A team of researchers at Carnegie Mellon University has developed a system that will allow robotic engineers to learn to code.
The project was inspired by a popular program for roboticists that uses voice recognition to teach a robot how to make complex calculations.
The researchers hope their system will enable robotic engineers and engineers in other fields to learn from each other and develop new technologies.
The researchers developed a new system, called the Robotic Engineered User Interface (REUI), that they call the first of its kind.
The REUI is a virtual machine that takes a robot and translates its commands into machine-readable text.
The REUi is based on a system developed at the University of Southern California and is built on a Raspberry Pi computer.
The computer sits inside a robot.
The robot then translates the REUIs commands into commands that can be executed by the robot.
That is, the robot interprets a human command and executes it.
The system allows robots to read instructions in text files that they can then execute.
In this way, robots can learn from one another, and they can apply new knowledge they have learned from previous robots.
This system uses a neural network, a system of interconnected processors that are designed to simulate the behavior of a living, breathing human.
The neural network uses a variety of inputs to create a model of the environment in which the robot is operating.
The system then uses that model to identify and simulate actions that might be performed by the human operator.
This allows the robot to be programmed to perform a task without the need for a human.
The brain of the robot, which is connected to the computer, uses the model to determine whether a given action is an appropriate action to perform.
When the model can make a decision about whether to perform the action, it communicates that decision to the human who is in control of the robotic arm.
The human then interprets the decision and acts accordingly.
To use the system, a robot needs to be connected to a computer and an Internet connection.
The robot then uses the REUs input to make decisions about how to respond to a given set of instructions, such as whether to open a door or push a button.
The model determines which actions to perform based on what it sees and hears.
The ROBOT is capable of running programs in a variety, and is also capable of learning to make new programs, the researchers said.
In addition, the system can be used to build other systems, which can then be used in a number of different applications.
The ROBOT can also be used for more sophisticated tasks such as driving robots.
The team’s goal is to build robots that can learn to program themselves and build applications to learn.
The project has received a grant from the National Science Foundation (NSF) to explore ways to improve the system.
In a statement, the Carnegie Mellon team said the project is based largely on research done by the National Robotics Engineering Center at Carnegie-Mellon.