import numpy as np from scipy.interpolate import interp1d def compute_path_from_wp(start_xp, start_yp, step = 0.1): """ """ final_xp=[] final_yp=[] delta = step #[m] for idx in range(len(start_xp)-1): section_len = np.sqrt(np.sum(np.power(np.diff(start_xp[idx:idx+2]),2)+np.power(np.diff(start_yp[idx:idx+2]),2))) interp_range = np.linspace(0,1, int(1+section_len/delta)) fx=interp1d(np.linspace(0,1,2),start_xp[idx:idx+2],kind=1) fy=interp1d(np.linspace(0,1,2),start_yp[idx:idx+2],kind=1) final_xp=np.append(final_xp,fx(interp_range)) final_yp=np.append(final_yp,fy(interp_range)) return np.vstack((final_xp,final_yp)) def get_nn_idx(state,path): """ """ dx = state[0]-path[0,:] dy = state[1]-path[1,:] dist = np.sqrt(dx**2 + dy**2) nn_idx = np.argmin(dist) try: v = [path[0,nn_idx+1] - path[0,nn_idx], path[1,nn_idx+1] - path[1,nn_idx]] v /= np.linalg.norm(v) d = [path[0,nn_idx] - state[0], path[1,nn_idx] - state[1]] if np.dot(d,v) > 0: target_idx = nn_idx else: target_idx = nn_idx+1 except IndexError as e: target_idx = nn_idx return target_idx def road_curve(state,track): """ """ POLY_RANK = 3 #given vehicle pos find lookahead waypoints nn_idx=get_nn_idx(state,track) LOOKAHED = POLY_RANK*2 lk_wp=track[:,max(0,nn_idx-1):nn_idx+LOOKAHED] #trasform lookahead waypoints to vehicle ref frame dx = lk_wp[0,:] - state[0] dy = lk_wp[1,:] - state[1] wp_vehicle_frame = np.vstack(( dx * np.cos(-state[3]) - dy * np.sin(-state[3]), dy * np.cos(-state[3]) + dx * np.sin(-state[3]) )) #fit poly return np.polyfit(wp_vehicle_frame[0,:], wp_vehicle_frame[1,:], POLY_RANK, rcond=None, full=False, w=None, cov=False) # def f(x,coeff): # """ # """ # return round(coeff[0]*x**3 + coeff[1]*x**2 + coeff[2]*x**1 + coeff[3]*x**0,6) # def f(x,coeff): # return round(coeff[0]*x**5+coeff[1]*x**4+coeff[2]*x**3+coeff[3]*x**2+coeff[4]*x**1+coeff[5]*x**0,6) def f(x,coeff): y=0 j=len(coeff) for k in range(j): y += coeff[k]*x**(j-k-1) return round(y,6) # def df(x,coeff): # """ # """ # return round(3*coeff[0]*x**2 + 2*coeff[1]*x**1 + coeff[2]*x**0,6) # def df(x,coeff): # return round(5*coeff[0]*x**4 + 4*coeff[1]*x**3 +3*coeff[2]*x**2 + 2*coeff[3]*x**1 + coeff[4]*x**0,6) def df(x,coeff): y=0 j=len(coeff) for k in range(j-1): y += (j-k-1)*coeff[k]*x**(j-k-2) return round(y,6)