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Autonomous Robot Taxi Obstacle Detection, Passenger Logic, and Hardware Module Suggestions

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  • #1 21665097
    Deepesh Verma
    Anonymous  
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  • #2 21665098
    Peter Evenhuis
    Anonymous  
  • #3 21665099
    Steve Lawson
    Anonymous  
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  • #4 21665100
    Deepesh Verma
    Anonymous  
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  • #5 21665101
    Cody Tappan
    Anonymous  
  • #6 21665102
    Gary Crowell Jr
    Anonymous  
  • #7 21665103
    Mark Harrington
    Anonymous  
  • #8 21665104
    Deepesh Verma
    Anonymous  
  • #9 21665105
    Cody Tappan
    Anonymous  
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  • #10 21665106
    Mark Harrington
    Anonymous  
  • #11 21665107
    Deepesh Verma
    Anonymous  

Topic summary

The discussion focuses on designing an autonomous robotic taxi capable of detecting various terrain obstacles such as uphill, plain, downhill, single bump, and two consecutive bumps. The taxi must stop to pick up one passenger upon detecting a single bump and drop all passengers when two consecutive bumps are detected, with a maximum passenger capacity of three. Key hardware suggestions include using accelerometers with interrupt outputs to detect shocks and differentiate terrain types by analyzing tilt and impulse data. Alternative sensor options mentioned are shock sensors, infrared emitter-receiver pairs for bump detection via resistance changes, microwave sensors, and reflected light sensors. The use of real-time operating systems (RTOS) is recommended to manage multiple sensor inputs and navigation tasks concurrently. Additional advice includes calibrating sensor data by comparing physical measurements such as wheel arch to ball joint distances under different load conditions to detect bumps. References to Renesas Car Rally kits provide example code and sensor integration concepts, though primarily for line detection rather than bumps. The importance of combining sensor data and employing fuzzy logic or finite state machines for decision-making is emphasized.
Summary generated by the language model.
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