Merge branch 'master' of https://github.com/acados/acados

acados/ocp_nlp/Makefile

@@ -46,6 +46,7 @@ OBJS += ocp_nlp_dynamics_common.o
 OBJS += ocp_nlp_dynamics_cont.o
 OBJS += ocp_nlp_dynamics_disc.o
 OBJS += ocp_nlp_sqp.o
+OBJS += ocp_nlp_ddp.o
 OBJS += ocp_nlp_sqp_rti.o
 OBJS += ocp_nlp_reg_common.o
 OBJS += ocp_nlp_reg_convexify.o

docs/installation/index.md

@@ -14,10 +14,11 @@ git submodule update --recursive --init
 ```
 
 ### Build and install `acados`
-Both a CMake and a Makefile based build system is supported at the moment.
+A CMake and a Makefile based build system is available in acados.
+Note that only the `CMake` build system is tested using CI and is thus recommended.
 Please choose one and proceed with the corresponding paragraph.
 
-#### **CMake**
+#### **CMake** (recommended)
 Install `acados` as follows:
 ```
 mkdir -p build

examples/acados_python/getting_started/minimal_example_ocp.py

@@ -31,6 +31,7 @@
 from acados_template import AcadosOcp, AcadosOcpSolver
 from pendulum_model import export_pendulum_ode_model
 import numpy as np
+import casadi as ca
 from utils import plot_pendulum
 
 def main():
@@ -52,16 +53,21 @@ def main():
     # set prediction horizon
     ocp.solver_options.tf = Tf
 
-    # set cost
+    # cost matrices
     Q_mat = 2*np.diag([1e3, 1e3, 1e-2, 1e-2])
     R_mat = 2*np.diag([1e-2])
 
-    # the 'EXTERNAL' cost type can be used to define general cost terms
-    # NOTE: This leads to additional (exact) hessian contributions when using GAUSS_NEWTON hessian.
-    ocp.cost.cost_type = 'EXTERNAL'
-    ocp.cost.cost_type_e = 'EXTERNAL'
-    ocp.model.cost_expr_ext_cost = model.x.T @ Q_mat @ model.x + model.u.T @ R_mat @ model.u
-    ocp.model.cost_expr_ext_cost_e = model.x.T @ Q_mat @ model.x
+    # path cost
+    ocp.cost.cost_type = 'NONLINEAR_LS'
+    ocp.model.cost_y_expr = ca.vertcat(model.x, model.u)
+    ocp.cost.yref = np.zeros((nx+nu,))
+    ocp.cost.W = ca.diagcat(Q_mat, R_mat).full()
+
+    # terminal cost
+    ocp.cost.cost_type_e = 'NONLINEAR_LS'
+    ocp.cost.yref_e = np.zeros((nx,))
+    ocp.model.cost_y_expr_e = model.x
+    ocp.cost.W_e = Q_mat
 
     # set constraints
     Fmax = 80

examples/acados_python/zoRO_example/diff_drive/diff_drive_utils.py

@@ -136,7 +136,7 @@ def ellipsoid_surface_2D(P, n=100):
     return a
 
 
-def plot_trajectory(cfg: MPCParam, traj_ref:np.ndarray, traj_zo:np.ndarray, P_matrices=None):
+def plot_trajectory(cfg: MPCParam, traj_ref:np.ndarray, traj_zo:np.ndarray, P_matrices=None, closed_loop=True):
 
     fig = plt.figure(1)
     ax = fig.add_subplot(1,1,1)
@@ -160,12 +160,14 @@ def plot_trajectory(cfg: MPCParam, traj_ref:np.ndarray, traj_zo:np.ndarray, P_ma
 
     ax.set_xlabel("x [m]")
     ax.set_ylabel("y [m]")
-    ax.set_xticks(np.arange(-2., 9., 2.))
-    ax.set_yticks(np.arange(0., 5., 2.))
-    ax.set_ylim([-.5, 3.6])
+    if closed_loop:
+        ax.set_xticks(np.arange(-2., 9., 2.))
+        ax.set_yticks(np.arange(0., 5., 2.))
+        ax.set_ylim([-.5, 3.6])
     ax.set_aspect("equal")
     ax.legend()
     plt.tight_layout()
+    plt.grid()
     if not os.path.exists("figures"):
         os.makedirs("figures")
 

examples/acados_python/zoRO_example/diff_drive/main.py

@@ -186,7 +186,7 @@ def solve_single_zoro_problem_visualize_uncertainty():
     print(f"x_opt = {x_opt}")
     print(f"status = {status}")
     plot_trajectory(cfg_zo, x_ref_interp, x_opt,
-                    P_matrices=zoroMPC.ocp.zoro_description.backoff_scaling_gamma**2 * zoroMPC.P_mats)
+                    P_matrices=zoroMPC.ocp.zoro_description.backoff_scaling_gamma**2 * zoroMPC.P_mats, closed_loop=False)
 
 
 def plot_result_trajectory(n_executions: int, use_custom_update=True):

interfaces/acados_template/acados_template/acados_ocp.py

@@ -201,7 +201,7 @@ def make_consistent(self) -> None:
             if opts.hessian_approx == 'GAUSS_NEWTON' and opts.ext_cost_num_hess == 0 and model.cost_expr_ext_cost_custom_hess_0 is None:
                 print("\nWARNING: Gauss-Newton Hessian approximation with EXTERNAL cost type not possible!\n"
                 "got cost_type_0: EXTERNAL, hessian_approx: 'GAUSS_NEWTON.'\n"
-                "GAUSS_NEWTON hessian is only supported for cost_types [NON]LINEAR_LS.\n"
+                "GAUSS_NEWTON hessian is not defined for EXTERNAL cost formulation.\n"
                 "If you continue, acados will proceed computing the exact hessian for the cost term.\n"
                 "Note: There is also the option to use the external cost module with a numerical hessian approximation (see `ext_cost_num_hess`).\n"
                 "OR the option to provide a symbolic custom hessian approximation (see `cost_expr_ext_cost_custom_hess`).\n")

interfaces/acados_template/acados_template/utils.py

@@ -57,6 +57,7 @@
     '3.6.2',
     '3.6.3',
     '3.6.4',
+    '3.6.5',
 )
 
 TERA_VERSION = "0.0.34"