Webots Robots Catalog
Use this skill to quickly select pre-built robot and vehicle models from the Webots PROTO library.
Scope
- Focus on cataloging available robot models, PROTO names, and practical starting points.
- Use
references/robots_reference.md for detailed device-name maps and high-frequency robot details.
- Exclude custom robot authoring workflows.
- Exclude low-level sensor and actuator API tutorials.
How to Add a Robot
Add button > PROTO nodes (Webots Projects) > robots > [manufacturer] > [model]
Mobile Robots (Research/Education)
| Robot |
Manufacturer |
PROTO Name |
Type |
Key Devices |
| e-puck |
GCtronic |
E-puck |
Differential |
8 DistanceSensors, Camera, 10 LEDs, Accelerometer |
| e-puck2 |
GCtronic |
E-puck2 |
Differential |
Same + ToF sensor, microphones |
| Thymio II |
Mobsya |
Thymio2 |
Differential |
7 DistanceSensors, ground sensors, accelerometer |
| Khepera IV |
K-Team |
Khepera4 |
Differential |
12 IR sensors, ultrasound, camera, gyro |
| Khepera III |
K-Team |
Khepera3 |
Differential |
11 IR sensors, ultrasound |
| Khepera I |
K-Team |
Khepera1 |
Differential |
8 IR sensors |
| Create (Roomba) |
iRobot |
Create |
Differential |
Bumper, cliff sensors, IR |
| JetBot |
NVIDIA |
JetBot |
Differential |
Camera |
Mobile Robots (Professional/Research)
| Robot |
PROTO Name |
Type |
Key Devices |
| Pioneer 3-DX |
Pioneer3dx |
Differential |
16 sonars, 2 LiDARs |
| Pioneer 3-AT |
Pioneer3at |
Skid-steer |
16 sonars |
| TurtleBot3 Burger |
TurtleBot3Burger |
Differential |
LiDAR, IMU, Camera |
| TurtleBot3 Waffle |
TurtleBot3WafflePI |
Differential |
LiDAR, Camera, IMU |
| Robotino 3 |
Robotino3 |
Omnidirectional |
9 IR, camera, bumper |
| Summit-XL |
SummitXlSteel |
Skid-steer |
GPS, IMU |
| Rosbot |
Rosbot |
Differential |
LiDAR, camera, IMU |
| MiR100 |
MiR100 |
Differential |
2 LiDARs, IMU |
Industrial Arms
| Robot |
PROTO Name |
DOF |
Key Features |
| UR3e |
UR3e |
6 |
Collaborative, 3kg payload |
| UR5e |
UR5e |
6 |
Collaborative, 5kg payload |
| UR10e |
UR10e |
6 |
Collaborative, 10kg payload |
| KUKA YouBot |
YouBot |
5+mobile |
Mobile manipulator |
| Franka Emika Panda |
PandaArm |
7 |
7-DOF collaborative |
| ABB IRB 4600 |
Irb4600-40 |
6 |
Industrial, 40kg payload |
| Niryo Ned |
NiryoNed |
6 |
Educational |
| EPSON T6 |
EpsonT6 |
4 (SCARA) |
High speed |
Humanoids
| Robot |
PROTO Name |
DOF |
Key Features |
| NAO |
Nao |
25 |
Speech, cameras, force sensors |
| Darwin-OP |
DarwinOp2 |
20 |
Open platform, walking |
| Robotis OP2 |
RobotisOp2 |
20 |
Competition robot |
| Robotis OP3 |
RobotisOp3 |
20 |
Upgraded OP2 |
| Atlas |
Atlas |
28 |
Boston Dynamics humanoid |
| iCub |
ICub |
53 |
Research humanoid |
Drones
| Robot |
PROTO Name |
Type |
Key Features |
| DJI Mavic 2 Pro |
Mavic2Pro |
Quadrotor |
Camera, GPS |
| Crazyflie |
Crazyflie |
Quadrotor |
Lightweight, swarm capable |
Vehicles
| Vehicle |
PROTO Name |
Key Features |
| BMW X5 |
BmwX5 |
SUV with sensors |
| Tesla Model 3 |
TeslaModel3 |
Electric car |
| Toyota Prius |
ToyotaPrius |
Hybrid |
| Lincoln MKZ |
LincolnMkz |
Autonomous driving platform |
| Citroen C-Zero |
CitroenCZero |
Electric city car |
Other Notable Robots
- Aibo ERS7 (Sony dog robot)
- Spot (Boston Dynamics quadruped)
- Salamander (amphibious)
- Blimp (lighter-than-air)
- Sojourner (Mars rover)
- PR2 (Willow Garage)
- Shrimp (climbing rover)
Example: Using an E-puck
# The E-puck has these device names:
# Motors: "left wheel motor", "right wheel motor"
# Distance sensors: "ps0" through "ps7"
# LEDs: "led0" through "led9"
# Camera: "camera"
# Accelerometer: "accelerometer"
from controller import Robot
robot = Robot()
timestep = int(robot.getBasicTimeStep())
# Get motors
left = robot.getDevice("left wheel motor")
right = robot.getDevice("right wheel motor")
left.setPosition(float('inf'))
right.setPosition(float('inf'))
# Get distance sensors
sensors = []
for i in range(8):
s = robot.getDevice(f"ps{i}")
s.enable(timestep)
sensors.append(s)
while robot.step(timestep) != -1:
values = [s.getValue() for s in sensors]
# Simple obstacle avoidance
if values[0] > 80 or values[7] > 80:
left.setVelocity(-2.0)
right.setVelocity(2.0)
else:
left.setVelocity(6.28)
right.setVelocity(6.28)
Usage Pattern
- Identify robot class first: mobile, manipulator, humanoid, drone, or vehicle.
- Select PROTO by model requirements (DOF, locomotion, payload, sensor suite).
- Add robot via PROTO tree and confirm device names from
references/robots_reference.md.
- Implement controller logic using exact device identifiers.