Difference between revisions of "S22: Road Runner"

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We used CAN Communication setup between all the nodes of the RoadRunner setup. This CAN Bus is terminated with the use of two 120 ohm resistors at both the ends of the Bus. Message IDs were chosen based upon an agreed priority scheme and Bus arbitration scheme. We assigned high priority IDs to messages that controlled the motor, thereby controlling the actual physical movement of the car, followed by sensor and GEO messages, and lowest priority messages were for debug and status messages from the respective nodes .
 
We used CAN Communication setup between all the nodes of the RoadRunner setup. This CAN Bus is terminated with the use of two 120 ohm resistors at both the ends of the Bus. Message IDs were chosen based upon an agreed priority scheme and Bus arbitration scheme. We assigned high priority IDs to messages that controlled the motor, thereby controlling the actual physical movement of the car, followed by sensor and GEO messages, and lowest priority messages were for debug and status messages from the respective nodes .
 
More technical details to fill in..
 
More technical details to fill in..
 +
 +
[[File:core_CAN_draw.png|200px|center]]
  
 
=== Hardware Design ===
 
=== Hardware Design ===

Revision as of 20:37, 19 April 2022

Road Runner

Road runner logo.png

WorkinProgress.jpg


Abstract

Road Runner is a self navigating car built with the ability to drive to a specified geo-location within its battery range, while avoiding any physical obstacles that come on its way and successfully reaching its destination, with no human intervention apart from commanding the destination location . The car’s infrastructure has four important nodes (Driver, Sensor and Bridge, Geo and Motor) communicating within themselves over internal CAN Bus and with the end user over a mobile application. The car always strives to stay on and maintain its path to the destination by periodically sensing and processing all the relevant information from the nodes to arrive at an informed decision. It is built on top of a hobby grade RC car chassis with all the necessary adjustments and components to achieve its intended objective of self navigating and object avoidance, one of the basic requirements and functionality of an autonomous vehicle.

Introduction

The project was divided into 5 modules:

  • Bridge and Sensor Controller
  • Motor Controller
  • Geo Controller
  • Driver / LCD Controller
  • Android app interface

Team Members & Responsibilities

<Team Picture>

Road Runner Firmware: GitLab Repo

Team Members:

  • Dhruv Choksi
  • Jonathan Doctolero
  • Tudor Donca
  • Hisaam Hashim
  • Saicharan Kadari
  • Kyle Kwong


Project Subteams:

  • Bridge and Sensor Controller:
    • Tudor Donca
    • Saicharan Kadari
  • Motor Controller:
    • Dhruv Choksi
    • Hisaam Hashim
  • Geological Controller:
    • Kyle Kwong
    • Jonathan Doctolero
    • Saicharan Kadari
  • Driver and LCD Controller:
    • Hisaam Hashim
    • Kyle Kwong
  • Android Application:
    • Jonathan Doctolero
    • Tudor Donca
  • Integration and System Testing:
    • Tudor Donca
    • Dhruv Choksi
    • Hisaam Hashim
    • Saicharan Kadari
    • Kyle Kwong
    • Jonathan Doctolero




Schedule

Week# Start Date End Date Task Status
1 03/06/2022 03/12/2022
  • Read previous projects, gather information and discuss among the group members.
  • Discuss each team-member's preference and assign controller roles
  • Create parts list for the RC car, discuss, and decide on each item
  • Completed
2 03/13/2022 03/19/2022
  • Design interface for Bridge and Sensor Controller, with unit tests
  • Design interface for Motor Controller, with unit tests
  • Design interface for Driver and LCD Controller, with unit tests
  • Integrate Bridge/Sensor Controller to CAN bus with DBC, handling messages
  • Integrate Motor Controller to CAN bus with DBC, handling messages
  • Integrate Driver Controller to CAN bus with DBC, handling messages
  • Order all parts from list and save tracking/price info
  • Completed
3 03/20/2022 03/26/2022
  • Connect Sensor, Motor, and Driver controller together on CAN bus and verify messages
  • Connect all nodes together on the CAN bus, connect android app, verify messages across all nodes
  • Design interface for Geological Controller, with unit tests
  • Design basic android app connection and communication
  • Completed
4 03/27/2022 04/02/2022
  • Integrate Geological Controller to CAN bus with DBC, handling messages
  • Integrate Android app with Bridge/Sensor controller, sending/receiving messages both ways
  • Integrate Motor and Steering with PWM control, figure out the working ranges
  • Integrate Bluetooth module to Bridge/Sensor controller, with UART logic
  • Connect Android app to Bridge/Sensor controller, send test message
  • All parts received
  • Completed
5 04/03/2022 04/09/2022
  • Connect all nodes together on the CAN bus, connect android app, verify messages across all nodes
  • Mobile app can send coordinates to Bridge controller
  • Start RPM sensor logic implementation and add it to Motor controller
  • MILESTONE - All individual modules considered "Roughly Working" with hardware interfaced
  • Completed
6 04/10/2022 04/16/2022
  • Integrate GPS and Compass peripherals, writing the driver and unit tests
  • Have Driver node process GPS position/heading/bearing messages and incorporate in the driver logic
  • Complete RPM sensor and integrate with Motor controller for reliable PID control
  • Bridge sends to mobile app car status / telemetry data
  • Compile additional parts list and order them
  • MILESTONE - Basic car driving ability with basic obstacle avoidance
In Progress
7 04/17/2022 04/23/2022
  • Create a on-board battery power supply for all components
  • Complete the Compass I2C integration and read values from the peripheral
  • Have PWM signals reliably controlling the motor speed, start working "backwards driving mode"
  • Interface LED ring on the Driver controller and display heading direction
  • MILESTONE - Integrated, reliably "heading" towards provided destination bearing, basic obstacle avoidance
  • First Demo (Apr. 19)
8 04/24/2022 04/30/2022
  • 3D print sensor housings, mounting for the whole platform
  • Design and solder the prototype board with all SJTwo boards
  • Add data to display on the LCD screen
  • Outdoor testing for longer range trips, and complete necessary enhancements
  • MILESTONE - Integration part 2, perform obstacle avoidance and destination bearing
  • Second Demo (Apr. 26)
9 05/01/2022 05/07/2022
  • Verify that the electrical and mechanical work is complete
  • MILESTONE - Integration and outdoor testing, adding necessary software changes
  • Third Demo (May 3)
10 05/08/2022 05/15/2022
  • Add "beep beep" sound with speaker
  • MILESTONE - Integration testing, deal with uneven terrain, reliable waypoints navigation and obstacle avoidance
  • Fourth Demo (May 10)


Parts List & Cost

Item# Part Description Vendor Qty Cost
1 RC Car Redcat [1] 1 $153.00
2 CAN Transceivers Various 6 $55
3 Ultrasonic Sensors Max Botix[2] 3 $134.00
4 Adafruit Bluetooth UART Tranceiver Adafruit[3] 1 $33.90
5 GPS Module and Antenna Adafruit[4][5] 1 $59.50
6 Compass Module Adafruit[6] 1 $29.00
7 Wheel Speed RPM Encoder 1
8 Discrete Electronic Components Generic[7] 1 $


Printed Circuit Board

<Picture and information, including links to your PCB>



CAN Communication

We used CAN Communication setup between all the nodes of the RoadRunner setup. This CAN Bus is terminated with the use of two 120 ohm resistors at both the ends of the Bus. Message IDs were chosen based upon an agreed priority scheme and Bus arbitration scheme. We assigned high priority IDs to messages that controlled the motor, thereby controlling the actual physical movement of the car, followed by sensor and GEO messages, and lowest priority messages were for debug and status messages from the respective nodes . More technical details to fill in..

Hardware Design

<Show your CAN bus hardware design>

DBC File

Gitlab link to the RoadRunner DBC file

VERSION ""

NS_ :
	BA_
	BA_DEF_
	BA_DEF_DEF_
	BA_DEF_DEF_REL_
	BA_DEF_REL_
	BA_DEF_SGTYPE_
	BA_REL_
	BA_SGTYPE_
	BO_TX_BU_
	BU_BO_REL_
	BU_EV_REL_
	BU_SG_REL_
	CAT_
	CAT_DEF_
	CM_
	ENVVAR_DATA_
	EV_DATA_
	FILTER
	NS_DESC_
	SGTYPE_
	SGTYPE_VAL_
	SG_MUL_VAL_
	SIGTYPE_VALTYPE_
	SIG_GROUP_
	SIG_TYPE_REF_
	SIG_VALTYPE_
	VAL_
	VAL_TABLE_

BS_: 

BU_: DBG DRIVER MOTOR SENSOR_BRIDGE GEOLOGICAL

BO_ 100 MOTOR_CMD: 4 DRIVER
 SG_ MOTOR_steer_degrees : 0|9@1- (1,-45) [-45|45] "degrees" MOTOR
 SG_ MOTOR_speed_kph : 9|20@1- (0.1,-40.5) [-40.5|40.5] "kph" MOTOR

BO_ 101 MOTOR_STATUS: 4 MOTOR
 SG_ MOTOR_STATUS_steer_degrees : 0|9@1- (1,-45) [-45|45] "degrees" DRIVER
 SG_ MOTOR_STATUS_speed_kph : 9|20@1- (0.1,-40.5) [-40.5|40.5] "kph" DRIVER



BO_ 200 SENSOR_SONARS: 8 SENSOR_BRIDGE
 SG_ SENSOR_SONARS_left : 0|10@1+ (1,0) [0|500] "cm" DRIVER
 SG_ SENSOR_SONARS_right : 10|10@1+ (1,0) [0|500] "cm" DRIVER
 SG_ SENSOR_SONARS_middle : 20|10@1+ (1,0) [0|500] "cm" DRIVER
 SG_ SENSOR_SONARS_back : 30|10@1+ (1,0) [0|500] "cm" DRIVER

BO_ 201 GPS_DESTINATION: 8 SENSOR_BRIDGE
 SG_ GPS_DESTINATION_latitude : 0|28@1- (0.000001,-90.000000) [-90|90] "Degrees" GEOLOGICAL
 SG_ GPS_DESTINATION_longitude : 28|28@1- (0.000001,-180.000000) [-180|180] "Degrees" GEOLOGICAL

BO_ 350 GEO_STATUS: 8 GEOLOGICAL
 SG_ GEO_STATUS_COMPASS_HEADING : 0|12@1+ (1,0) [0|359] "Degrees" DRIVER,SENSOR_BRIDGE
 SG_ GEO_STATUS_COMPASS_BEARING : 12|12@1+ (1,0) [0|359] "Degrees" DRIVER,SENSOR_BRIDGE
 SG_ GEO_STATUS_DISTANCE_TO_DESTINATION : 24|24@1+ (1,0) [0|0] "Meters" DRIVER,SENSOR_BRIDGE

BO_ 360 GEO_CURRENT_POSITION: 8 GEOLOGICAL
 SG_ GEO_CURRENT_POSITION_latitude : 0|28@1- (0.000001,-90.000000) [-90|90] "Degrees" DRIVER,SENSOR_BRIDGE
 SG_ GEO_CURRENT_POSITION_longitude : 28|28@1- (0.000001,-180.000000) [-180|180] "Degrees" DRIVER,SENSOR_BRIDGE 

BO_ 500 DEBUG_SENSOR_BRIDGE: 8 SENSOR_BRIDGE
 SG_ sensor_left_raw_value : 0|12@1+ (1,0) [0|0] "" DBG
 SG_ sensor_right_raw_value : 12|12@1+ (1,0) [0|0] "" DBG
 SG_ sensor_middle_raw_value : 24|12@1+ (1,0) [0|0] "" DBG
 SG_ sensor_back_raw_value : 36|12@1+ (1,0) [0|0] "" DBG

BO_ 510 DEBUG_DRIVER: 8 DRIVER
 SG_ driver_intention : 0|8@1+ (1,0) [0|0] "" DBG
 SG_ driver_steer_direction : 8|8@1+ (1,0) [0|0] "" DBG
 SG_ driver_drive_direction : 16|8@1+ (1,0) [0|0] "" DBG

CM_ BU_ DRIVER "The driver controller driving the car";
CM_ BU_ MOTOR "The motor controller of the car";
CM_ BU_ SENSOR_BRIDGE "The sensor and bluetooth bridge controller of the car";
CM_ BU_ GEOLOGICAL "The GPS and compass controller of the car";
CM_ BO_ 100 "Sync message used to synchronize the controllers";

BA_DEF_ "BusType" STRING ;
BA_DEF_ BO_ "GenMsgCycleTime" INT 0 0;
BA_DEF_ SG_ "FieldType" STRING ;

BA_DEF_DEF_ "BusType" "CAN";
BA_DEF_DEF_ "FieldType" "";
BA_DEF_DEF_ "GenMsgCycleTime" 0;

BA_ "GenMsgCycleTime" BO_ 100 1000;
BA_ "GenMsgCycleTime" BO_ 200 50;

BA_ "FieldType" SG_ 100 DRIVER_HEARTBEAT_cmd "DRIVER_HEARTBEAT_cmd";
VAL_ 100 DRIVER_HEARTBEAT_cmd 2 "DRIVER_HEARTBEAT_cmd_REBOOT" 1 "DRIVER_HEARTBEAT_cmd_SYNC" 0 "DRIVER_HEARTBEAT_cmd_NOOP" ;

BA_ "FieldType" SG_ 510 driver_intention "driver_intention";
VAL_ 510 driver_intention 1 "DESTINATION_HEADING" 0 "OBSTACLE_AVOIDANCE";

BA_ "FieldType" SG_ 510 driver_steer_direction "driver_steer_direction";
VAL_ 510 driver_steer_direction 2 "TURN_RIGHT" 1 "TURN_LEFT" 0 "STRAIGHT";

BA_ "FieldType" SG_ 510 driver_drive_direction "driver_drive_direction";
VAL_ 510 driver_drive_direction 2 "BACKWARDS" 1 "FORWARDS" 0 "STOPPED";










Sensor ECU

<Picture and link to Gitlab>

Hardware Design

Roadrunner uses three HRLV-MAXSonar-EZ0 MB1003[8] as its eyes and ears on the front and HRLV-MAXSonar-EZ at the rear end . The HRLV-MAXSonar-EZ0 comes in five different models for the ultrasonic sensor. The HRLV-MAXSonar-EZ sensor line is the most cost-effective solution for applications where precision range-finding, low-voltage operation, space-saving, and low-cost are needed. This sensor line features 1mm resolution, target-size and operating-voltage compensation for improved accuracy, superior rejection of outside noise sources, internal speed-of-sound temperature compensation, and optional external speed-of-sound temperature compensation.

These models are the MB1003, MB1013, MB1023, MB1033, and MB1043. The models are based on the beam width of the sensor. It was observed that MB1003 has the optimal beam pattern and was better suited for our objective of object detection. If the beam pattern is too wide given the, there is a greater chance of cross talk between sensors. If the beam pattern is too narrow, there may be blind spots which must be accounted for. Thus, three HRLV-MAXSonar-EZ0 MB1003 sensors were used and the possible unavoidable cross talk is contained by the optimal positioning and software configuration. It will be noted that the SJTWO board is configured to have three ADC channels. Thus to account for a fourth sensor, the DAC was configured to be an ADC channel. Details of this configuration will be discussed in the software design.


Front view of the MB1003 HRLV-MAXSonar-EZ0
Rear view of the MB1003 000 HRLV-MAXSonar-EZ0 with pin labels
Sensor Mounts and Placement

It is decided to place the ultrasonic sensors on mounts and a custom setup to reduce the cross talk and position them to capture the most field of view and possibly avoid any blind spots for the car movement.

Sensor Readings Extraction

To extract range readings from the MB1003, the "AN" pin which represents analog output was utilized. A range reading is commanded by triggering the "RX" pin high for 20us or more. From the details of the sensor datasheet it is observed that the output analog voltage is based on a scaling factor of (Vcc/512) per inch. As in our setup, all four of the sensors were powered from the SJTWO board, thus a 3.3v VCC was supplied to each sensor. According to the HRLV-MaxSonar-EZ datasheet, with 3.3v source, the analog output was expected to be roughly 6.4mV/inch. However, when initially testing the output range readings, the output was inaccurate. We were thankful for the past students' experiences to notice that the ADC channels for the SJTWO are configured at start-up to have an internal pull up resistor. Disabling this pull up resistor will be discussed more in Software Design and this made the range readings more accurate. The readings were tested by having multiple objects placed in front of each sensor and measuring the distance of the object to the sensors physically. Although the range readings accuracy is improved by the pull-up resistor modification, it was found that the range readings did not necessarily follow the expected 6.4mV/inch. Hence, we decided to calibrate the sensors to xx mV/inch. This value was extracted by placing objects around the sensors and checking if the analog output to inch conversion matched to the actual measured distance.

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>



Motor ECU

<Picture and link to Gitlab>

Hardware Design

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>



Geographical Controller

<Picture and link to Gitlab>

Hardware Design

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>





Communication Bridge Controller & LCD

<Picture and link to Gitlab>

Hardware Design

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>



Master Module

<Picture and link to Gitlab>

Hardware Design

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>



Mobile Application

<Picture and link to Gitlab>

Hardware Design

Software Design

<List the code modules that are being called periodically.>

Technical Challenges

< List of problems and their detailed resolutions>






Conclusion

<Organized summary of the project>

<What did you learn?>

Project Video

Project Source Code

Advise for Future Students

<Bullet points and discussion>

Acknowledgement

=== References ===