
Preview the robotics and Python programming with the Webots simulator, exploring how sun angle influences the simulated environment.
Explore robotics and Python programming with the Webots simulator, learning to program a mobile robot and a robotic arm using Python.
download the windows 2022 version of webots from cyber vortex.com, run the installer for all, then launch to open a blank file in the default project directory.
Visit Python.org, download the latest version for Windows, run the setup, add Python to the path, click install now, and close the wizard after completion.
Create a new project directory, select a folder to save all codes and files, and prepare to start a new world in Webots.
Configure the python path in Webots by opening tools, selecting preferences, and entering python in lowercase under the python option to enable python commands in the vbox editor.
Open the vbox application and create a new world file in Webots. Name the world, keep default options, and add a rectangle arena to include a default floor, then finish.
Explore the Webots simulator interface by rotating, panning, and zooming the view, editing the scene tree, and adjusting floor size, tile size, type, and color for the upcoming object additions.
Explore the Webots library for adding objects and robots, click floor to reveal the plus option, then open the Proton Nodes Robot Project Option and browse robots.
Explore common simulation control options in Webots: open, save, and reload world files, monitor the run timeline, and control execution with reset, step-by-step, normal, and fastest modes.
Expand the proto nodes robots project, choose the pioneer 380 robot, and review its translation and rotation properties as you prepare to add a controller and save the project.
Create a new robot controller in Webots, selecting Python as the language. Name the controller uniquely and customize the default code to control the robot.
Learn how to access a Webots robot's motors and sensors by converting it to base nodes, then control behavior through the Python robot class, setting velocities and using time steps.
Set the velocity for all four motors with the set velocity method, run the Webots simulation, and set position to 6.28 for a full revolution.
Learn to import and control a robotic arm, explore arm kinematics, and add a conveyor belt in the Webots world to build a factory simulation.
Configure factory components in Webots by converting the conveyor to a robot, adjusting scale and translation, and placing cardboard and wooden boxes for end-of-conveyor pickup by the arm.
Add a Python controller to the conveyor in Webots, set belt velocity and target position, and configure the box's mass to move and stop in front of the robot.
Learn forward kinematics to compute endpoint coordinates from joint angles, and inverse kinematics to derive joint angles from a desired endpoint, using libraries to solve inverse kinematics for robotic arms.
install and use the ICP inverse kinematics library to calculate robotic arm joint angles, follow command-line steps to install and verify, and handle common install errors.
Convert the robot to the base node, create a new Python controller, name it clearly, assign it to the arm in the scene tree, and save the world.
Develop an inverse kinematics solution by importing the icp library, creating a kinematic chain from a urdf file, and defining origin and urdf links for the robot.
Create a temporary URDF file of the robot arm, encode it in UTF-8, then build a kinematic chain from the file and apply an active links mask for inverse kinematics.
Implement a time-based ik sequence to grip a box with a Webots robot arm, adjusting gripper orientation and joint angles to grab from the side as the conveyor moves.
Control the robot gripper to grab a box via inverse kinematics in the Webots simulator, tune grip and joint values, then lift and drop the box.
Program and synchronize a mobile robot and robotic arm in Webots to pick up, transfer between conveyors, and drop a box, adjusting joints and gripper timing.
Add conveyors and robots, convert to the base node, adjust translation and scaling on a wooden box, rotate the arm by 1.57 radians about the z axis, and save.
Modify the mobile controller to set position to infinite, achieve forward motion where distance equals speed times time, and execute timed left turns, then stop all motors.
Adjust velocity commands for the robot arm and observe the box’s real-time translations; pause to calculate the inverse kinematic solution from the current box position.
adjust end-point coordinates for a robotic arm after a 90-degree rotation, switch x and y, and refine gripping force to avoid hitting the box in simulation.
Lift the box by increasing the z value in the home position, save, and reset the simulation; then create a second controller for the conveyor and add a time factor.
Run the final simulation to see the result and conclude the project, then extend operation by adding more conveyors and robots for additional practice.
Complete this course by applying Python to program robots in the Webots simulator, and build skills through more projects, experimentation with different robots and components.
This course is designed with the intention of giving you practical and hands-on knowledge to get started with programming the mobile robot and robotic arm in Webots simulator. Webots is a widely used simulator in industries and for research purpose and it has a wide range of robots that you can simulate. In this course, you will learn some very critical concepts of Robotics like how to implement inverse kinematics to the robotic arm. The use of an Inverse Kinematics library that you will learn in this course will not only help you in Webots simulation but also in other software where you are programming real robots.
In this course, you will create a typical factory simulation where the robotic arm will pick an object from the conveyor and place it on the mobile robot. The mobile robot will transfer the object from one place to another in factory environment. And a second Robotic arm will pick the object from the mobile robot and place it on the conveyor. This system will be controlled with multiple controllers programmed in Python.
Robot simulation is highly used in industries where the cost and risk in the project is high. This course will help you in gaining the skill that is required in the industries and also help you in creating the base infrastructure for your future projects.