Apollo和Autoware规划部分使用的算法的demo
Apollo_PiecewiseJerk_algorithm
Apollo piecewise_jerk算法主要包括两方面，路径规划和速度规划，最后组合成轨迹 路径规划: PIECEWISE_JERK_PATH_OPTIMIZER (QP) 速度规划: SPEED_HEURISTIC_OPTIMIZER (DP) PIECEWISE_JERK_NONLINEAR_SPEED_OPTIMIZER (QP)
DP_path_planner 基于动态规划的路径规划,(s,l),主要是静态障碍物的避障
DP_speed_planner 基于动态规划的速度规划,(s,t),粗略的处理动态障碍物的避障
op_local_planner Autoware中使用撒点的方法做局部避障
ST_graph 静态障碍物和动态障碍物生成ST_graph
QP_path_planner.py文件中
def compute_A(self):
Ad = []
for i in range(self.horizon - 1):
f_i = np.array([[1.0, self.ds[i], 0.0],
[0.0, 1.0, self.ds[i]]])
Ad.append(f_i)
# print("Ad \n", Ad)
Ax = sparse.csr_matrix(block_diag(*Ad))
# print("Ax \n", Ax.toarray())
f_2 = np.array([[-1.0, 0.0, 0.0],
[0.0, -1.0, 0.0]])
Ay = sparse.kron(sparse.eye(self.horizon - 1), f_2)
off_set = np.zeros(((self.horizon - 1)*2, 3))
Ax = sparse.hstack([Ax, off_set])
print("Ax \n", Ax)
Ay = sparse.hstack([off_set, Ay])
Aeq = Ax + Ay # 数学的加法
print("Aeq.shape \n", Aeq.toarray())
这里面的Ax Ay 是什么意思啊? 能解释一下吗.非常感谢
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