本文整理汇总了Python中hpp.corbaserver.ProblemSolver.selectSteeringMethod方法的典型用法代码示例。如果您正苦于以下问题：Python ProblemSolver.selectSteeringMethod方法的具体用法？Python ProblemSolver.selectSteeringMethod怎么用？Python ProblemSolver.selectSteeringMethod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.selectSteeringMethod方法的2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: velocity
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import selectSteeringMethod [as 别名]
#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)示例2: Buggy
# 需要导入模块: from hpp.corbaserver import ProblemSolver [as 别名]
# 或者: from hpp.corbaserver.ProblemSolver import selectSteeringMethod [as 别名]
from hpp.gepetto import PathPlayer
robot = Buggy("buggy")
robot.setJointBounds ("root_joint", [-5, 16, -4.5, 4.5,
-1.01, 1.01, -1.01, 1.01])
from hpp.corbaserver import ProblemSolver
ps = ProblemSolver (robot)
from hpp.gepetto import ViewerFactory
gui = ViewerFactory (ps)
gui.loadObstacleModel ('hpp_environments', "scene", "scene")
q_init = robot.getCurrentConfig ()
q_goal = q_init [::]
q_init[0:2] = [-3.7, -4];
gui (q_init)
q_goal [0:2] = [15,2]
gui (q_goal)
ps.setInitialConfig (q_init)
ps.addGoalConfig (q_goal)
ps.selectSteeringMethod ("ReedsShepp")
ps.selectPathPlanner ("DiffusingPlanner")
ps.addPathOptimizer ("RandomShortcut")
t = ps.solve ()
print ("solving time", t)