Robotic arms can enhance robotics education by demonstrating complex concepts, but when you need to use them outside of the laboratory, things get tricky. With COVID forcing everyone to stay inside, researchers from the Tecnologico de Monterry in Mexico were inspired to make an affordable robotic arm hat could be used with remote learning. The robotic arm is fully open sourced and can be simply assembled by teachers outside of the classroom without the need for special tools.
The team set out to create an affordable robotic arm that could showcase robotic concepts in a physical environment, like kinematics, a mathematical process underpinning the movements of robots that can be difficult to understand without physical demonstrations. Using the Denavit-Hartenberg convention, the robot was implemented to use matrices with the desired joint angle values to determine the position of the end effector or any object the robot is trying to move like a pen or marker.
Not only does the robotic arm have a low production cost, but it can be connected to WiFi and teleoperated via an online app as well. Users can also easily access every command and parameter behind the arm's movements thanks to the program it's based on. This allows students to further understand a robot's behavior.
The robotic arm has four key components: an electromechanical arm structure, a control system, a WiFi communications module and a human-machine interface. And since it's entirely open source and easy to modify, it can be designed and adapted according to the user's specific needs.
"Our robot was primarily designed for educational purposes," said researcher Victor H. Benitez. "Educators can easily use and modify the robotic arm to teach students about the applications of the many topics mentioned in their lessons, even when facing the difficulties of online education."
The team is currently working on a second version of the robotic arm to improve its performance while keeping the price low. Though it's main use is for demonstrating complex robotic concepts, the team believes it can also be applied to topics related to 3D printing, computer science and programming.