我试图用Python创建一个类,但遇到了一些问题。你知道吗
首先我尝试继承一个向量系统来进行轨迹优化,但我得到的错误是没有“AutoDiff”
RuntimeError: The object named [] of type drake::pydrake::(anonymous)::Impl::PyVectorSystem does not support ToAutoDiffXd
代码:
import numpy as np
from pydrake.systems.framework import VectorSystem
from pydrake.all import (DirectCollocation, PiecewisePolynomial, Solve)
# Define the system.
class ex1(VectorSystem):
def __init__(self):
VectorSystem.__init__(self,
1, # 1 input.
2) # 2 outputs.
self.DeclareContinuousState(2) # 2 state variable.
# xdot(t) = -x(t) - y(t); ydot(t) = -y(t) - x(t) + u
def DoCalcVectorTimeDerivatives(self, context, u, x, xdot):
xdot[:] = np.array([-x[0] - x[1], -x[1] - x[0] + u[0]])#.reshape(3,1) #u[0]
# y(t) = x(t)
def DoCalcVectorOutput(self, context, u, x, y):
y[:] = x
def runDircol(self, x0, xf, tf0):
N = 11
umax = 10.
context = self.CreateDefaultContext()
dircol = DirectCollocation(self, context, num_time_samples=N,
minimum_timestep=0.1, maximum_timestep=1.0)
u = dircol.input()
dircol.AddEqualTimeIntervalsConstraints()
dircol.AddConstraintToAllKnotPoints(u[0] <= .5*umax)
dircol.AddConstraintToAllKnotPoints(u[0] >= -.5*umax)
dircol.AddBoundingBoxConstraint(x0, x0, dircol.initial_state())
dircol.AddBoundingBoxConstraint(xf, xf, dircol.final_state())
R = 10.0 # Cost on input "effort".
dircol.AddRunningCost(R*u[0]**2)
# Add a final cost equal to the total duration.
dircol.AddFinalCost(dircol.time())
initial_x_trajectory = \
PiecewisePolynomial.FirstOrderHold([0., tf0], np.column_stack((x0, xf)))
dircol.SetInitialTrajectory(PiecewisePolynomial(), initial_x_trajectory)
result = Solve(dircol)
print(result.get_solver_id().name())
print(result.get_solution_result())
assert(result.is_success())
#import pdb; pdb.set_trace()
xtraj = dircol.ReconstructStateTrajectory(result)
utraj = dircol.ReconstructInputTrajectory(result)
return utraj,xtraj
if __name__ == "__main__":
# Declare model
plant = ex1() # Default instantiation
# Trajectory optimization
x0 = (0.0,0.0) #Initial state that trajectory should start from
xf = (1.0,1.0) #Final desired state
tf0 = 0.5 # Guess for how long trajectory should take
utraj, xtraj = plant.runDircol(x0, xf, tf0)
其次,我尝试从LeafSystem继承,但由于模板问题。我无法使用创建上下文plant.CreateDefaultContext(). 我得到一个错误:
TypeError: unbound method CreateDefaultContext() must be called with ex1_[float] instance as first argument (got nothing instead)
如果我使用plant().CreateDefaultContext(),我会在之后出现奇怪的错误,比如出错context.num输出端口()或无法呼叫plant.to符号() (TypeError:必须使用ex1[float]实例作为第一个参数调用unbound method ToSymbolic()等。。。 代码:
import numpy as np
from pydrake.all import LeafSystem_
from pydrake.systems.scalar_conversion import TemplateSystem
@TemplateSystem.define("ex1_")
def ex1_(T):
class Impl(LeafSystem_[T]):
def _construct(self, converter=None):
LeafSystem_[T].__init__(self, converter)
# one inputs
self.DeclareVectorInputPort("u", BasicVector_[T](1))
# two outputs (full state)
self.DeclareVectorOutputPort("x", BasicVector_[T](2), self.CopyStateOut)
# two positions, no velocities
self.DeclareContinuousState(2, 0, 0)
def _construct_copy(self, other, converter=None):
Impl._construct(self, converter=converter)
def CopyStateOut(self, context, output):
x = context.get_continuous_state_vector().CopyToVector()
output.SetFromVector(x) # = y
def DoCalcTimeDerivatives(self, context, derivatives):
x = context.get_continuous_state_vector().CopyToVector()
u = self.EvalVectorInput(context, 0).CopyToVector()
xdot[:] = np.array([-x[0] - x[1], -x[1] - x[0] + u[0]]) #.reshape(3,1) #u[0]
derivatives.get_mutable_vector().SetFromVector(xdot)
return Impl
if __name__ == "__main__":
# Declare model
plant = ex1_[None] # Default instantiation
#context = plant.CreateDefaultContext(DubinsPlant_[None]())
context = plant().CreateDefaultContext()
import pdb; pdb.set_trace()
sym_system = plant.ToSymbolic()
如果您能帮我解决其中一个问题,我将不胜感激。你知道吗
(在Ubuntu 16.04上运行)
为了回答您的第一个问题,很遗憾我没有更新
VectorSystem
以支持子类类型转换: https://github.com/RobotLocomotion/drake/issues/10745我过几分钟再试试。你知道吗
编辑:啊,可能更复杂。请参阅本期更新。你知道吗
回答第二个问题,
plant
不是ex1_[None]
的实例。所以plant.ToSymbolic()
将不起作用。可行的解决方案是:相关问题 更多 >
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