Difference between revisions of "S24: Team Falcons"

Revision as of 00:03, 24 May 2024

Project Title

Falcons

Abstract

The Falcon RC car project is the combined efforts of our team to create an autonomously RC Car that avoids all obstacles and follow GPS to reach the destination. Here, we have put in all our experience in software design, hardware design, unit testing, power systems, and mobile application development. Project development started in March of 2024 and ended in May 2024.

Introduction

The project was divided into 4 modules:

• Sensor and Bridge Controller
• Driver Controller
• Geo Controller
• Motor Controller

Driver controller is the master controller that receive inputs from sensor controller and geo controller, and gives output commands to motor controller. The destination coordinate is send from Android application to sensor node via Bluetooth. The app also send a hard start and stop to the car. The car starts only on receiving start signal from the app and stops completely on receiving stop signal from app.

Team Members & Responsibilities

<Team Picture>

Gitlab Project Link - https://gitlab.com/jincyjose491/sjtwo-c[1]

• Sensor
  • Link to Gitlab user1
  • Link to Gitlab user2

• Motor
  • Link to Gitlab user1
  • Link to Gitlab user2

• Geographical
  • Link to Gitlab user1
  • Link to Gitlab user2

• Communication Bridge Controller & LCD
  • Link to Gitlab user1
  • Link to Gitlab user2

• Android Application
  • Link to Gitlab user1
  • Link to Gitlab user2

• Testing Team
  • Link to Gitlab user1
  • Link to Gitlab user2

Schedule

Parts List & Cost

Printed Circuit Board

<Picture and information, including links to your PCB>

CAN Communication

<Talk about your message IDs or communication strategy, such as periodic transmission, MIA management etc.>

Hardware Design

<Show your CAN bus hardware design>

DBC File

<Gitlab link to your 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 IO MOTOR SENSOR GEO


BO_ 100 DRIVER_HEARTBEAT: 1 DRIVER
 SG_ DRIVER_HEARTBEAT_cmd : 0|8@1+ (1,0) [0|0] "" SENSOR,MOTOR

BO_ 10 START_STOP: 1 SENSOR
 SG_ START_STOP_cmd : 0|8@1+ (1,0) [0|1] "cmd" MOTOR

BO_ 200 SENSOR_SONARS: 5 SENSOR
 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_rear : 30|10@1+ (1,0) [0|500] "cm" DRIVER

BO_ 210 GEO_STATUS: 8 GEO
  SG_ GEO_STATUS_COMPASS_HEADING : 0|10@1+ (1,0) [0|359] "Degrees" DRIVER, SENSOR
  SG_ GEO_STATUS_COMPASS_BEARING : 10|10@1+ (1,0) [0|359] "Degrees" DRIVER, SENSOR
  SG_ GEO_STATUS_DISTANCE_TO_DESTINATION : 20|16@1+ (0.1,0) [0|1500] "Meters" DRIVER, SENSOR
  SG_ GEO_STATUS_BEARING_ANGLE_TO_CHKPT : 36|10@1+ (1,0) [0|359] "Degrees" DRIVER, SENSOR
  SG_ GEO_STATUS_DISTANCE_TO_CHKPT : 46|16@1+ (1,0) [0|1500] "Meters" DRIVER, SENSOR
  SG_ GEO_STATUS_GPS_LOCK_ACQUIRED : 62|1@1+ (1,0) [0|0] "Boolean" DRIVER, SENSOR

BO_ 250 GPS_DESTINATION_LOCATION: 8 SENSOR
 SG_ GPS_DEST_LATITUDE_SCALED : 0|32@1- (1,0) [-90000000|90000000] "Degrees" GEO
 SG_ GPS_DEST_LONGITUDE_SCALED : 32|32@1- (1,0) [-180000000|1800000000] "Degrees" GEO

BO_ 300 MOTOR_CMD: 2 DRIVER
 SG_ MOTOR_CMD_steering : 0|8@1- (1,0) [-45|45] "degree" MOTOR
 SG_ MOTOR_CMD_movement : 8|8@1- (0.1,0) [-10|10] "kph" MOTOR

BO_ 400 MOTOR_RPM_SENSOR_DATA: 1 MOTOR
 SG_ RPM_SPEED: 0|8@1+ (0.1,0) [0|10] "kph" DRIVER, SENSOR

BO_ 500 MOTOR_STATUS: 2 MOTOR
 SG_ MOTOR_STATUS_steering : 0|8@1- (1,0) [-45|45] "degree" DRIVER
 SG_ MOTOR_STATUS_movement : 8|8@1- (0.1,0) [-6|6] "kph" DRIVER

BO_ 510 DBG_DRIVER: 3 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

BO_ 800 DEBUG_GEO_COORDS_CURRENT: 8 GEO
 SG_ DEBUG_GEO_GPS_CURRENT_LAT_SCALED : 0|32@1- (1,0) [-90000000|90000000] "Degrees" DRIVER, SENSOR
 SG_ DEBUG_GEO_GPS_CURRENT_LON_SCALED : 32|32@1- (1,0) [-180000000|1800000000] "Degrees" DRIVER, SENSOR

BO_ 801 DEBUG_GEO_COORDS_CHKPT: 8 GEO
 SG_ DEBUG_GEO_GPS_CHKPT_LAT_SCALED : 0|32@1- (1,0) [-90000000|90000000] "Degrees" DRIVER, SENSOR
 SG_ DEBUG_GEO_GPS_CHKPT_LON_SCALED : 32|32@1- (1,0) [-180000000|1800000000] "Degrees" DRIVER, SENSOR

CM_ BU_ DRIVER "The driver controller driving the car";
CM_ BU_ MOTOR "The motor controller of the car";
CM_ BU_ SENSOR "The sensor controller of the car";
CM_ BU_ GEO "The geo controller of the car";
CM_ BO_ 100 "Sync message used to synchronize the controllers";
CM_ SG_ 100 DRIVER_HEARTBEAT_cmd "Heartbeat command from the driver";

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" ;

Sensor Controller ECU

• GitLab Link :Sensor Controller
  

Component selection

Selecting the appropriate sensor for an application is crucial. For this project, the sensor needs to be responsive, accurate, capable of operating in outdoor environments, and able to detect obstacles at long ranges. While there are numerous distance measurement options available, we have used MaxBotix (MB1010 LV EZ1) for all the positions. Initially we were thinking to use ultrasonic transducers sensors, but since it needs to have time measurement between the transmitted trigger signal and received echo which was complex software logic, it got ruled out. Maxbotix sensors have easy-to-use output formats and low power consumption of 2 mA for 3v power.

Sonar_Sensor

Hardware Design

Sensors are interfaced with combination of GPIO, ADC and other pins of the SJTwo board.

Sensor Interface with SJTwo board

Sensor pin configuration to SJTwo board

The sensor interface made use of onboard ADC (analog to digital converter) pins because we were utilizing the analog output of Maxbotix sensors. LPC 408x has a 12-cycle progressive approximation analog to a digital converter. These ADC have been designed to read sensor readings on a size of 4096 counts. To utilize sjtwo pins as ADC with better sign precision, there was the extra change expected in default ADC drivers which require disabling pull-up and pull-down resistors from the IOCON register of each ADC initialization. Maxbotix sensors need to get set off by logic high pulse on their Rx Pin, this has been executed by setting a proper trigger pin as GPIO output. By doing IOCON configurations specific to the ADC channel, selection of analog mode, and disabling pull-up, and pull-down mode, sensor inputs were configured for 3 ADC channels and 1 DAC Channel which was configured as ADC by doing appropriate IOCON Selection.

ADC Pin configuration

Sensors Pin Layout Pin Name Function P0.6 Trigger for middle sensor P0.7 Trigger for rear sensor P0.8 Trigger for left sensor P0.9 Trigger for right sensor P0.25 ADC input from left sensor P1_31 ADC input from right sensor P1_30 ADC input from middle sensor P0.26 DAC input from rear sensor

Sensors Connection Schematics

Software Design

Created APIs to trigger sensors, get the readings and calculate distance (readings from sensors are just raw values not real distance in inches). To achieve minimal cross-talk and faster sensor reading, used 20 Hz periodic_callbacks. Sensors are getting triggered in the specific manner like Left -> Right -> Rear ->middle to reduce crosstalk between adjacent sensors and power consumption of sensors. With this order, a 10ms window was given to each sensor. Software should sample 32 sensor readings in a buffer that might contain any abrupt intermittent value which needs to be avoided. By sorting these sensor readings using a quick sorting algorithm, the median was considered as the final end reading for broadcasting over the CAN bus. All the sensor values are digitally converted in the range of 0 to 4096 (12 bit ADC). These values are converted to distance format in centimeter unit using formula conv_val = (raw_val * 0.3182) - 0.3959.

Sensor Node Algorithm

Technical Challenges

• Problem: Crosstalk between adjacent sensors when all sensors transmitting waves simultaneously
  • Solution: Triggering sensors at different specific order and positioning sensors on the proper angles.

• Problem: Power Deficiency
  • Solution: At first, when the sensors were tested individually (as well as together on early iterations of the car), they performed to specifications. However, when other subsystems were integrated into the car, the sensor feedback fluctuated wildly. Adding capacitor to the sensor pins was the crucial solution.

• Problem: After fixing the power issues, still there were fluctuations in the sensor data, thereby causing collision while testing obstacle avoidance.
  • Solution: We created 3D mounts to place on the sensors head. Those mounts created the sonar waves to reflecting back to the sensor causing interference while testing. Thus removal of the 3D mounts helped to get better readings.

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

Geo controller: https://gitlab.com/jincyjose491/sjtwo-c/-/tree/master/projects/geo_controller?ref_type=heads

Navigation in modern systems seamlessly integrates GPS with compass technology to enhance driving experience and safety. GPS provides accurate location data by communicating with satellites, while the compass offers directional orientation of the vehicle. This combination is essential also in the RC car project as it enables the vehicle to autonomously maneuver to a given detsination coordinate. The GPS modules keeps track of the current position of the car, provides the direction that the car should move towards and the compass module keeps track of the direction in which the car is actually heading. Integrating the two modules, an algorithm has been developed as elaborated below to achieve the complete autonomous functionality.

Hardware Design

The Geo controller is interfaced to both the GPS module and the compass modules. Both these modules are powered using stable 3.3V inputs which are derived from the SJ Two boards. The GPS communicates with the board via UART and is connected to the controller at the P4.28 and P4.29, Rx and TX pins respectively. The GPS requires an antenna which is interfaced to the module via a UFL to SMA connector. Though the GPS module houses an led to indicate FIX on GPS lock, the led3 of SJTwo board was used to also show lock acquired after GPS string was received. The compass module communicates with the board via I2C and is connected at P0.10 SDA and P0.11 SCL pins respectively. As part of the hardware design, the compass module was mounted on a separate long pole, away from other interferences. The led1 of SJTwo board was used to indicate a successful comapss read.

Compass module

GPS module

<Layout pic>

Software Design

The GPS module provides data in the form of NMEA strings. NMEA (National Marine Electronics Association) is a standard protocol used by GPS receivers to transmit data. These strings contain various pieces of information, such as latitude, longitude, altitude, and time. The data bytes sent from the GPS module through UART are first loaded into a line buffer. The algorithm then parses this buffer to capture the specific $GPGGA strings that includes the correct position, time, and fix status.

$GPGGA string parameters

Following is the GPS string parsing logic where the lattitude and longitude are retrieved:

static gps_coordinates_t gps_string_to_coordinates(char gps_line[line_buffer_size]) {
  gps_coordinates_t coordinates = {0, 0};
  char gps_line_copy[line_buffer_size];
  strcpy(gps_line_copy, gps_line);
  char *token = strtok(gps_line_copy, ",");
  int token_count = 0;
  char *tokens[6];
  while (token != NULL && token_count < 7) {
    if (token_count == 2 || token_count == 3 || token_count == 4 || token_count == 5 || token_count == 6) {
      tokens[token_count - 2] = token;
    }
    token = strtok(NULL, ",");
    token_count++;
  }

  // Check GPS Quality indicator value != 0 to see if FIX acquired
  if (strtof(tokens[4], NULL)) {
    GPS_fix_acquired = true;

    coordinates.latitude = strtof(tokens[0], NULL);
    char *latitude_dir = tokens[1];
    coordinates.longitude = strtof(tokens[2], NULL);
    char *longitude_dir = tokens[3];
    if (*latitude_dir == 'S')
      coordinates.latitude *= -1;
    if (*longitude_dir == 'W') {
      coordinates.longitude *= -1;
    }
  }
  return coordinates;
}

The compass module required calibration to provide accurate results. This was accomplished using MotionCal software, interfaced with an Arduino. After determining the hard and soft iron offsets, these values were applied in the code to perform software-based compass calibration. The compass heading relative to true north was then calculated based on the mounting direction. Proper register configuration was necessary to initialize the module and read the compass readings accurately.

Compass calibration

Following are the compass register settings for proper initialization. They are derived as per the instructions described in the LSM303AGR datasheet.

void compass__init() {
  i2c__initialize(current_i2c, i2c_baudrate_hz, clock__get_peripheral_clock_hz(), &binary_semaphore_struct,
                  &mutex_struct);
  uint8_t ctrl_reg1_value = 0x8C;
  uint8_t ctrl_reg2_value = 0x02;
  uint8_t ctrl_reg3_value = 0x10;
  i2c__write_single(current_i2c, magnetometer_write, MAGNETOMETER_CTRL_REG1, ctrl_reg1_value);
  i2c__write_single(current_i2c, magnetometer_write, MAGNETOMETER_CTRL_REG2, ctrl_reg2_value);
  i2c__write_single(current_i2c, magnetometer_write, MAGNETOMETER_CTRL_REG3, ctrl_reg3_value);
}

Checkpoint Algorithm

The checkpoint algorithm finds the nearest checkpoint coordinate based on the current location among a series of checkpoints, considering also the distance to destination coordinates. Initially, it calculates the distance between the current location and the destination. Then, it iterates through each checkpoint, finding the distance from the current location to the checkpoint and from the checkpoint to the destination. If both distances are less than the minimum distance to the destination found so far, it updates the minimum distance and sets the next checkpoint accordingly. Finally, it returns the coordinates of the closest checkpoint considering the destination. This ensures proper navigation by selecting the most relevant checkpoint.

gps_coordinates_t find_closest_checkpoint_coordinate(gps_coordinates_t current_coordinate,
                                                     gps_coordinates_t destination_coordinate) {
  float min_distance_to_destination =
      coordinates__get_distance_to_destination(current_coordinate.latitude, current_coordinate.longitude,
                                               destination_coordinate.latitude, destination_coordinate.longitude);
  gps_coordinates_t next_checkpoint = destination_coordinate;

  for (uint8_t index = 0; index < max_checkpoints; index++) {
    float distance_to_waypoint =
        coordinates__get_distance_to_destination(current_coordinate.latitude, current_coordinate.longitude,
                                                 checkpoints[index].latitude, checkpoints[index].longitude);
    float distance_from_waypoint_to_destination =
        coordinates__get_distance_to_destination(checkpoints[index].latitude, checkpoints[index].longitude,
                                                 destination_coordinate.latitude, destination_coordinate.longitude);

    if (distance_to_waypoint < min_distance_to_destination &&
        distance_from_waypoint_to_destination < min_distance_to_destination) {
      min_distance_to_destination = distance_to_waypoint;
      next_checkpoint = checkpoints[index];
    }
  }
  return next_checkpoint;
}

Selected checkpoints at SJSU North Garage

The following checkpoints were added to the checkpoint structure for the final demo, by manually verifying the coordinates using Google maps. The exact locations are difficult to derive, so coordinates away from the edges were chosen. Else these coordinates may appear to be beyond the building edges as per the GPS module on the RC car. The destination was set to the edge of the building and sent to the GEO module via CAN from the bridge controller.

Technical Challenges

As the geo logic came as the final step in the project, it could only be tested thoroughly after all other modules performed reliably. Several issues were identified and resolved on the geo controller side:

• Problem: The compass was giving unreliable values and not pointing to true north.
  • Solution: The compass needed to be calibrated for the environment in which it was used, especially with the motor running.

• Problem: The compass was giving a fixed range of values 170-250 dgrees, instead of the full 0-359 range, despite repeated calibrations.
  • Solution: The register configurations had to be updated. Specifically, the block data update needed to be set, and offset cancellation had to be enabled.

• Problem: The GPS was giving no parsed outputs.
  • Solution: The issue was traced back to soldering errors. The TX and RX wires were not swapped correctly; the TX of the board needed to connect to the RX of the GPS module, and vice versa.

• Problem: GPS was not acquiring stable lock inspite of testing it in open space and having the antenna connected.
  • Solution: A button cell was added to the GPS module in the slot (rear side) provided in the module which enabled it to acquire locks faster.

• Problem: GPS parsing was incorrect and not returning proper data. Sometimes the buffer returned unknown symbols and empty results.
  • Solution: The line buffer size was increased to ensure all the received bytes were added to the buffer before the line removal function had to be called. It was alse ensured that a lock was obtained before reading any data for uupdating coordinates.

Driver Node

Gitlab Link: https://gitlab.com/jincyjose491/sjtwo-c/-/tree/master/projects/driver?ref_type=heads

LCD Display

Hardware Design

Driver node gives the interconnection between input and output. It receives input from geo node and sensor node and give commands to the motor node. The only hardware driver has is the LCD display and CAN transceiver. The LCD display used is a SunFounder IIC I2C TWI Serial 2004 20x4 LCD Module and is interfaced through an I2C bus through the I2C2 port. The module used and pin connections for LCD is shown below.

LCD Display

Software Design

Driver has more software and less hardware. For navigation, there are two algorithms - obstacle avoidance and GPS navigation. Obstacle avoidance has precedence over GPS navigation. In case of any obstacle, car avoids obstacle. In other cases, it follows the path from geo node input. When the destination is reached, car slows down and stops.

Different debug signals were added to check the logic when car was working. This helped in corrected undesired behavior of car taking turns without obstacle, stopping without reason, etc. The debug values used and their indications are shown in below table.

Obstacle Avoidance

The obstacle avoidance code is written in the form of a truth table that has 4 bit input and one bit output. Inputs are four sensor values and output the motor commands. Bases on changes in sensor values, the motor command also changes. The logic that worked for us is given below

GPS Navigation

For GPS navigation the angle difference between heading and bearing is calculated and motor turn commands are generated based on this. Heading gives the current position in angle with respect to north. Bearing gives the angle to destination with respect to north. The logic that worked for our hardware is given below:

Technical Challenges

Since driver comes as the interconnect between all other nodes, the driver logic could be verified by outside testing only when we had stable input from geo and sensor node and motor nodes working as expected for given PWM. Unit testing can help in building of logic. But for actual test, we have to make sure all inputs are reliable. This can be verified with debug messages on bluetooth, CAN messages on busmaster, LCD display or LED indicators. The verification or debugging should be done in same frequency as which driver is processing.

• Problem: LCD was not displaying anything.
  • Solution: Initially tried with 3.3V supply, then 5V supply and finally added level shifter to I2C pins. But the issue was slave address given in the datasheet was wrong. I got the correct slave address from web serial. After this was corrected, LCD worked well with 3.3V.

• Problem: LCD flickered a lot when everything was connected together.
  • Solution: We initially connected all 5V supplies to a single 5V source. This included servo motor also. And it was causing the flicker. So, we powered up servo and rpm from ESC, all other sensors were powered separately from power bank and the issue was solved. This problem could have been avoided if more reports were read on how to power everything up.

• Problem: Driver gave a reverse signal for one clock cycle when there was no obstacle.
  • Solution: Sensors gave random value for just one clock cycle and this caused driver to generate reverse command. After sensor inputs were corrected and made stable, the problem was solved.

• Problem: Driver not able to correct turning commands to motor even after sensing obstacle on side. This happened in the clock cycle when there was obstacle on all three side and it took reverse.
  • Solution: We gave steps in angle changes in size of 5. Instead of direct 45 degree turn, car always turned in steps. So even though it sensed obstacle step sized turn angles took long clock cycles. So I finally reverted back to simple code logic of 45 degree turn and obstacle avoidance started working perfectly.

• Problem: We thought driver was giving wrong commands to sensor values that was there on app.
  • Solution: Sensor values were updated at 1 Hz. Driver was working at 10Hz which is 10 times faster than what we see on app. So incorrect sensor value for just one cycle was not displayed. Finally debugged it in a hard way from all debugging sources listed above.

Communication Bridge Controller

• GitLab Link :Bridge Controller
  

The bridge controller aims to communicate with the Android application, receiving GPS coordinates to initiate vehicle movement and essential debug information for field testing. The user selects the final destination on Google Maps via the Android application, directing the car to navigate to the specified location.

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

• Make sure you have a clear idea on how to power up every modules in the project. This require careful distribution of power across the boards, sensors, motors. Connect everything together in the initial stage to see if entire module can work well when connected together. Doing this at an early stage helps to understand how to correctly power up everything. Again, you'll get an idea on which all modules should/should not be connected together, which module require additional power source, etc. from previous reports. Most of your problems could be solved from previous year reports. Don't limit yourself to 2-3 reports. Read more.. It'll be useful.

• Try to interface everything and see if communication is reliable between the nodes. Do this early so that you can work on project requirements.

• Find out your motor PWM for forward, neutral and reverse as soon as you get the car. You can save time here.

• Simplify the wire connections to save time when you meet. When we met in the initial few weeks, most of the time was spent on connecting everything from scratch and figuring out why something is not working.

• Get good quality hardware so that you don't have to invest more time here.

Acknowledgement

We would like to thank our instructor, Preet, for all his efforts in our class and all motivation and guidance lifelong. We have learnt so much about unit testing, C coding, software-hardware integration, team work, git and documentation, all because of Preet.

We also have to acknowledge all the teams who came before us, their reports helped us a lot.

References