Page 172 - Toucpad robotics C11
P. 172

5.  Mobility loop: Distance-based obstacle avoidance with PWM (via pigpio or L298N enable pins).
                  6.  Energy saver: Read BH1750/LDR-ADC   toggle relay.
                  7.   Integrate  and  run  end-to-end: Move    avoid    handle QR attendance  at  a checkpoint    demonstrate
                     energy saver.
                  8.  Document & demo video.
              I.  Validation Checklist (teacher rubric snapshot)
                     Movement stable ( ) | Obstacle avoidance reliable ( ) | Servo mechanism works ( ) | Attendance logs correctly
                     l
                     ( ) | Energy saver responds to light changes ( ) | Clear documentation ( )


                                                                                    Lid
                                          Ultrasonic Sensor
                                                                                       Servo



                                                                                          RFID
                                           LDR


                                      DC Motor






                                        Motor
                                                                                         Car
                                           Arduino Uno




                                                    Smart Campus Assistant Robot

                                                                                       21 st   #Coding & Computational Thinking
              Assignment 2   Disaster Response Drone Simulation                       Century
                                                                                       Skills  #Digital Literacy
              Theme: Search-and-rescue planning with safe, school-friendly simulators.
              A.  Plan & Scenario Setup
                  1.  Define a disaster map: 10×10 grid with blocked cells (debris), safe paths, and targets (survivor markers).
                  2.  Select simulator:
                         DroneBlocks (block coding), CoDrone EDU, or VEXcode VR (Drone/Robot variant).
                     °
                         Optional Python vision add-on with OpenCV for image/marker detection (Pi/PC camera).
                     °
              B.  Mission Requirements (write as specs)
                     Autonomous grid search (lawnmower/zig-zag or spiral).
                     l
                     Obstacle avoidance (skip blocked cells or altitude adjust).
                     l
                     Detect target (colored marker/QR in sim or via image detection).
                     l
                     Raise alert/log (on-screen message, CSV log, or simulated beacon drop).
                     l
              C.  Algorithm Design (paper first   then blocks/code)
                  1.  State machine: TAKEOFF   SEARCH   DETECT   AID_DROP (optional)   RETURN_HOME   LAND.
                  2.  SEARCH strategy:
                         Zig-zag (lawnmower): for row in 1..N   sweep left   right then right   left.
                     °
                         Skip/route around blocked cells (predefined in array).
                     °

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              Touchpad Robotics - XI
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