sample program of lidar sensing simulation is added in document

doc/3_sensor_models/3_3_sensors.md

@@ -183,3 +183,87 @@ These functions are called in the update function and draw function of the vehic
             axes.set_xlim(self.spec.x_lim.min_value(), self.spec.x_lim.max_value())
             axes.set_ylim(self.spec.y_lim.min_value(), self.spec.y_lim.max_value())
 ```
+
+### 3.3.6 LiDAR Sensing Simulation
+The object sesning with 2D LiDAR can be simulated by executing the following sample program. A single 2D LiDAR senses multiple obstacles and the point cloud data is generated.  
+[lidar_obstacle_sensing.py](/src/simulations/perception/lidar_obstacle_sensing/lidar_obstacle_sensing.py)  
+```python
+"""
+lidar_obstacle_sensing.py
+
+Author: Shisato Yano
+"""
+
+# import path setting
+import numpy as np
+import sys
+from pathlib import Path
+
+abs_dir_path = str(Path(__file__).absolute().parent)
+relative_path = "/../../../components/"
+
+sys.path.append(abs_dir_path + relative_path + "visualization")
+sys.path.append(abs_dir_path + relative_path + "state")
+sys.path.append(abs_dir_path + relative_path + "vehicle")
+sys.path.append(abs_dir_path + relative_path + "obstacle")
+sys.path.append(abs_dir_path + relative_path + "sensors")
+sys.path.append(abs_dir_path + relative_path + "sensors/lidar")
+
+
+# import component modules
+from global_xy_visualizer import GlobalXYVisualizer
+from min_max import MinMax
+from time_parameters import TimeParameters
+from vehicle_specification import VehicleSpecification
+from state import State
+from four_wheels_vehicle import FourWheelsVehicle
+from obstacle import Obstacle
+from obstacle_list import ObstacleList
+from sensors import Sensors
+from sensor_parameters import SensorParameters
+from omni_directional_lidar import OmniDirectionalLidar
+
+
+# flag to show plot figure
+# when executed as unit test, this flag is set as false
+show_plot = True
+
+
+def main():
+    """
+    Main process function
+    """
+
+    # set simulation parameters
+    x_lim, y_lim = MinMax(-30, 30), MinMax(-30, 30)
+    vis = GlobalXYVisualizer(x_lim, y_lim, TimeParameters(span_sec=20))
+
+    # create obstacle instances
+    obst_list = ObstacleList()
+    obst1 = Obstacle(State(x_m=-5.0, y_m=15.0, speed_mps=1.0), yaw_rate_rps=np.deg2rad(10), width_m=1.0)
+    obst_list.add_obstacle(obst1)
+    obst2 = Obstacle(State(x_m=-15.0, y_m=-15.0), length_m=10.0, width_m=5.0)
+    obst_list.add_obstacle(obst2)
+    obst3 = Obstacle(State(x_m=20.0), yaw_rate_rps=np.deg2rad(15))
+    obst_list.add_obstacle(obst3)
+    vis.add_object(obst_list)
+
+    # create vehicle instance
+    spec = VehicleSpecification(area_size=30.0) # spec instance
+    lidar = OmniDirectionalLidar(obst_list, SensorParameters(lon_m=spec.wheel_base_m/2)) # lidar instance
+    vehicle = FourWheelsVehicle(State(color=spec.color), spec, sensors=Sensors(lidar=lidar)) # set state, spec, lidar as arguments
+    vis.add_object(vehicle)
+
+    # plot figure is not shown when executed as unit test
+    if not show_plot: vis.not_show_plot()
+
+    # show plot figure
+    vis.draw()
+
+
+# execute main process
+if __name__ == "__main__":
+    main()
+
+```
+![](/src/simulations/perception/lidar_obstacle_sensing/lidar_obstacle_sensing.gif)