openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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# Copyright (c) The acados authors.
#
# This file is part of acados.
#
# The 2-Clause BSD License
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.;
from dataclasses import dataclass, field
import numpy as np
@dataclass
class ZoroDescription:
"""
Zero-Order Robust Optimization scheme.
For advanced users.
"""
backoff_scaling_gamma: float = 1.0
fdbk_K_mat: np.ndarray = None
unc_jac_G_mat: np.ndarray = None # default: an identity matrix
P0_mat: np.ndarray = None
W_mat: np.ndarray = None
idx_lbx_t: list = field(default_factory=list)
idx_ubx_t: list = field(default_factory=list)
idx_lbx_e_t: list = field(default_factory=list)
idx_ubx_e_t: list = field(default_factory=list)
idx_lbu_t: list = field(default_factory=list)
idx_ubu_t: list = field(default_factory=list)
idx_lg_t: list = field(default_factory=list)
idx_ug_t: list = field(default_factory=list)
idx_lg_e_t: list = field(default_factory=list)
idx_ug_e_t: list = field(default_factory=list)
idx_lh_t: list = field(default_factory=list)
idx_uh_t: list = field(default_factory=list)
idx_lh_e_t: list = field(default_factory=list)
idx_uh_e_t: list = field(default_factory=list)
def process_zoro_description(zoro_description: ZoroDescription):
zoro_description.nw, _ = zoro_description.W_mat.shape
if zoro_description.unc_jac_G_mat is None:
zoro_description.unc_jac_G_mat = np.eye(zoro_description.nw)
zoro_description.nlbx_t = len(zoro_description.idx_lbx_t)
zoro_description.nubx_t = len(zoro_description.idx_ubx_t)
zoro_description.nlbx_e_t = len(zoro_description.idx_lbx_e_t)
zoro_description.nubx_e_t = len(zoro_description.idx_ubx_e_t)
zoro_description.nlbu_t = len(zoro_description.idx_lbu_t)
zoro_description.nubu_t = len(zoro_description.idx_ubu_t)
zoro_description.nlg_t = len(zoro_description.idx_lg_t)
zoro_description.nug_t = len(zoro_description.idx_ug_t)
zoro_description.nlg_e_t = len(zoro_description.idx_lg_e_t)
zoro_description.nug_e_t = len(zoro_description.idx_ug_e_t)
zoro_description.nlh_t = len(zoro_description.idx_lh_t)
zoro_description.nuh_t = len(zoro_description.idx_uh_t)
zoro_description.nlh_e_t = len(zoro_description.idx_lh_e_t)
zoro_description.nuh_e_t = len(zoro_description.idx_uh_e_t)
return zoro_description.__dict__