# 1 Lab + Hwk 4: Introduction to the e-puck Robot

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4 S: Stop the motors and execute the following commands p,0,0 d,200,-200 While the e-puck is moving, press Q <Enter> from time to time. Q 4 (4): Can you guess what P does? What do the values returned by Q mean? By how much does Q increase per second? Q 5 (5): Stop the motors again and execute the following commands P,0,0 D,200,200 By how much does Q increase for each wheel rotation? Let your e-puck cross a sheet of A4 paper at this speed. Read the values returned by Q when the robot reaches the end of the paper. Infer the approximate length of the paper! You can now quit minicom by typing Ctrl-A Q. 2.3 Obstacle Avoidance In the previous lab, we introduced the Braitenberg robot controller. In this section, you will run the Braitenberg obstacle avoidance algorithm on the e-puck itself. S: Within your Lab-4 directory, type the following commands to program your robot with the Braitenberg obstacle avoidance program: cd obstacleavoidance/ epuckupload -f obstacleavoidance.hex 999 Don t forget to press the blue reset button on the e-puck as soon as the dots appear on the screen (stars indicate that program is being uploaded). Now, put the robot in the arena and observe it doing obstacle avoidance. S: Do the same for obstacleavoidance_log. This code differs in three ways from the previous algorithm: The output of the infrared sensors is passed through a log function. Since the infrared sensors output decreases exponentially with the distance, this linearizes the Braitenberg inputs. An average over 10 samples is computed in order to reduce measurement noise. AP, Distributed Intelligent Systems, Lab+Hwk 4: Introduction to the e-puck robot 4

6 Q 13 (8): sin(), cos() and floating point operations are very time-consuming on microcontrollers. How could you speed up the following code: float amplitude_at_freq6(int sample[]) { int i; float x=0., y=0.; for (i=0; i<512; i++) { x+=cos((float)i/6*2*pi) * (float)(sample[i]); y+=sin((float)i/6*2*pi) * (float)(sample[i]); } } return sqrt(x**2+y**2); (Note that the microcontroller on the e-puck would allow us to further optimize such code using DSP operations. This, however, requires assembly code and is not what we want you to do here.) Q 14 (5): The following sketch describes how the e-puck library generates the motor signals for the left motor. (The right motor works exactly the same way.) Your program interval Timer 5 (hardware timer on the microcontroller) set restart Function void set_motor_speed_left(int speed) set timer interval and restart timer interrupt Timer interval Timer 5 interrupt function void _ISRFAST _T5Interrupt() set motor signals Signal A Signal B Signal C Signal D... Timer interrupts Each time the motor signals change, the (stepper) motor moves one step. What happens if you call set_motor_speed_left extremely often, such as in Q 11 with a low wait value? Q 15 (5): What would happen (physically) if you set a too high speed (e.g. 1500)? r Q 16 (12): An e-puck starts at t 0 at x = [ x y ] T [ 0 0 0] T 0 0 θ 0 =. Its initial position uncertainty is P 0 = At t 1 it stops and the wheel counter indicate that the left wheel traveled forward Δs l = 0. 96m and the right wheel traveled AP, Distributed Intelligent Systems, Lab+Hwk 4: Introduction to the e-puck robot 6

7 forward for Δ s r = 1. 04m. The error constants are k r = k l = and the distance between the wheels is b = 5. 3cm. What is the position and orientation at [ x y ] x 1 = 1 1 θ1 at t 1? (Hint: formulas in Siegwart, Nourbakhsh Autonomous Mobile Robots ). What is the covariance matrix P 1 representing the position uncertainty at t 1? (Hints: use the error propagation law given in formula 4.60 to compute P 1, the Jacobian F for a robot like the e-puck is given in 5.11). It is easiest if you set the problem up in MATLAB. AP, Distributed Intelligent Systems, Lab+Hwk 4: Introduction to the e-puck robot 7

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