gtsam.examples.simulation Namespace Reference

Functions
def	generate_simulation_data (num_landmarks, world_size, robot_radius, robot_angular_vel, num_steps, dt, odometry_noise_model, measurement_noise_model, max_sensor_range, X, L, odom_seed=42, meas_seed=42, landmark_seed=42)

Function Documentation

generate_simulation_data()

def gtsam.examples.simulation.generate_simulation_data	(		num_landmarks,
			world_size,
			robot_radius,
			robot_angular_vel,
			num_steps,
			dt,
			odometry_noise_model,
			measurement_noise_model,
			max_sensor_range,
			X,
			L,
			odom_seed = 42,
			meas_seed = 42,
			landmark_seed = 42
	)

Generates ground truth and simulated measurements for SLAM.

Args:
    num_landmarks: Number of landmarks to generate.
    world_size: Size of the square world environment.
    robot_radius: Radius of the robot's circular path.
    robot_angular_vel: Angular velocity of the robot (rad/step).
    num_steps: Number of simulation steps.
    dt: Time step duration.
    odometry_noise_model: GTSAM noise model for odometry.
    measurement_noise_model: GTSAM noise model for bearing-range.
    max_sensor_range: Maximum range of the bearing-range sensor.
    X: GTSAM symbol shorthand function for poses.
    L: GTSAM symbol shorthand function for landmarks.
    odom_seed: Random seed for odometry noise.
    meas_seed: Random seed for measurement noise.
    landmark_seed: Random seed for landmark placement.

Returns:
    tuple: Contains:
        - landmarks_gt_dict (dict): L(i) -> gtsam.Point2 ground truth.
        - poses_gt (list): List of gtsam.Pose2 ground truth poses.
        - odometry_measurements (list): List of noisy gtsam.Pose2 odometry.
        - measurements_sim (list): List of lists, measurements_sim[k] contains
                                   tuples (L(lm_id), bearing, range) for step k.
        - landmarks_gt_array (np.array): 2xN numpy array of landmark positions.

Definition at line 7 of file simulation.py.