#line_handles = ax.plot(x_endeff,y_endeff,linewidth=0.5)
#line_handles = ax.plot(t,cost_vars[:,1:1+n_dofs],linewidth=0.5)
line_handles = ax.plot(x_endeff, y_endeff, linewidth=0.5)
ax.plot(0.5, 0.5, 'or')
ax.axis('equal')
return line_handles
if __name__ == '__main__':
for n_dofs in [3]:
# Initialize a viapoint task and save it to file
viapoint = 0.5 * np.ones(2) # Always 2D!
task = TaskViapoint(viapoint)
directory = "./demoOptimizationDmpArm2DDataTmp/" + str(n_dofs) + "D/"
task.saveToFile(directory, "viapoint_task.txt")
# Call the executable with the directory to which results should be written
print("Call executable to run optimization with " + str(n_dofs) +
"D viapoint.")
executable = "./demoOptimizationDmpArm2D"
print(executeBinary(executable, str(n_dofs) + " " + directory))
print(" Plotting")
fig = plt.figure(n_dofs, figsize=(12, 4))
plotOptimizationRollouts(directory, fig, plotRollout)
#plotOptimizationRolloutsTask(directory,fig,task)
print("Showing")
lib_path = os.path.abspath('../')
sys.path.append(lib_path)
from executeBinary import executeBinary
lib_path = os.path.abspath('../../python/')
sys.path.append(lib_path)
from dmp_bbo.dmp_bbo_plotting import plotOptimizationRollouts
from dmp_bbo.dmp_bbo_plotting import plotOptimizationRolloutsTask
from dmp_bbo.tasks.TaskViapoint import TaskViapoint
if __name__=='__main__':
# Initialize a viapoint task and save it to file
n_dims = 2
viapoint = np.linspace(1.5,2,n_dims)
viapoint_time = 0.2
viapoint_radius = 0.0
task = TaskViapoint(viapoint,viapoint_time, viapoint_radius)
directory = "/tmp/demoOptimizationDmpParallel/"+str(n_dims)+"D/"
task.saveToFile(directory,"viapoint_task.txt")
# Call the executable with the directory to which results should be written
executable = "../../bin/demoOptimizationDmpParallel"
executeBinary(executable, directory)
fig = plt.figure(1,figsize=(12, 4))
plotOptimizationRolloutsTask(directory,fig,task)
plt.show()
dmp = Dmp(tau, y_init, y_attr, function_apps)
# Make the task
viapoint = 3*np.ones(n_dims)
viapoint_time = 0.3
if n_dims==2:
# Do not pass through viapoint at a specific time, but rather pass
# through it at any time.
viapoint_time = None
viapoint_radius=0.1
goal=y_attr
goal_time=1.1*tau
viapoint_weight=1.0
acceleration_weight=0.0001
goal_weight=0.0
task = TaskViapoint(viapoint,viapoint_time, viapoint_radius, goal,goal_time,viapoint_weight, acceleration_weight,goal_weight)
# Make task solver, based on a Dmp
dt = 0.01
integrate_dmp_beyond_tau_factor = 1.5
task_solver = TaskSolverDmp(dmp,dt,integrate_dmp_beyond_tau_factor);
n_search = dmp.getParameterVectorSelectedSize()
covar_update = 'decay'
mean_init = np.full(n_search,0.0)
covar_init = 1000.0*np.eye(n_search)
distribution = DistributionGaussian(mean_init, covar_init)
eliteness = 10