From 6a5b62c44268879c26d66a81b2cf17c75c1379c3 Mon Sep 17 00:00:00 2001 From: William Chen <billyskc@ucla.edu> Date: Sat, 1 Jun 2019 22:08:50 -0700 Subject: [PATCH] having troubles comparing est states with groudtruth --- CoLo-AT/Algorithm Comparison.pdf | Bin 27907 -> 23864 bytes .../__pycache__/data_analyzer.cpython-36.pyc | Bin 6905 -> 7463 bytes CoLo-AT/data_analysis/data_analyzer.py | 36 +- ...simulated_dataset_manager_w.cpython-36.pyc | Bin 7048 -> 6914 bytes .../simulated_dataset_manager_w.py | 12 +- CoLo-AT/gs_ci_journal_sim.py | 22 +- .../__pycache__/ekf_gs_ci2.cpython-36.pyc | Bin 4318 -> 4318 bytes .../__pycache__/ekf_ls_bda.cpython-36.pyc | Bin 4820 -> 4820 bytes CoLo-AT/localization_algos/ekf_gs_ci2.py | 2 +- CoLo-AT/localization_algos/ekf_ls_bda.py | 1 - .../__pycache__/robot_system.cpython-36.pyc | Bin 4113 -> 4120 bytes CoLo-AT/robots/robot_system.py | 2 +- .../__pycache__/sim_manager.cpython-36.pyc | Bin 5319 -> 5193 bytes .../__pycache__/state_recorder.cpython-36.pyc | Bin 4684 -> 5055 bytes CoLo-AT/simulation_process/sim_manager.py | 15 +- CoLo-AT/simulation_process/state_recorder.py | 37 +- CoLo-AT/tmp_est.txt | 406 ++ CoLo-AT/tmp_est_1.txt | 3618 +++++++++++++++++ CoLo-AT/tmp_est_3.txt | 405 ++ CoLo-AT/tmp_est_5.txt | 198 + CoLo-AT/tmp_gt.txt | 406 ++ CoLo-AT/tmp_gt_1.txt | 3618 +++++++++++++++++ CoLo-AT/tmp_gt_3.txt | 405 ++ CoLo-AT/tmp_gt_5.txt | 198 + 24 files changed, 9332 insertions(+), 49 deletions(-) create mode 100644 CoLo-AT/tmp_est.txt create mode 100644 CoLo-AT/tmp_est_1.txt create mode 100644 CoLo-AT/tmp_est_3.txt create mode 100644 CoLo-AT/tmp_est_5.txt create mode 100644 CoLo-AT/tmp_gt.txt create mode 100644 CoLo-AT/tmp_gt_1.txt create mode 100644 CoLo-AT/tmp_gt_3.txt create mode 100644 CoLo-AT/tmp_gt_5.txt diff --git a/CoLo-AT/Algorithm Comparison.pdf b/CoLo-AT/Algorithm Comparison.pdf index ecf54c22f8094da499d2356a5eb9472b84c1e26d..5f20d4ab14b247153f9467c25c81c7fb173c5b06 100644 GIT binary patch delta 11423 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trace_per_run = [] + state_err_per_run = [] lm_measurement_num = [] relative_measurment_num = [] comm_num = [] - trace_per_run = [] + time_arr = [] + f_est = open("tmp_est_1.txt", "w") + + f_gt = open("tmp_gt_1.txt", "w") while True: loc_err_per_time_iterval = 0 trace_per_time_iterval = 0 + state_err_per_time_interval = 0 num_dataline_per_time_iterval = 0 lm_measurement_count = 0 relative_measurement_count = 0 @@ -125,8 +131,15 @@ class Analyzer(): if selected_labels == None or data_in_time_order[time_index][1] in selected_labels: loc_err_per_time_iterval+= data_in_time_order[time_index][7] trace_per_time_iterval += data_in_time_order[time_index][4] + + state_err_per_time_interval += np.linalg.norm(data_in_time_order[time_index][8] - data_in_time_order[time_index][9])/self.num_robots + num_dataline_per_time_iterval+=1 - + + f_est.write(str(data_in_time_order[time_index][0])+ ' ' + str(data_in_time_order[time_index][1])+''+update_in_time_order[time_index] +'\n') + np.savetxt(f_est, data_in_time_order[time_index][8]) + f_gt.write(str(data_in_time_order[time_index][0])+ ' ' + str(data_in_time_order[time_index][1])+ '\n') + np.savetxt(f_gt, data_in_time_order[time_index][9]) time_index += 1 if finish_flag: @@ -135,10 +148,12 @@ class Analyzer(): if num_dataline_per_time_iterval != 0: loc_err_per_run.append(loc_err_per_time_iterval/num_dataline_per_time_iterval) trace_per_run.append(trace_per_time_iterval/num_dataline_per_time_iterval) + state_err_per_run.append(state_err_per_time_interval/num_dataline_per_time_iterval) else: loc_err_per_run.append(0) trace_per_run.append(0) + state_err_per_run.append(0) lm_measurement_num.append(lm_measurement_count) relative_measurment_num.append(relative_measurement_count) @@ -151,11 +166,14 @@ class Analyzer(): print(data_recorder.name,': ') print('Avg location deviation errors per run: ', sum(loc_err_per_run)/len(loc_err_per_run)) print('Avg trace of state variances per run: ', sum(trace_per_run)/len(trace_per_run)) + print('Avg state estimation errors per run: ', sum(state_err_per_run)/len(state_err_per_run)) if plot_graphs: - self.plot_loc_err_and_trace(loc_err_per_run, trace_per_run, time_arr, operations_distr = [lm_measurement_num, relative_measurment_num, comm_num], recorder_name = recorder_name) + self.plot_loc_err_and_trace(state_err_per_run, trace_per_run, time_arr, operations_distr = [lm_measurement_num, relative_measurment_num, comm_num], recorder_name = recorder_name) - return loc_err_per_run, trace_per_run, time_arr + f_est.close() + f_gt.close() + return loc_err_per_run, state_err_per_run, trace_per_run, time_arr def robot_location_at_unit_time_interval(self, data_recorder, unit_time_interval = 0.2): #recorded_dataline = [time, robot_label, est_x_pos, est_y_pos, trace_state_var, gt_x_pos, gt_y_pos, loc_err] @@ -235,7 +253,7 @@ class Analyzer(): fig1.set_title('Location error') fig1.set_xlabel('Time [s]') fig1.set_ylabel('RMS [m]') - fig1.set_ylim(0, 0.6) + fig1.set_ylim(0, 2) fig1.legend(loc=1) fig1.legend(loc='center left', bbox_to_anchor=(1, 0.5)) #fig1.tick_params(labelsize=18) @@ -243,7 +261,7 @@ class Analyzer(): fig2.set_title('Trace of state covariance') fig2.set_xlabel('Time [s]') fig2.set_ylabel('Sigma_s [m^2]') - fig2.set_ylim(0, 0.6) + fig2.set_ylim(0, 2) fig2.legend(loc=1) fig2.legend(loc='center left', bbox_to_anchor=(1, 0.5)) #fig2.tick_params(labelsize=18) @@ -262,9 +280,9 @@ class Analyzer(): arr_loc_err = [] arr_trace = [] for data_recorder in arr_data_recorder: - loc_err_per_run, trace_per_run, time_stamps = self.calculate_loc_err_and_trace_state_variance_per_run(data_recorder, plot_graphs = False, selected_labels = selected_labels) + loc_err_per_run, state_err_per_run, trace_per_run, time_stamps = self.calculate_loc_err_and_trace_state_variance_per_run(data_recorder, plot_graphs = False, selected_labels = selected_labels) if only_trace == None or data_recorder.name not in only_trace: - arr_loc_err.append([time_stamps, loc_err_per_run, data_recorder.name]) + arr_loc_err.append([time_stamps, state_err_per_run, data_recorder.name]) # Need to change back to loc_err_per_run from state_err_per_run arr_trace.append([time_stamps, trace_per_run, data_recorder.name] ) print('Plotting Comparison Graphs') diff --git a/CoLo-AT/dataset_manager/__pycache__/simulated_dataset_manager_w.cpython-36.pyc b/CoLo-AT/dataset_manager/__pycache__/simulated_dataset_manager_w.cpython-36.pyc index 381de36ccc1f4eb7c7dd8ef1ec3fc445ea46b36d..9e3e4e74adcb8ea3383a2dcef692da93246a0506 100644 GIT binary patch delta 1853 zcmb7E&2Jk;6rb5|uXp{qc5DYqTeV7DNGT+3+UASWKtyN*w4vpY)GVx>#BrQ-yn!^# z%CrtrZv+kE1P4xt3j!+jz#jqJkPJwvRB=J#0tX~6ytfV}Qc(a~`+IMG`)20tyx*JK z!?#YEgSKs6J^bt3;^8k$Q`ICw2y^Zf)E!Fu#UEOYPK!nT=7GnM&mknckV0<&;CZ1N z=k^b|aHnGYPPIXta#DEaB$dRc=8uUY68#9r5FQmDL@(0U#Qo?RJuT+#f>^cU)E7-_ zR?J$x;up)Y--N&h=1J&gpLoyCi9Y)z9fasUx+&hVFNrz3_dsHy?3Ze8-CJ?la%sg~ z3-(Mq5>D%nO=)L=Wu2YgjrGvC#V4_g%^g_XCskUNJldj^a9WjHBv3plP`S*Gpxu`0 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class Sim_Dataset_Manager: def __init__(self, dataset_name): self.name = dataset_name - def circular_path_4_robots(self, duration, op_freqs = [[10, 2, 2], [10, 2, 2], [10, 2, 2], [10, 2, 2]], lm_dict = {6:[0,0]}): + def circular_path_4_robots(self, duration, op_freqs = [[2, 1, 1], [2, 1, 1], [2, 1, 1], [2, 1, 1]], lm_dict = {6:[0,0]}): + self.robot_lables = [1,2,3,4] self.duration = duration self.landmark_map = lm_dict @@ -129,6 +130,7 @@ class Sim_Dataset_Manager: def respond(self, req, current_time, need_specific_time = False): + np.random.seed(0) message = req.get_message() valid_respond = False if need_specific_time: @@ -148,7 +150,7 @@ class Sim_Dataset_Manager: if op_idx == 0: #propagation req_type = 'odometry' - actual_v = np.random.uniform(-0.25, 0.25) # between 0 to 0.5 m/s + actual_v = np.random.uniform(0, 0.5) # between 0 to 0.5 m/s input_v = actual_v + np.random.normal(0, self.noise_v) actual_av = 0.02 delta_t = self.op_time_interval[rbt_idx, op_idx] @@ -211,12 +213,6 @@ class Sim_Dataset_Manager: def dataset_reset(self): - self.start_time = 0 - self.starting_states = {} - self.starting_states[1] = [self.start_time, 0, 5, pi/2] - self.starting_states[2] = [self.start_time, 5, 0, pi] - self.starting_states[3] = [self.start_time, 0, -5, 3*pi/2] - self.starting_states[4] = [self.start_time, 0, 5, 2*pi] self.num_robots = len(self.robot_lables) self.measurement_data = [[] for i in range(self.num_robots)] diff --git a/CoLo-AT/gs_ci_journal_sim.py b/CoLo-AT/gs_ci_journal_sim.py index 9769bc1..f85042e 100644 --- a/CoLo-AT/gs_ci_journal_sim.py +++ b/CoLo-AT/gs_ci_journal_sim.py @@ -27,7 +27,7 @@ from ekf_gs_sci2 import EKF_GS_SCI2 ############################################################################## -duration = 200 +duration = 100 robot_labels = [1,2,3,4] testing_dataset = Sim_Dataset_Manager('testing') start_time, starting_states, dataset_data, time_arr = testing_dataset.circular_path_4_robots(duration) @@ -39,13 +39,13 @@ sim = SimulationManager('sim gs_ci') state_recorder = StatesRecorder('gs_ci', robot_labels) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder, simple_plot = False) +data_in_time_order= state_recorder.get_data_in_time_order() -loc_err_per_run, trace_per_run, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder, plot_graphs = False, selected_labels = [1]) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder, plot_graphs = False, selected_labels = [1]) #analyzer.trajectory_plot(state_recorder) - ############################################################################## testing_dataset.dataset_reset() @@ -55,7 +55,7 @@ robot = RobotSystem('robot', robot_labels, loc_algo, distr_sys = True) sim = SimulationManager('sim gs_ci_bound') state_recorder_bound = StatesRecorder('gs_ci_bound', robot_labels, state_var_only = True) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder_bound, simple_plot = False) -loc_err_per_run, trace_per_run_b, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_bound, plot_graphs = False, selected_labels = [1]) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_bound, plot_graphs = False, selected_labels = [1]) ############################################################################## @@ -66,7 +66,7 @@ robot = RobotSystem('robot', robot_labels, loc_algo, distr_sys = False) sim = SimulationManager('sim cen_ekf') state_recorder_LS_cen = StatesRecorder('LS_cen', robot_labels) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder_LS_cen, simple_plot = False) -loc_err_per_run, trace_per_run, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_cen, plot_graphs = False) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_cen, plot_graphs = False, selected_labels = [1] ) ############################################################################## @@ -77,7 +77,7 @@ robot = RobotSystem('robot', robot_labels, loc_algo, distr_sys = False) sim = SimulationManager('sim ls_bda') state_recorder_LS_BDA = StatesRecorder('LS_BDA', robot_labels) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder_LS_BDA, simple_plot = False) -loc_err_per_run, trace_per_run, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_BDA, plot_graphs = False) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_BDA, plot_graphs = False, selected_labels = [1]) ############################################################################## @@ -89,7 +89,7 @@ robot = RobotSystem('robot', robot_labels, loc_algo, distr_sys = False) sim = SimulationManager('sim ls_ci') state_recorder_LS_CI = StatesRecorder('LS_CI', robot_labels) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder_LS_CI, simple_plot = False) -loc_err_per_run, trace_per_run, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_CI, plot_graphs = False) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_LS_CI, plot_graphs = False, selected_labels = [1]) ############################################################################## @@ -100,6 +100,10 @@ robot = RobotSystem('robot', robot_labels, loc_algo, distr_sys = True) sim = SimulationManager('sim gs_sci') state_recorder_GS_SCI = StatesRecorder('GS_SCI', robot_labels) sim.sim_process_native(robot_labels, testing_dataset, robot, state_recorder_GS_SCI, simple_plot = False) -loc_err_per_run, trace_per_run, t_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_GS_SCI, plot_graphs = False) +loc_err_per_run, state_err_per_run, trace_per_run, time_arr = analyzer.calculate_loc_err_and_trace_state_variance_per_run(state_recorder_GS_SCI, plot_graphs = False, selected_labels = [1]) + +analyzer.algos_comparison([state_recorder, state_recorder_LS_cen, state_recorder_LS_BDA, state_recorder_LS_CI, state_recorder_GS_SCI, state_recorder_bound], only_trace = ['gs_ci_bound'], selected_labels = [1]) + + -analyzer.algos_comparison([state_recorder, state_recorder_LS_cen, state_recorder_LS_BDA, state_recorder_LS_CI, state_recorder_GS_SCI, state_recorder_bound], only_trace = ['gs_ci_bound'], selected_labels = [1]) \ No newline at end of file +#analyzer.algos_comparison([state_recorder], selected_labels = [1]) \ No newline at end of file diff --git a/CoLo-AT/localization_algos/__pycache__/ekf_gs_ci2.cpython-36.pyc b/CoLo-AT/localization_algos/__pycache__/ekf_gs_ci2.cpython-36.pyc index 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zcmcbjdPSAfn3tF9df4X}`;DBx*ccf%v#^V?FxqUE=2m56%%1Eh_={0?vW?IT05Cud A#Q*>R delta 44 zcmcbjdPSAfn3tE!x&1?o!$!_uY>Z5sS=hx`7;QI8bE~p3=1g`J{KY6Y*+ysv03v-1 AWB>pF diff --git a/CoLo-AT/localization_algos/ekf_gs_ci2.py b/CoLo-AT/localization_algos/ekf_gs_ci2.py index 2adbad7..a7af3df 100644 --- a/CoLo-AT/localization_algos/ekf_gs_ci2.py +++ b/CoLo-AT/localization_algos/ekf_gs_ci2.py @@ -26,7 +26,7 @@ class EKF_GS_CI2(ekf_algo_framework): sigma_odo = sensor_covariance var_v = 0.25# variance of the velocity - exp_v = 0 # expected vecolcity for other robots + exp_v = 0.25 # expected vecolcity for other robots i = 2*index num_robots = int(len(s)/2) diff --git a/CoLo-AT/localization_algos/ekf_ls_bda.py b/CoLo-AT/localization_algos/ekf_ls_bda.py index d8dab87..c40c670 100644 --- a/CoLo-AT/localization_algos/ekf_ls_bda.py +++ b/CoLo-AT/localization_algos/ekf_ls_bda.py @@ -52,7 +52,6 @@ class EKF_LS_BDA(ekf_algo_framework): Q = np.zeros((2*num_robots,2*num_robots)) Q[i:i+2, i:i+2] = Q_ii sigma_s = sigma_s + Q #errors in the odometric measurements of the robots are uncorrelated, it's a diagonal matrix - return [s, orinetations, sigma_s] diff --git a/CoLo-AT/robots/__pycache__/robot_system.cpython-36.pyc b/CoLo-AT/robots/__pycache__/robot_system.cpython-36.pyc index e6f893b9bb34363e909e83cc8442b5731bb39e34..8efa11f51354b72a7d338dbf8da285ba516c3b0c 100644 GIT binary patch delta 159 zcmbQJFhhaUn3tC;mhp2;>_*PTY>c-iuVpLYVrO7ra0cRHzRlX~FPW5TBva&Tm_-;Q z8DOjw1#u8hrbfDkJw<U2+h!B4IgGq)x42S^OX7=55=&BxCtu_)U{s&%#M92GG5Hja z7NgbVuRv0FvI4I$qtWCL-dxrqbD$-Y&+>j^RGWN&FP}{v$SsPQe3xH*vJd}J0Qej$ AbN~PV delta 121 zcmbQCFj0Zin3tF9X7Yy^myMi@*%+fHuVpLYVq;)na0cRHp3U0qFPSEbamh2XZZ_kZ z!^p@w`9606quS&Eo_0p{$v1ek7%e6<^J+2bOxEKyW;C3f#GA`=iz~IbB)+&Lu_U#4 Z@)h1sj4G3l^X0Rt0ZlB5o@~Q^2LRMtB8mV2 diff --git a/CoLo-AT/robots/robot_system.py b/CoLo-AT/robots/robot_system.py index 075be13..9a66279 100644 --- a/CoLo-AT/robots/robot_system.py +++ b/CoLo-AT/robots/robot_system.py @@ -155,5 +155,5 @@ class RobotSystem: [est_states, est_orientaions, est_state_variance]= self.robot_sys.get_status() trace_sigma_s = self.robot_sys.get_trace_state_variance(robot_index) - robot_state = {'x_pos':est_states[2*robot_index], 'y_pos': est_states[2*robot_index+1], 'trace of state variance': trace_sigma_s, 'state variance': est_state_variance, 'update_type': update_type } + robot_state = {'est_states':est_states, 'x_pos':est_states[2*robot_index], 'y_pos': est_states[2*robot_index+1], 'trace of state variance': trace_sigma_s, 'state variance': est_state_variance, 'update_type': update_type } return robot_state diff --git a/CoLo-AT/simulation_process/__pycache__/sim_manager.cpython-36.pyc b/CoLo-AT/simulation_process/__pycache__/sim_manager.cpython-36.pyc index 8406071719767482050a4be41f2168eaa7139445..3968e9e3901e4f41cd9e997a0445f3559c8da804 100644 GIT binary patch delta 862 zcmY+DOHb5L6vx|6XXtchfEh>xF|ZOTm=OivJVbC563_@LzEV5%4s>SPDd%=X2!;h4 zHzp=`Y2r>+ZU~7B7jB84z~p`d-MBDrOiVndxG~NB-P8a1-$&2AJ+!_Iq(^c&voQVh 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zpvbg>l2-&pRGNS|#B`=iFIk7425QX1QzrzI0RGp8#;UPq>2mEQyaBB}bPfBewE7=t C8gD-U diff --git a/CoLo-AT/simulation_process/sim_manager.py b/CoLo-AT/simulation_process/sim_manager.py index a575a10..32433e8 100644 --- a/CoLo-AT/simulation_process/sim_manager.py +++ b/CoLo-AT/simulation_process/sim_manager.py @@ -54,13 +54,13 @@ class SimulationManager(): return True def allow_operation(self, rsp): - ''' + if rsp.get_type()=='measurement': rbt_idx = rsp.get_robot_index() rsp_dasa = rsp.get_data() if rsp_dasa['subject_ID'] > 5 and self.robots_cant_observe_lm is not None and self.robot_labels[rbt_idx] in self.robots_cant_observe_lm: return False - ''' + return True @@ -80,12 +80,12 @@ class SimulationManager(): #recording starting states starting_st= dm.get_starting_states() state_recorder.set_starting_state(starting_st) - + # robot_system.set_starting_state(dm.get_starting_states()) robot_system.set_start_moving_times(dm.get_start_moving_times()) robot_system.load_map(dm.get_landmark_map()) - + state_var = [] while self.time < start_time+duration: #print("Current time:", self.time) @@ -96,10 +96,7 @@ class SimulationManager(): if self.time < prev_time: print('Time inconsistant!') break - ''' - if valid == False : - break - ''' + if valid_op and self.allow_operation(rsp): robot_state = robot_system.localization_update(rsp) state_var.append(robot_state['state variance']) @@ -140,7 +137,7 @@ class SimulationManager(): print('******** Simulation Process Finished! ********') print('End time: ', self.time) - + return self.time diff --git a/CoLo-AT/simulation_process/state_recorder.py b/CoLo-AT/simulation_process/state_recorder.py index 97a6696..4a39679 100644 --- a/CoLo-AT/simulation_process/state_recorder.py +++ b/CoLo-AT/simulation_process/state_recorder.py @@ -21,6 +21,7 @@ class StatesRecorder(): self.loc_err_arr = {} self.trace_sigma_s_arr = {} self.updata_type_arr = {} + self.gt_states = np.matrix(np.zeros((2*self.num_robots,1))) for i, label in enumerate(self.dataset_labels): self.recorded_data[label]=[] self.loc_err_arr[label]=[] @@ -28,20 +29,29 @@ class StatesRecorder(): self.updata_type_arr[label]=[] def set_starting_state(self, stating_states): + self.gt_states = np.matrix(np.zeros((2*self.num_robots,1))) + for i, label in enumerate(self.dataset_labels): + x_pos = stating_states[label][1] + y_pos = stating_states[label][2] + self.gt_states[2*i, 0] = x_pos + self.gt_states[2*i+1, 0] = y_pos + for i, label in enumerate(self.dataset_labels): self.start_time = stating_states[label][0] time = 0 x_pos = stating_states[label][1] y_pos = stating_states[label][2] - initial_trace_state_var = 0.0001 + initial_trace_state_var = 0.002 * label loc_err = 0 - recorded_dataline = [time, label, x_pos, y_pos, initial_trace_state_var, x_pos, y_pos, loc_err] + recorded_dataline = [time, label, x_pos, y_pos, initial_trace_state_var, x_pos, y_pos, loc_err, self.gt_states.copy(), self.gt_states.copy()] + self.data_in_time_order.append(recorded_dataline) self.recorded_data[label].append(recorded_dataline) self.loc_err_arr[label].append(0) self.trace_sigma_s_arr[label].append(initial_trace_state_var) self.updata_type_arr[label].append('ini') self.updata_type_in_time_order.append('ini') + def get_name(self): return self.name @@ -55,40 +65,45 @@ class StatesRecorder(): robot_idx = message['robot_index'] time = message['time']-self.start_time gt = message['groundtruth'] - #print(robot_state['x_pos']) est_x_pos = float(robot_state['x_pos']) est_y_pos = float(robot_state['y_pos']) + est_states = robot_state['est_states'] trace_state_var = robot_state['trace of state variance'] updata_type = robot_state['update_type'] gt_x_pos = gt['x_pos'] gt_y_pos = gt['y_pos'] - robot_label = self.dataset_labels[robot_idx] - + + self.gt_states[2*robot_idx, 0] = gt_x_pos + self.gt_states[2*robot_idx+1, 0] = gt_y_pos + robot_label = self.dataset_labels[robot_idx] + if self.state_var_only: loc_err = 0 - recorded_dataline = [time, robot_label, gt_x_pos, gt_y_pos, trace_state_var, gt_x_pos, gt_y_pos, loc_err] + recorded_dataline = [time, robot_label, gt_x_pos, gt_y_pos, trace_state_var, gt_x_pos, gt_y_pos, loc_err, self.gt_states.copy(), self.gt_states.copy()] else: loc_err = sqrt((est_x_pos-gt_x_pos)*(est_x_pos-gt_x_pos)+(est_y_pos-gt_y_pos)*(est_y_pos-gt_y_pos)) - recorded_dataline = [time, robot_label, est_x_pos, est_y_pos, trace_state_var, gt_x_pos, gt_y_pos, loc_err] - + recorded_dataline = [time, robot_label, est_x_pos, est_y_pos, trace_state_var, gt_x_pos, gt_y_pos, loc_err, est_states.copy(), self.gt_states.copy()] + + #print(est_states) + #print(self.gt_states) #warning (optional) ''' if(trace_state_var<0): print('TIME: ', time+self.start_time) print(updata_type) print('neg trace: ', recorded_dataline) - ''' - ''' + if(loc_err >= 1): print(updata_type) print('>1 m loc err: ',recorded_dataline) print(req.get_message()) ''' - #print(recorded_dataline) + #print(self.gt_states) 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