_joint', [0,0])
+rbprmBuilder.setJointBounds ('torso_2_joint', [0.006761,0.006761])
+
+# The following lines set constraint on the valid configurations:
+# a configuration is valid only if all limbs can create a contact with the corresponding afforcances type
+rbprmBuilder.setFilter(['talos_lleg_rom','talos_rleg_rom'])
+rbprmBuilder.setAffordanceFilter('talos_lleg_rom', ['Support',])
+rbprmBuilder.setAffordanceFilter('talos_rleg_rom', ['Support'])
+# We also bound the rotations of the torso. (z, y, x)
+rbprmBuilder.boundSO3([-4.,4.,-0.1,0.1,-0.1,0.1])
+# Add 6 extraDOF to the problem, used to store the linear velocity and acceleration of the root
+rbprmBuilder.client.robot.setDimensionExtraConfigSpace(extraDof)
+# We set the bounds of this extraDof with velocity and acceleration bounds (expect on z axis)
+rbprmBuilder.client.robot.setExtraConfigSpaceBounds([-vMax,vMax,-vMax,vMax,0,0,-aMax,aMax,-aMax,aMax,0,0])
+indexECS = rbprmBuilder.getConfigSize() - rbprmBuilder.client.robot.getDimensionExtraConfigSpace()
+
+# Creating an instance of HPP problem solver
+ps = ProblemSolver( rbprmBuilder )
+# define parameters used by various methods : 
+ps.setParameter("Kinodynamic/velocityBound",vMax)
+ps.setParameter("Kinodynamic/accelerationBound",aMax)
+# force the orientation of the trunk to match the direction of the motion
+ps.setParameter("Kinodynamic/forceYawOrientation",True)
+ps.setParameter("DynamicPlanner/sizeFootX",0.2)
+ps.setParameter("DynamicPlanner/sizeFootY",0.12)
+ps.setParameter("DynamicPlanner/friction",mu)
+# sample only configuration with null velocity and acceleration :
+ps.setParameter("ConfigurationShooter/sampleExtraDOF",False)
+ps.setParameter("PathOptimization/RandomShortcut/NumberOfLoops",500)
+
+# initialize the viewer :
+from hpp.gepetto import ViewerFactory
+vf = ViewerFactory (ps)
+
+# load the module to analyse the environnement and compute the possible contact surfaces
+from hpp.corbaserver.affordance.affordance import AffordanceTool
+afftool = AffordanceTool ()
+afftool.setAffordanceConfig('Support', [0.5, 0.03, 0.00005])
+afftool.loadObstacleModel ("hpp_environments", "multicontact/maze_easy", "planning", vf)
+v = vf.createViewer(displayArrows = True)
+#afftool.visualiseAffordances('Support', v, v.color.lightBrown)
+v.addLandmark(v.sceneName,1)
+
+
+'''
+# Setting initial configuration
+q_init = rbprmBuilder.getCurrentConfig ();
+q_init[8] = 0.006761 # torso 2 position in reference config
+q_init [0:3] = [-0.9,1.5,0.98]
+q_init[-6:-3] = [0.07,0,0]
+v (q_init)
+ps.setInitialConfig (q_init)
+# set goal config
+rbprmBuilder.setCurrentConfig (q_init)
+q_goal = q_init [::]
+q_goal[0:3] = [2,2.6,0.98]
+q_goal[-6:-3] = [0.1,0,0]
+v(q_goal)
+'''
+
+import numpy as np
+
+
+while(True):
+    q_init = generate_random_conf_with_orientation(rbprmBuilder,root_bounds)
+    v (q_init)
+    ps.setInitialConfig (q_init)
+    if CONFIRM_SAMPLING:
+      print "Accept?y/n"
+      user_in = raw_input()
+      if user_in == 'y':
+          break
+    else:
+      break
+
+
+#set goal
+while(True):
+    q_goal = generate_random_conf_with_orientation(rbprmBuilder,root_bounds)
+    v (q_goal)
+    if CONFIRM_SAMPLING:
+      print "Accept?y/n"
+      user_in = raw_input()
+      if user_in == 'y':
+          break
+    else:
+      break
+
+ps.resetGoalConfigs()
+ps.addGoalConfig (q_goal)
+
+
+
+# Choosing RBPRM shooter and path validation methods.
+ps.selectConfigurationShooter("RbprmShooter")
+ps.addPathOptimizer ("RandomShortcutDynamic")
+ps.selectPathValidation("RbprmPathValidation",0.05)
+# Choosing kinodynamic methods :
+ps.selectSteeringMethod("RBPRMKinodynamic")
+ps.selectDistance("Kinodynamic")
+ps.selectPathPlanner("DynamicPlanner")
+
+# Solve the planning problem :
+ps.setMaxIterPathPlanning(50000)
+t = ps.solve ()
+#tic = time.time()
+#v.solveAndDisplay('rm',5,0.01)
+#ps.optimizePath(0)
+#print "solve in " + str(time.time()-tic)
+
+#raw_input()
+
+
+print "Guide planning time : ",t
+
+for i in range(10):
+    print "Optimize path, "+str(i+1)+"/10 ... "
+    ps.optimizePath(ps.numberPaths()-1)
+pathId = ps.numberPaths()-1
+
+
+# display solution : 
+from hpp.gepetto import PathPlayer
+pp = PathPlayer (v)
+pp.dt=0.1
+pp.displayVelocityPath(pathId)
+v.client.gui.setVisibility("path_"+str(pathId)+"_root","ALWAYS_ON_TOP")
+pp.dt = 0.01
+pp(pathId)
+
+pathId = ps.numberPaths()-1
+# move the robot out of the view before computing the contacts
+q_far = q_init[::]
+q_far[2] = -2
+v(q_far)
+
+#tStart = time.time()
+#for i in range(1000):
+#    rbprmBuilder.isConfigValid(q_init)
+#tot = time.time() - tStart
+#print "avg time : ",tot/1000.
+
+

script/scenarios/memmo/talos_mazeEas_path.py

@@ -3,11 +3,13 @@ from hpp.gepetto import Viewer
 from hpp.corbaserver import Client
 from hpp.corbaserver import ProblemSolver
 import time
-
+from tools.sample_root_config import generate_random_conf_without_orientation
 Robot.urdfName += "_large"
 
+CONFIRM_SAMPLING = False
+
 vMax = 0.3# linear velocity bound for the root
-aMax = 0.1 # linear acceleration bound for the root
+aMax = 0.2 # linear acceleration bound for the root
 extraDof = 6
 mu=0.5# coefficient of friction
 # Creating an instance of the helper class, and loading the robot
@@ -44,7 +46,7 @@ ps.setParameter("DynamicPlanner/sizeFootY",0.12)
 ps.setParameter("DynamicPlanner/friction",mu)
 # sample only configuration with null velocity and acceleration :
 ps.setParameter("ConfigurationShooter/sampleExtraDOF",False)
-ps.setParameter("PathOptimization/RandomShortcut/NumberOfLoops",100)
+ps.setParameter("PathOptimization/RandomShortcut/NumberOfLoops",500)
 
 # initialize the viewer :
 from hpp.gepetto import ViewerFactory
@@ -78,45 +80,31 @@ v(q_goal)
 
 import numpy as np
 
-def generate_random_point(bounds):
-    return np.random.rand(3,1)*(bounds[:,1:]-bounds[:,0:1]) + bounds[:,0:1]
-
-def generate_random_conf(bounds):
-    q = rbprmBuilder.getCurrentConfig ();
-    while True:
-        xyz = generate_random_point(np.array(root_bounds).reshape(-1,2))[:,0]
-        angle = 0#np.random.rand()*np.pi*0.7
-        quat = np.array([0,0,np.sin(angle/2), np.cos(angle/2)])
-        q[0:3] = xyz
-        q[3:7] = quat
-	q[8] = 0.006761
-        q[-6:-3] = [0.1*np.cos(angle),0.1*np.sin(angle),0]
-	v(q)
-        status,message = rbprmBuilder.isConfigValid(q)
-        if status:
-            return q
-	else:
-	    print "Getting invalid config. try again."
-	    print message
 #set init
 while(True):
-    q_init = generate_random_conf(root_bounds)
+    q_init = generate_random_conf_without_orientation(rbprmBuilder,root_bounds)
     v (q_init)
     ps.setInitialConfig (q_init)
-    print "Accept?y/n"
-    user_in = raw_input()
-    if user_in == 'y':
-        break
+    if CONFIRM_SAMPLING:
+      print "Accept?y/n"
+      user_in = raw_input()
+      if user_in == 'y':
+          break
+    else:
+      break
 
 
 #set goal
 while(True):
-    q_goal = generate_random_conf(root_bounds)
+    q_goal = generate_random_conf_without_orientation(rbprmBuilder,root_bounds)
     v (q_goal)
-    print "Accept?y/n"
-    user_in = raw_input()
-    if user_in == 'y':
-        break
+    if CONFIRM_SAMPLING:
+      print "Accept?y/n"
+      user_in = raw_input()
+      if user_in == 'y':
+          break
+    else:
+      break
 
 ps.resetGoalConfigs()
 ps.addGoalConfig (q_goal)
@@ -133,29 +121,34 @@ ps.selectDistance("Kinodynamic")
 ps.selectPathPlanner("DynamicPlanner")
 
 # Solve the planning problem :
-#ps.setMaxIterPathPlanning(1000)
+ps.setMaxIterPathPlanning(100000)
 t = ps.solve ()
-#tic = time.time()
 #v.solveAndDisplay('rm',5,0.01)
-#ps.optimizePath(0)
-#print "solve in " + str(time.time()-tic)
 
-#raw_input()
+print "Guide planning time : ",t
+
+
+for i in range(10):
+    print "Optimize path, "+str(i+1)+"/10 ... "
+    ps.optimizePath(ps.numberPaths()-1)
+
+ps.extractPath(ps.numberPaths()-1,1.,ps.pathLength(ps.numberPaths()-1)-1.)
+pathId = ps.numberPaths()-1
+q_init = ps.configAtParam(pathId,0)
+q_goal = ps.configAtParam(pathId,ps.pathLength(pathId))
 
 
-print "Guide planning time : ",t
 
 
 # display solution : 
 from hpp.gepetto import PathPlayer
 pp = PathPlayer (v)
 pp.dt=0.1
-pp.displayVelocityPath(1)
-v.client.gui.setVisibility("path_1_root","ALWAYS_ON_TOP")
+pp.displayVelocityPath(pathId)
+v.client.gui.setVisibility("path_"+str(pathId)+"_root","ALWAYS_ON_TOP")
 pp.dt = 0.01
-pp(1)
+pp(pathId)
 
-pathId = ps.numberPaths()-1
 # move the robot out of the view before computing the contacts
 q_far = q_init[::]
 q_far[2] = -2