print "final root position : ", q_goal
ps.setInitialConfig(q_init)
ps.addGoalConfig(q_goal)
# write problem in files :
f = open(statusFilename, "w")
f.write("q_init= " + str(q_init) + "\n")
f.write("q_goal= " + str(q_goal) + "\n")
f.close()
# Choosing RBPRM shooter and path validation methods.
ps.selectConfigurationShooter("RbprmShooter")
ps.selectPathValidation("RbprmPathValidation", 0.05)
# Choosing kinodynamic methods :
ps.selectSteeringMethod("RBPRMKinodynamic")
ps.selectDistance("Kinodynamic")
ps.selectPathPlanner("DynamicPlanner")
# Solve the planning problem :
success = ps.client.problem.prepareSolveStepByStep()
if not success:
print "planning failed."
import sys
sys.exit(1)
ps.client.problem.finishSolveStepByStep()
try:
# display solution :
from hpp.gepetto import PathPlayer
def __call__(self,q):
return
v = FakeViewer()
#afftool.visualiseAffordances('Support', v, v.color.lightBrown)
q_init = rbprmBuilder.getCurrentConfig ();
q_init[:7] = cfg.INIT_CONFIG_ROOT
# Choosing RBPRM shooter and path validation methods.
psGuide.selectConfigurationShooter("RbprmShooter")
psGuide.selectPathValidation("RbprmPathValidation",0.05)
# Choosing kinodynamic methods :
psGuide.selectSteeringMethod("RBPRMKinodynamic")
psGuide.selectDistance("Kinodynamic")
psGuide.selectPathPlanner("DynamicPlanner")
# Solve the planning problem :
# move the robot out of the view before computing the contacts
from hpp.corbaserver import Client
#~ #DEMO code to play root path and final contact plan
cl = Client()
cl.problem.selectProblem("rbprm_path")
rbprmBuilder2 = Robot ("toto")
ps2 = ProblemSolver( rbprmBuilder2 )
cl.problem.selectProblem("default")
#~ cl.problem.movePathToProblem(pId,"rbprm_path",rbprmBuilder.getAllJointNames()[1:])
r2 = Viewer (ps2, viewerClient=v.client)
q_far = q_init[::]
class AbstractPathPlanner:
rbprmBuilder = None
ps = None
v = None
afftool = None
pp = None
extra_dof_bounds = None
robot_node_name = None # name of the robot in the node list of the viewer
def __init__(self):
self.v_max = -1 # bounds on the linear velocity for the root, negative values mean unused
self.a_max = -1 # bounds on the linear acceleration for the root, negative values mean unused
self.root_translation_bounds = [
0
] * 6 # bounds on the root translation position (-x, +x, -y, +y, -z, +z)
self.root_rotation_bounds = [
-3.14, 3.14, -0.01, 0.01, -0.01, 0.01
] # bounds on the rotation of the root (-z, z, -y, y, -x, x)
# The rotation bounds are only used during the random sampling, they are not enforced along the path
self.extra_dof = 6 # number of extra config appended after the joints configuration, 6 to store linear root velocity and acceleration
self.mu = 0.5 # friction coefficient between the robot and the environment
self.used_limbs = [
] # names of the limbs that must be in contact during all the motion
self.size_foot_x = 0 # size of the feet along the x axis
self.size_foot_y = 0 # size of the feet along the y axis
self.q_init = []
self.q_goal = []
@abstractmethod
def load_rbprm(self):
"""
Build an rbprmBuilder instance for the correct robot and initialize it's extra config size
"""
pass
def set_configurations(self):
self.rbprmBuilder.client.robot.setDimensionExtraConfigSpace(
self.extra_dof)
self.q_init = self.rbprmBuilder.getCurrentConfig()
self.q_goal = self.rbprmBuilder.getCurrentConfig()
self.q_init[2] = self.rbprmBuilder.ref_height
self.q_goal[2] = self.rbprmBuilder.ref_height
def compute_extra_config_bounds(self):
"""
Compute extra dof bounds from the current values of v_max and a_max
By default, set symmetrical bounds on x and y axis and bounds z axis values to 0
"""
# bounds for the extradof : by default use v_max/a_max on x and y axis and 0 on z axis
self.extra_dof_bounds = [
-self.v_max, self.v_max, -self.v_max, self.v_max, 0, 0,
-self.a_max, self.a_max, -self.a_max, self.a_max, 0, 0
]
def set_joints_bounds(self):
"""
Set the root translation and rotation bounds as well as the the extra dofs bounds
"""
self.rbprmBuilder.setJointBounds("root_joint",
self.root_translation_bounds)
self.rbprmBuilder.boundSO3(self.root_rotation_bounds)
self.rbprmBuilder.client.robot.setExtraConfigSpaceBounds(
self.extra_dof_bounds)
def set_rom_filters(self):
"""
Define which ROM must be in collision at all time and with which kind of affordances
By default it set all the roms in used_limbs to be in contact with 'support' affordances
"""
self.rbprmBuilder.setFilter(self.used_limbs)
for limb in self.used_limbs:
self.rbprmBuilder.setAffordanceFilter(limb, ['Support'])
def init_problem(self):
"""
Load the robot, set the bounds and the ROM filters and then
Create a ProblemSolver instance and set the default parameters.
The values of v_max, a_max, mu, size_foot_x and size_foot_y must be defined before calling this method
"""
self.load_rbprm()
self.set_configurations()
self.compute_extra_config_bounds()
self.set_joints_bounds()
self.set_rom_filters()
self.ps = ProblemSolver(self.rbprmBuilder)
# define parameters used by various methods :
if self.v_max >= 0:
self.ps.setParameter("Kinodynamic/velocityBound", self.v_max)
if self.a_max >= 0:
self.ps.setParameter("Kinodynamic/accelerationBound", self.a_max)
if self.size_foot_x > 0:
self.ps.setParameter("DynamicPlanner/sizeFootX", self.size_foot_x)
if self.size_foot_y > 0:
self.ps.setParameter("DynamicPlanner/sizeFootY", self.size_foot_y)
self.ps.setParameter("DynamicPlanner/friction", 0.5)
# sample only configuration with null velocity and acceleration :
self.ps.setParameter("ConfigurationShooter/sampleExtraDOF", False)
def init_viewer(self,
env_name,
env_package="hpp_environments",
reduce_sizes=[0, 0, 0],
visualize_affordances=[]):
"""
Build an instance of hpp-gepetto-viewer from the current problemSolver
:param env_name: name of the urdf describing the environment
:param env_package: name of the package containing this urdf (default to hpp_environments)
:param reduce_sizes: Distance used to reduce the affordances plan toward the center of the plane
(in order to avoid putting contacts closes to the edges of the surface)
:param visualize_affordances: list of affordances type to visualize, default to none
"""
vf = ViewerFactory(self.ps)
self.afftool = AffordanceTool()
self.afftool.setAffordanceConfig('Support', [0.5, 0.03, 0.00005])
self.afftool.loadObstacleModel("package://" + env_package + "/urdf/" +
env_name + ".urdf",
"planning",
vf,
reduceSizes=reduce_sizes)
self.v = vf.createViewer(ghost=True, displayArrows=True)
self.pp = PathPlayer(self.v)
for aff_type in visualize_affordances:
self.afftool.visualiseAffordances(aff_type, self.v,
self.v.color.lightBrown)
def init_planner(self, kinodynamic=True, optimize=True):
"""
Select the rbprm methods, and the kinodynamic ones if required
:param kinodynamic: if True, also select the kinodynamic methods
:param optimize: if True, add randomShortcut path optimizer (or randomShortcutDynamic if kinodynamic is also True)
"""
self.ps.selectConfigurationShooter("RbprmShooter")
self.ps.selectPathValidation("RbprmPathValidation", 0.05)
if kinodynamic:
self.ps.selectSteeringMethod("RBPRMKinodynamic")
self.ps.selectDistance("Kinodynamic")
self.ps.selectPathPlanner("DynamicPlanner")
if optimize:
if kinodynamic:
self.ps.addPathOptimizer("RandomShortcutDynamic")
else:
self.ps.addPathOptimizer("RandomShortcut")
def solve(self):
"""
Solve the path planning problem.
q_init and q_goal must have been defined before calling this method
"""
if len(self.q_init) != self.rbprmBuilder.getConfigSize():
raise ValueError(
"Initial configuration vector do not have the right size")
if len(self.q_goal) != self.rbprmBuilder.getConfigSize():
raise ValueError(
"Goal configuration vector do not have the right size")
self.ps.setInitialConfig(self.q_init)
self.ps.addGoalConfig(self.q_goal)
self.v(self.q_init)
t = self.ps.solve()
print("Guide planning time : ", t)
def display_path(self, path_id=-1, dt=0.1):
"""
Display the path in the viewer, if no path specified display the last one
:param path_id: the Id of the path specified, default to the most recent one
:param dt: discretization step used to display the path (default to 0.1)
"""
if self.pp is not None:
if path_id < 0:
path_id = self.ps.numberPaths() - 1
self.pp.dt = dt
self.pp.displayVelocityPath(path_id)
def play_path(self, path_id=-1, dt=0.01):
"""
play the path in the viewer, if no path specified display the last one
:param path_id: the Id of the path specified, default to the most recent one
:param dt: discretization step used to display the path (default to 0.01)
"""
self.show_rom()
if self.pp is not None:
if path_id < 0:
path_id = self.ps.numberPaths() - 1
self.pp.dt = dt
self.pp(path_id)
def hide_rom(self):
"""
Remove the current robot from the display
"""
self.v.client.gui.setVisibility(self.robot_node_name, "OFF")
def show_rom(self):
"""
Add the current robot to the display
"""
self.v.client.gui.setVisibility(self.robot_node_name, "ON")
@abstractmethod
def run(self):
"""
Must be defined in the child class to run all the methods with the correct arguments.
"""
# example of definition:
"""
self.init_problem()
# define initial and goal position
self.q_init[:2] = [0, 0]
self.q_goal[:2] = [1, 0]
self.init_viewer("multicontact/ground", visualize_affordances=["Support"])
self.init_planner()
self.solve()
self.display_path()
self.play_path()
"""
pass
#q_goal[0:3] = [6.5,-1,0.4] # straight line
q_goal [0:3] = [3,-4,0.4] # easy goal position
#q_goal[0:3]=[-4.5,-4.8,0.4]# harder goal position
#set goal velocity (along x,y,z axis) :
q_goal[-6:-3]=[0,0,0]
vf.loadObstacleModel ("iai_maps", "room", "room")
# with displayArrow parameter the viewer will display velocity and acceleration of the center of the robot with 3D arrow. The length scale with the amplitude with a length of 1 for the maximal amplitude
v = vf.createViewer(displayArrows = True)
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.addPathOptimizer ("RandomShortcut")
#select kinodynamic methods :
ps.selectSteeringMethod("Kinodynamic")
ps.selectDistance("Kinodynamic")
# the Kinodynamic steering method require a planner that build directionnal roadmap (with oriented edges) as the trajectories cannot always be reversed.
ps.selectPathPlanner("BiRRTPlanner")
print (ps.solve ())
# display the computed roadmap. Note that the edges are all represented as straight line and may not show the real motion of the robot between the nodes :
v.displayRoadmap("rm")
#Alternatively, use the following line instead of ps.solve() to display the roadmap as it's computed (note that it slow down a lot the computation)
#v.solveAndDisplay('rm',1)
# Highlight the solution path used in the roadmap
v.displayPathMap('pm',0)
