Autonomous Quadcopter UAS P15230
Agenda ● Project Description / High Level Customer Needs / Eng Specs ● Concept Summary ● System Architecture ● Design Summary ● System Testing Results ● Objective Project Evaluation: Success and Failure ● Opportunities/Suggestions for Future Work
Project Description An autonomous Unmanned Aerial System (UAS) was built on an off-the-shelf quadcopter base. The quadcopter was designed in order to navigate an obstacle-filled course using various navigation techniques, including simultaneous mapping and planning, object detection and avoidance, and basic facial recognition. The project was originally intended for use in the ImagineRIT “RIT Meets the Jetsons: Flying Cars” competition, and was designed as such. The project was later entered in the ARM Design Competition held during ImagineRIT.
Customer Requirements
Engineering Requirements
System Architecture: Overall 5 Architectural Components: 1. Flight Actualization 2. Mapping, Pathing, and Object Detection 3. Localization 4. Facial Recognition 5. Safety
System Architecture - Electrical ● Power Distribution ● Signal Path System Interconnection Printed Circuit Board
Electrical System-Power Management ● Battery a. Turnigy:4000mah ● Hall effect current sensor a. ACS 709 System interconnect
Power Management cont. ● Current and Voltage Reading a. Voltage Reading -ADC on Teensy:13-bit -Resistor Voltage Divider b. Current Reading - ADC on Teensy:13-bit -3V max Resistor Voltage Divider
System Architecture - Embedded uC ● Interval Timer ● Pulse Position Library ● ISR Capture ● Analysis
Design Summary: Mechanical ● Frame: ○ DJI F450 Airframe Kit ■ Simple to replace components ■ Large Buildon space ■ Stable ● Propulsion ○ DJI E300 Tuned Propulsion Kit ■ 30A ESCs & 2212 920kV motors 9.4x4.3” props ■ 600 grams/axis rated max lift ● Craft lifts full load and has no issues overcoming initial lift at static thrust. Would be cautious about adding much more weight to craft without adjusting propulsion system ● Rotor Shroud: ○ Designed to protect mechanical and electrical components of craft as well as bystanders and users. ● Leg Extensions: ○ 3D printed extensions raise craft for increased ground clearance. ○ Give guaranteed level take off ○ Allow for additional hardware mounting below lower plate of craft ■ Battery ■ Future add-ons
Design Summary: Mechanical cont. ● Current craft damage analysis Shroud corner damage (repaired) ○ Shroud ■ collision with ceiling in lab caused corner to break off, but performed its job and protected both the craft and bystanders ○ Raspberry Pi 2 & Pi Cam ■ SD card slot on Pi 2 broke off in ceiling collision ■ Pi Cam 3D print bracket was damaged in collision, needs to be replaced ● Moving Forward (future safety/durability improvement) Raspberry Pi 2 SD card slot Pi Cam Bracket ○ Shroud weak points such as corners may be reinforced with bamboo skewers/bilateral tape ○ Protective covers can be produced for electrical hardware components that are more exposed on top of shroud (Raspberry Pi 2, Pi Cam, GY- 80, Teensy) ■ Con: Added weight ■ Alternative: Imbed more components into shroud foam
Design Summary: Software Class Diagram
Design Summary:Software State Chart
Design Summary: LIDAR Scanning Algorithm
System Testing: LIDAR Scanning Algorithm ● Successfully tracks laser line pixel location indoors up to 30 ft away. ● Converts line pixels to real world locations, but needs more accuracy verification. ● Can convert detection to real world coordinates with simulated live compass heading and craft location coordinates. ● Fixed-point C code formatted for full mapping system integration but never tested. Hardware ● Pi NoIR camera successfully detects 980nm line laser indoors with IR pass filter. The sun and bare incandescent light sources can cause issues. ● Line laser power output can be tuned down to safe ~1 mW levels at 3 ft away and still be visible within 30ft. ● Raspberry Pi 2 runs standalone algorithm at about 5-15 fps, but data monitoring causes major performance hit. Untested running full system integration.
Design Summary: Localization Using three routers with known coordinates on the <x,y,z=0> grid, the Raspberry Pi is connected to each and a distance is calculated based on the signal strength of the router at that time. These distances are then used in Math used to derive equations for <x,y,z> coordinates geometric formulae to obtain the position of the craft.
System Testing: Mapping & Path Planning 2D grid update mapping ● Left, Right, and back sonar sensors update the map if an object is detected within a 1 meter range.Map update accounts for heading of the craft with initial calibrations at start of program. ● LIDAR integration untested ● Altitude determination of the craft varies by .5 meters from barometer readings, and is limited by sonar range (<3m) Path Planning ● Path planning to multiple points on the same map is achieved in simulation ● Path planning with a dynamic map (updated by simulated sonar reading) is achieved ● Craft not able to navigate with planned paths.
System Testing: Embedded uC ● Used I2C Master-Slave Arduino-to-Teensy connection to emulate communication with Raspberry Pi ● Over Ride Switch - Confirmed Working through RC UAS Test ● Autonomous Mode - Confirmed Working though RC UAS Test ○ Further PID refinement necessary
System Testing - Localization ● WiFi-based triangulation proved to be too inaccurate for the precise measurements needed for pathing algorithms. ● Calculated distances depended on signal strength, which did not vary enough with distance to make accurate measurements. ● Could be used for larger-scale position finding, ie. for general location of craft, but should no longer be considered for pinpoint measurements. ● For future versions of the project, RFID could be considered as a replacement. The triangulation method and final output would remain the same, with only the distance calculations changing.
Project Evaluation Current State: A quadcopter platform capable for research in autonomous flight. Hardware platform may interface with any guidance system using i2C communication and defined packet structure, additionally full RC control is available to user. Main hardware components are off the shelf allowing for easy replacement.
Project Evaluation: ERs Status S1:Complete Autonomous ● Craft does not fly completely autonomously, but has autonomous mode implementable. S2: Take still images during flight ● Craft can not take still images, as the camera used continually throws errors when used. S3: Store still images during flight ● Can not store still images, as there is no camera to record the images and no dedicated storage space available on the craft. S4: Flys duration of function ● Craft has 10 minutes of continuous flight
Project Evaluation: ERs Status cont. S5: Can fly with additional payload ● Craft can fly with additional payload, however this requirement was no longer considered necessary for ImagineRIT. S6:Portable ● Can easily be carried by the user S7: Onboard range sensing ● Sonar sensors are integrated into the onboard system. LIDAR hasn’t been integrated into the onboard system. S8: Obstacle avoidance ● Craft isn’t tuned to avoid obstacles that it recognizes.
Project Evaluation: ERs Status cont. S9: Safe for users and bystanders ● Craft can be taken into manual mode. Safe if experienced pilot. S10: Stay within Budget ● Project total was $1125.14; this is $125.14 over budget. S11: Facial Recognition ● Facial Detection implemented in MATLAB environment but not integrated into onboard system. S12: Craft will not break on impact ● Craft take significant damage from drops of greater than 3 ft and high speed collision with objects
Opportunities & Suggested Future Work 1. Finalize Flight Control a. Tuning of Flight Controls (CC3D & Teensy PID) b. Face Tracking or Alternative Following UAS c. WiFi Positioning Integration To UAS For Indoor Flight d. GPS Positioning Integration To UAS For Outdoor Flight 2. Indoor Mapping (2D or 3D) a. LIDAR Integration To UAS b. Use of RFID or similar system for more accurate coordinate position 3. Refine PCB for Late-Term Changes 4. Ergonomics a. Battery b. Rx & Tx Binding Method
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