def main():
args = get_onoff_args('backend ipopt')
sys = QuadRotor()
N = 40
dimx, dimu = sys.nx, sys.nu
cost = QuadCost(N, sys.nx, sys.nu)
t0 = 0.0
tf = 5.0
prob = TrajOptProblem(sys, N, t0, tf, gradmode=True)
prob.xbd = [-1e20 * np.ones(sys.nx), 1e20 * np.ones(sys.nx)]
prob.ubd = [0 * np.ones(sys.nu), 4 * np.ones(sys.nu)]
prob.x0bd = [np.zeros(sys.nx), np.zeros(sys.nx)]
prob.xfbd = [np.zeros(sys.nx), np.zeros(sys.nx)]
prob.xfbd[0][:3] = 5
prob.xfbd[1][:3] = 5
if False:
prob.add_obj(cost)
else:
lqr = LqrObj(R=np.ones(4))
prob.add_lqr_obj(lqr)
prob.pre_process()
# construct a solver for the problem
cfg = OptConfig(args.backend, print_level=5)
slv = OptSolver(prob, cfg)
guessx = np.zeros(prob.nx)
straightx = np.reshape(guessx[:N * dimx], (N, dimx))
for i in range(3):
straightx[:, i] = np.linspace(0, prob.xfbd[0][i], N)
guessx[N * dimx:-1] = np.random.random(N * dimu)
rst = slv.solve_guess(guessx)
print(rst.flag)
if rst.flag == 1:
# parse the solution
sol = prob.parse_sol(rst.sol.copy())
show_sol(sol)
def main():
args = get_onoff_args('oned', 'pen', 'lqr', 'linear', 'orderone',
'backend ipopt')
if args.oned:
testOneD(args)
if args.pen:
testPen(args)
if args.linear:
testLinear(args)
if args.orderone:
testOrderOne(args)
def main():
args = get_onoff_args('cartpole', 'lqr', 'backend ipopt')
if args.cartpole:
gradmode(args)
def main():
args = get_onoff_args('one', 'two', 'oneleg')
if args.one:
testOne()
if args.oneleg:
testOneLeg()
def main():
args = get_onoff_args('grad', 'pen', 'lqr', 'backend ipopt')
if args.grad:
gradmode(args)
if args.pen:
penMode(args)
def main():
args = get_onoff_args('linear', 'ad', 'pen', 'fd')
if args.linear:
test_linear(args.ad)
if args.pen:
test_pendulum(args.ad, args.fd)