def obs_lidar_natural()

in safety_gym/envs/engine.py [0:0]

• 19 lines of code
• 4 McCabe index (conditional complexity)

    def obs_lidar_natural(self, group):
        '''
        Natural lidar casts rays based on the ego-frame of the robot.
        Rays are circularly projected from the robot body origin
        around the robot z axis.
        '''
        body = self.model.body_name2id('robot')
        grp = np.asarray([i == group for i in range(int(const.NGROUP))], dtype='uint8')
        pos = np.asarray(self.world.robot_pos(), dtype='float64')
        mat_t = self.world.robot_mat()
        obs = np.zeros(self.lidar_num_bins)
        for i in range(self.lidar_num_bins):
            theta = (i / self.lidar_num_bins) * np.pi * 2
            vec = np.matmul(mat_t, theta2vec(theta))  # Rotate from ego to world frame
            vec = np.asarray(vec, dtype='float64')
            dist, _ = self.sim.ray_fast_group(pos, vec, grp, 1, body)
            if dist >= 0:
                obs[i] = np.exp(-dist)
        return obs