Adding New Examples Guide¶

This guide explains how to add new robot examples to the Webots-Simulink Bridge project.

Potential New Examples¶

Based on Webots' available robot models and common simulation use cases, here are recommended examples to add:

Autonomous Vehicles¶

BMW X5 / Tesla Model 3¶

Type: Passenger car with Ackermann steering
Sensors: Camera, LiDAR, radar, GPS, IMU
Use Cases: ADAS development, lane keeping, ACC, autonomous parking
Webots Model: BmwX5, TeslaModel3

bmw_x5/
├── controllers/
│   └── simulink_control_app/
│       ├── simulink_control_app.m
│       ├── simulink_control.slx
│       ├── wb_camera_get_image.m
│       ├── wb_lidar_get_range_image.m
│       ├── wb_radar_get_targets.m
│       └── ...
└── worlds/
    └── highway.wbt

Citroen C-Zero / Smart ForTwo¶

Type: Compact electric vehicle
Use Cases: Urban autonomous driving, parking algorithms

Industrial Robots¶

Universal Robots (UR5e/UR10e)¶

Type: 6-DOF collaborative robot arm
Sensors: Joint encoders, force/torque sensor
Use Cases: Pick-and-place, trajectory planning, inverse kinematics
Webots Model: UR5e, UR10e

ur5e_arm/
├── controllers/
│   └── simulink_control_app/
│       ├── simulink_control_app.m
│       ├── simulink_control.slx
│       ├── wb_motor_set_position.m
│       ├── wb_position_sensor_get_value.m
│       └── ...
└── worlds/
    └── ur5e_workspace.wbt

KUKA iiwa / ABB IRB¶

Type: Industrial robot arm
Use Cases: Manufacturing simulation, welding, assembly

Humanoid Robots¶

NAO Robot¶

Type: Bipedal humanoid (58cm)
Sensors: Cameras, IMU, touch sensors, microphones
Use Cases: Gait control, balance, gesture recognition
Webots Model: Nao

nao_humanoid/
├── controllers/
│   └── simulink_control_app/
│       ├── simulink_control_app.m
│       ├── simulink_control.slx
│       ├── wb_motor_set_position.m   # Joint control
│       ├── wb_camera_get_image.m
│       ├── wb_accelerometer_get_values.m
│       └── ...
└── worlds/
    └── nao_walking.wbt

Boston Dynamics Spot¶

Type: Quadruped robot
Sensors: Depth cameras, IMU, joint encoders
Use Cases: Legged locomotion, terrain navigation

Underwater Vehicles¶

BlueROV2¶

Type: Remotely operated underwater vehicle
Sensors: Depth sensor, IMU, cameras, sonar
Use Cases: Underwater inspection, marine research

bluerov2/
├── controllers/
│   └── simulink_control_app/
│       ├── simulink_control_app.m
│       ├── simulink_control.slx
│       ├── wb_motor_set_velocity.m   # Thruster control
│       ├── wb_distance_sensor_get_value.m  # Depth
│       └── ...
└── worlds/
    └── underwater.wbt

Agricultural Robots¶

Autonomous Harvester¶

Type: Agricultural vehicle with implement
Sensors: GPS, LiDAR, cameras
Use Cases: Precision agriculture, autonomous harvesting

Drone Sprayer¶

Type: Agricultural multirotor
Use Cases: Crop spraying, field mapping

Swarm Robotics¶

E-puck Swarm¶

Type: Multiple small mobile robots
Sensors: Proximity sensors, cameras, IR communication
Use Cases: Swarm algorithms, collective behavior

epuck_swarm/
├── controllers/
│   └── simulink_control_app/
│       ├── simulink_control_app.m
│       ├── simulink_control.slx
│       └── ...
└── worlds/
    └── swarm_arena.wbt  # Multiple e-puck robots

Example Structure Template¶

Every example should follow this structure:

example_name/
├── README.md                        # Quick start guide
├── controllers/
│   ├── keyboard_controller/         # Optional manual control
│   │   └── keyboard_controller.py
│   └── simulink_control_app/        # Main Simulink integration
│       ├── simulink_control_app.m   # Initialization script
│       ├── simulink_control.slx     # Main Simulink model
│       ├── state_space_modeling.slx # Optional state-space model
│       └── wb_*.m                   # MATLAB wrapper functions
├── protos/                          # Optional custom PROTO files
│   └── CustomRobot.proto
└── worlds/
    └── world.wbt                    # Webots world file

Step-by-Step: Adding a New Example¶

Step 1: Create Directory Structure¶

mkdir -p examples/new_robot/controllers/simulink_control_app
mkdir -p examples/new_robot/worlds

Step 2: Create Webots World File¶

Create worlds/world.wbt with: - Robot definition with sensors and actuators - Environment (floor, obstacles, etc.) - Set controller to simulink_control_app

Step 3: Create Initialization Script¶

Create simulink_control_app.m:

% MATLAB controller for Webots
% File: simulink_control_app.m
% Description: [Robot Name] Simulink Control Initialization
% Author: [Your Name]
% Date: [Date]

TIME_STEP = 16;

% ===== SENSORS =====
% Initialize each sensor your robot has

% IMU / Inertial Unit
imu = wb_robot_get_device('inertial_unit');
wb_inertial_unit_enable(imu, TIME_STEP);

% GPS
gps = wb_robot_get_device('gps');
wb_gps_enable(gps, TIME_STEP);

% Gyroscope
gyro = wb_robot_get_device('gyro');
wb_gyro_enable(gyro, TIME_STEP);

% LiDAR (if applicable)
lidar = wb_robot_get_device('lidar');
wb_lidar_enable(lidar, TIME_STEP);

% Camera (if applicable)
camera = wb_robot_get_device('camera');
wb_camera_enable(camera, TIME_STEP);

% ===== ACTUATORS =====
% Initialize motors/actuators

motor1 = wb_robot_get_device('motor1');
motor2 = wb_robot_get_device('motor2');
% ... add more as needed

% ===== LOAD SIMULINK MODEL =====
open_system('simulink_control');
load_system('simulink_control');

Step 4: Create MATLAB Wrapper Functions¶

Copy and adapt wrapper functions from existing examples:

Essential functions: - wb_robot_step.m - Simulation step - wb_motor_set_velocity.m - Motor velocity control - wb_motor_set_position.m - Motor position control

Sensor functions (as needed): - wb_gps_get_values.m - wb_gyro_get_values.m - wb_accelerometer_get_values.m - wb_inertial_unit_get_roll_pitch_yaw.m - wb_lidar_get_range_image.m - wb_camera_get_image.m - wb_distance_sensor_get_value.m

Step 5: Create Simulink Model¶

Create simulink_control.slx
Add MATLAB Function blocks for sensor reading
Add control algorithm blocks
Add MATLAB Function blocks for actuator commands
Configure sample time to match TIME_STEP

Step 6: Create Documentation¶

README.md (in example folder):

# [Robot Name]

![Robot Image](./worlds/.world.jpg)

Brief description of the robot.

## Features
- Feature 1
- Feature 2

## Quick Start
1. Open `worlds/world.wbt` in Webots
2. Set controller to `simulink_control_app`
3. Open `simulink_control.slx` in MATLAB
4. Run simulation

## File Structure
...

See [full documentation](../../docs/examples/robot-name.md) for details.

Full documentation (docs/examples/robot-name.md): - System overview - Specifications table - Component tables (sensors, actuators) - Simulink integration details - Control system design - Usage examples - Applications - References

Add to mkdocs.yml:

- Examples:
    - Category:
        - Robot Name: examples/robot-name.md

Step 8: Test the Example¶

Open Webots world
Run MATLAB initialization
Start Simulink model
Verify sensor data flow
Test actuator commands
Document any issues

MATLAB Wrapper Function Template¶

function result = wb_sensor_get_value(tag)
% WB_SENSOR_GET_VALUE Get value from Webots sensor
%   result = wb_sensor_get_value(tag) returns the sensor value
%
%   Parameters:
%       tag - Device tag from wb_robot_get_device
%
%   Returns:
%       result - Sensor value (type depends on sensor)

    % Mark as extrinsic for Simulink code generation
    coder.extrinsic('calllib');

    % Initialize output
    result = 0;  % or zeros(1,3) for vector outputs

    % Call Webots API
    result = calllib('libController', 'wb_sensor_get_value', tag);
end

Best Practices¶

Consistent Naming: Use snake_case for folders, kebab-case for docs
Device Names: Match exactly what's in the Webots world file
TIME_STEP: Use 16ms (62.5 Hz) for most applications
Error Handling: Add try-catch in critical functions
Documentation: Include screenshots and GIFs
Testing: Verify on multiple platforms (Windows, Linux, macOS)