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Explore the design process of an innovative autonomous firefighting robot for a prestigious international contest, including sensors, microcontroller, routing, and flame extinguishing mechanisms. Witness the challenges and solutions in navigating mazes, detecting flames, and implementing SLAM technology. Follow the use of advanced sensors like laser scanners and thermal array sensors to improve performance and efficiency.
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Team 1617: Autonomous Firefighting Robot Contest Katherine Drogalis, Electrical Engineering Zachariah Sutton, Electrical Engineering Chutian Zhang, Engineering Physics Advisor: Professor John Ayers
Overview • Project Overview & Contest Background • Mechanical Design & Layout • Sensors& Routing • Microcontroller • Flame Extinguishing • Power Supply • Budget
Design a Fully Autonomous Robot to Find & Extinguish a Flame • Trinity International Robot Contest (April 1-3, 2016) • User initiated, autonomous start & navigation • Search for and extinguish burning candle • Design can be extended to real life situations
Trinity International Robot Contest • 8x8’ plywood maze • Arbitrary start position • Competing in 2 of 3 levels • Timed trials • Unique robot • 31x31x27 cm robot Level 1 Arena Level 2 Arena
Round Polycarbonate Body • No rigid corners to bump walls • Electrical insulating property • Strong; Will not crack when cut • Threaded rod for support • Levels: Top to Bottom • Start button; LED; mic; kill-power plug; handle • Flame detection sensors; extinguisher • Microcontroller; laser scanner • Driving motors; control circuit; batteries
Two Motors Independently Driving Two Wheels • Can turn different angles simultaneously • Take commands from microcontroller • Option 1: Stepper Motors • Position controlled: constant input voltage drives motor to specific position • Draws current to maintain position - waste of battery power • Option 2: Servomotors • Similar to Stepper • Consumes power as rotates to position then rests - better, wastes less power! • Angle of rotation is limited to 180o (or so) back and forth • Complicated setup with PWM tuning
Best Option: DC Motor w/ Encoder • Velocity controlled: constant input voltage drives motor to specific velocity • Can control position by applying velocity commands over a certain time • Pulse-Width Modulation signal • FAST - 100 rpm • 12V - perfect for battery operation • Count wheel rotations with encoders • 64 counts per rotor revolution (6400 counts per wheel revolution)
Need to Sense: Walls/Obstacles & Flame • Range sensing options • Ultrasonic: cheap, easy to use, low interference, low resolution • Infrared: cheap, range limited, interference prone, low resolution • Laser: expensive, long range, low/no interference, processing required, high res • Flame sensing options • Look for presence of both light and heat • Light: photoresistors/photodiodes, subject to external interference • Heat: IR non-contact sensing, must work at range of ~1 m
Choice: 360o Laser Scanner by RoboPeak • Scanner vs. Stationary • Stationary: cheaper, would need to be mounted on scanning platform • Scanner: set sample rate, configurable scan speed, built-in angular encoder • Measurements in body reference frame polar coordinates (heading = 0º) • “r” coordinate useful in finding wall discontinuities • Need to convert to cartesian for SLAM • 2000 samples per second • Vary scan speed to control angular distance between samples • Get ~1 sample per degree with 5.5 Hz scan rate
Flame Sensor • RoBoard RM-G212 16X4 Thermal Array Sensor • produce a map of heat values • able to pick up the difference 1.5m away • low power consumption • 16 x 4 = 64 pixels • FOV: 60º horizontal, 16.4º vertical • 0.02 Degree Celsius uncertainty • Can find center of candle at close range • Have a particular pixel act as target location • May be unecessary to add light sensing
Experimental Flame Sensor Heat Map Heat measurements at distance of 0.2 m Heat measurements at distance of 1.5 m
Experimental Flame Sensor Heat Map Candle in total field of view
Routing/Navigation • SLAM (Simultaneous Localization and Mapping) • Find current location in a map of landmarks • Use laser to pick out corners and terminal points in walls • Predict next position from current position and a given control command • Compare prediction with sensor result after command is executed • Correct based on previous reliability of sensor measurements and predictions • Adaptive
Microcontroller • Arduino Mega 2560 • 256 kB of Flash Memory • 8 kB of SRAM • 4 kB of EEPROM • 7 to 12 Volts • Highly versatile • Many available open source libraries • Programmable in C++ • Raspberry Pi (possible addition) • Helps the speed of processing • All real-time calculations with scanner data must be accomplished within 500 us • Will add if unable to make Arduino code this efficient
Flame Extinguishing • Realistic: Compressed gas (CO2) • Best option for large-scale fire - bonus points! • Cartridge at the back of the robot • Extended nozzle at the front aligned with the sensors • Pointed directed at the candle flame • Unrealistic: Fan • Will make a large-scale fire worse! • Controlled by Arduino • Fallback option
Power Supply and Other Requirements • Rechargeable DC batteries • Two sets - use one while charging other - save time! • 4 separate cells - option to pull power from individual cells • Max 14.8 V • 5500 mAh • 532.2 grams • Other requirements • Start button: green background • LEDs: white background • Microphone: blue background • Kill-power plug: yellow background • Handle