It must be sent using the API in order to visualize it. Grid Button: Toggles the visualization of the navigation matrix. The student can also use it to visualize the output of the print() function. Simulation Button: Opens a VNC with GZClient.Ĭonsole Button: This shows the error messages related to the student’s code that is sent. The lower the value the slower the simulation will run, which will vary depending on the computer. A RTF of 1 implies that simulation time is passing at the same speed as real time. RTF (Real Time Factor): The RTF defines how much real time passes with each step of simulation time. The student should adjust the Target Frequency according to the Measured Frequency. The numerator is the one set as the Measured Frequency who is the one measured by the computer (a frequency of execution the computer is able to maintain despite the commanded one) and the input (denominator) is the Target Frequency which is the desired frequency by the student. A higher value implies the code runs a large number of times. A smaller value implies the code runs less number of times.
Reset button resets the simulation(primarily, the position of the robot).īrain and GUI Frequency: This input shows the running frequency of the iterative part of the code (under the while True:). Load button loads the code from the local machine. Save button saves the code on the local machine. Stop button stops the code that is currently running on the Robot. Play button sends the code written by User to the Robot. Pull the current distribution of Robotics Academy Docker Image:įrom GUI import GUI from HAL import HAL # Enter sequential code!Ĭontrol Buttons: The control buttons enable the control of the interface. Windows users should choose WSL 2 backend Docker installation if possible, as it has better performance than Hyper-V. This is the preferred way for running the exercise.
The main objective will be to cover the largest area of a house using the programmed algorithm. The robot is equipped with a map and knows it’s current location in it. The objective of this practice is to implement the logic of a navigation algorithm for an autonomous vacuum cleaner by making use of the location of the robot.
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