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DIY hobby servos quadruped robot

Cheap 3D printed 4 legged robot, that almost looks like boston dynamics spot but moves like a newborn.

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Being a undergradute in physics and bored of solving paper problems, i decided to solve and apply a real world problems so i started this robotics project in order to introduce my self to control theory, studying its maths and practicing pragramming.
It runs with Raspberry Pi 4 as brain, plus an Arduino Mega for reading/writing of signals of 12 hobby servos and IMU, controlled by a PS3 Dualshock.


General Summary

The code which is mostly written by me, using python3 along with some typical libraries for the task, for now implements a walking loop inside a kinematic model, so you can command a pose to the body, as well as feet position and also velocity and directinal commands for the walking loop. Controlled by a ps3 controller via bluetooth.

Arduino is used for speed up the reading and writing of signals, so in the future i can add other sensor, as well as position feedback... This communication is made via bidirectional Serial Commands, so servo pulses are sent to the arduino and angles on IMU are recived on the Raspberry Pi.

As soon as you see the project, you will notice i'm not using Raspberry Pi, thats becouse as i don't have batteries for now (This will be finished in the following updates), its more comfortable for me to work on the PC, on Raspberry Pi it would work the same.

Last run of the robot:

Code of the robot


Project log index (updated):

  1. Model and code explanation.
    1. The kinematic model.
    2. Step trajectory and Gait planner.
    3. Arduino code.
    4. Raspberry Pi communication interfaces.
    5. Calibrating the servos.
  2. Robot experiments.
    1. A simple walking method.
    2. Real robot vs PyBullet simulation.
    3. Hitting the robot.
    4. Quadruped robot meets my cat.
    5. A more stable walking.

Why building a quadruped robot?

Appart from the interesting control problems that this robot involves, there are lot of interesting tasks this it can carry out and they are beginning to be demonstrated, as we have seen with Spot robot in the 2020 pandemic:

It's obious that there is still lot of work to do, but we are at the time where we can built one of these in our homes and have a very good aproximation of it.

There is a key factor in this robot, it doesn't need roads in orther to operate, so it can reach places that are very hard for a wheeled machine, so these 4-legged robot are ideal for tasks such as surveillance, recognition of areas not passable by vehicles and even rescues in areas with danger of collapse.

Finally, it is clear for now, that my robot isn't able to do those tasks, but for now i am satisfied that the robot wolks stable and who knows if in the future it will be able to bring me a beer from the fridge, just by telling to it: 'dog bring me a beer!'

What problems will you face with this robot?

These legged robot have always amazed me, but it was hard to find easy to understand research, as well as a non-trivial mecanical designs plus complex maths. This makes the project hard to achive good results with DIY resources. So i rolled up my slevees and started reading papers from different investigation groups in the subject.

What my project apport to the maker community?

As this project is multidiciplinary, appart from designing my own version of the robot, i focused on its maths, solving different problems related with the movement of the robot, making a very looking forward model which only implements the maths necessary to run the robot, showing how every equation is related with the real robot and givin a general view of it.

This is not the most robust way of building a model, as in real world robots there are lot of additional maths methods in order to pulish the behaviour of the robot, for example, adding interpolation methods would make the robot performs smoother or building an state stimator + filter (kalman state stimator) would let you do very preccise meassurements on the robot and make its movements even more natural.

Visual scheme of electronics and model.

As you can see in the scheme, in this setup i use one bulk converter por 3 servos, with 4 bulk converters in total. This is because each servo drains up to 4A peak.

NOTE: This would not be a rigorous way of wiring, it is just a drawing.

Licensing

This project uses the GPL v3 license for all software related.

This project uses the Attribution-NonCommercial-ShareAlike 4.0 International for all hardware components.

Robot...

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  • 12 × Servo DS3218 PRO version. 20 kg/cm torque and 0.1 s/60º.
  • 12 × Metal horns for the servos. Plastic one are not a choose, as they generate play.
  • 3 × 2x 18650 battery holders in serie (7,4 V)
  • 20 × 8x3x4 mm bearings (autter x inner x width)
  • 1 × MPU6050 IMU. accelerometer + gyrocope.

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  • Calibrating the servos.

    Miguel Ayuso Parrilla08/01/2020 at 09:15 0 comments

    First of all, you will need to plug all servos to their proper pin, in my case here they are (you can change this for your how setup):

    void connectServos() {
                          //FR
      Servos[0].attach(40); //coxa
      Servos[1].attach(38); //femur
      Servos[2].attach(36); //tibia
                          //FL
      Servos[3].attach(42); //coxa
      Servos[4].attach(44); //femur
      Servos[5].attach(46); //tibia
                         //BR
      Servos[6].attach(34); //coxa
      Servos[7].attach(32); //femur
      Servos[8].attach(30); //tibia
                         //BL
      Servos[9].attach(48); //coxa
      Servos[10].attach(50); //femur
      Servos[11].attach(52); //tibia
    }

    As soon as the servos are corretly attached, what i made in order to put the servos on its correct position is just to dissasembly the legs, i mean, separate the servo output from the its horn, in order to let the servo move freely. This way you can power the servos, let them go to the zero position and the reassembly.

    I wrote a small sketch in order to put the servos on their zero position, you can find it at servo_calibration.py file, this way you can attatch the servo very close to their zero position.

    Then, a more precise calibration is needed, you will need to calibrate the offset of each servo, those offset are defined at angleToPulse.py file. This file only contains the line defining the pulse corresponding to each angle for every servo.

    Being a line in the form: y = Ax + B. The offset of each servo is defined by B, which mean the pulse at the zero angle.

    If you are using different servos, the slope of the line (A) will be different so you will need to identify it. What i did, is just to take 4-5 meassurement of pulse at different angles and put them on an excel where i calculate the adjucted line from those points.

    def convert(FR_angles, FL_angles, BR_angles, BL_angles):
        pulse = np.empty([12])
        #FR
        pulse[0] = int(-10.822 * np.rad2deg(-FR_angles[0])) + 950
        pulse[1] = int(-10.822 * np.rad2deg(FR_angles[1])) + 2280
        pulse[2] = int(10.822 * (np.rad2deg(FR_angles[2]) + 90)) + 1000
        #FL
        pulse[3] = int(10.822 * np.rad2deg(FL_angles[0])) + 1020 
        pulse[4] = int(10.822 * np.rad2deg(FL_angles[1])) + 570
        pulse[5] = int(-10.822 * (np.rad2deg(FL_angles[2]) + 90)) + 1150
        #BR
        pulse[6] = int(10.822 * np.rad2deg(-BR_angles[0])) + 1060 
        pulse[7] = int(-10.822 * np.rad2deg(BR_angles[1])) + 2335 
        pulse[8] = int(10.822 * (np.rad2deg(BR_angles[2]) + 90)) + 1200
        #BL
        pulse[9] = int(-10.822 * np.rad2deg(BL_angles[0])) + 890
        pulse[10] = int(10.822 * np.rad2deg(BL_angles[1])) + 710
        pulse[11] = int(-10.822 * (np.rad2deg(BL_angles[2]) + 90)) + 1050
        return pulse

  • A more stable walking.

    Miguel Ayuso Parrilla07/20/2020 at 11:49 0 comments

    This log is about polishing the gaitPlanner as you can see in the next video:


    What is interesting on this video is that no control algorithm is running, but it seems very stable.

    This is achived just by separating stance phase from the swing (as explained in the gaitPlanner.py log), this way i can define an offset between both phases, so running the stance phase at 3/4 of the hole step, makes the robot to hold its weigth on the 4 legs for a short period of time being a bit more stable, just by running the gaitPlanner loop.
    Visually the gait is defined like follows:

    Aditional info about that is that servos got very hot if it runs for more than 10 minutes.

  • Quadruped robot meets my cat.

    Miguel Ayuso Parrilla07/07/2020 at 18:29 0 comments

    As a quick update of the V2 robot performing i have introduced it to my cat.

    My cat is very introverted and usually doesn't like new things, in this case isn't different but it seems to cause she some curiosity.

    The robot performs well, as it uses the last version of the code, the extra weigth of the batteries and raspberry pi is not a problem as the new design is much more lighter and the servos are now powered at 6V in stead of 5V as in the first version.

    On the other hand, i have notice the model randomly gives bad solutions running on the raspberry pi, thats why sometimes you see the leg make a strange movement. I haven't identify the problem yet, maybe is my software problem or bufer overflow.

    There is no aim to hurt the animal, is my cat omg.

  • Real robot vs PyBullet simulation.

    Miguel Ayuso Parrilla06/26/2020 at 14:45 0 comments

    In this video i compare the real robot model with the simulation model:

    I'm using PyBullet physics engine, it is simple to use and seems to have a good performance as well as very precise results. In the video you can see that the simulation is a bit slow, this is becouse the simulation (at the time of the video) was not working at real time but computing the simulation every 20 ms.

  • Raspberry Pi communication interfaces.

    Miguel Ayuso Parrilla06/21/2020 at 21:41 0 comments

    This log is going to be about the python communication files, explaining the interfaces used in order to communicate both with the ps3 controller and with the arduino.

    Serial Bidirectional Communication on python.

    This is written in the serial_com.py file and the code goes as follow:

    • First thing is to define the serial port and its baudrate.
    import serial
    
    class ArduinoSerial: 
        def __init__(self , port):
            #ls -l /dev | grep ACM to identify serial port of the arduino
            self.arduino = serial.Serial(port, 500000, timeout = 1)
            self.arduino.setDTR(False) #force an arduino reset
            time.sleep(1)
            self.arduino.flushInput()
            self.arduino.setDTR(True)
    • Then the communication is done with the next two fuctions. This fuctions are very general and can be used without big chnges.

      This program will stop the main loop until the next data arrives, this way the arudino memory is not overloaded with the pulse commands arriving.

    def serialSend(self, pulse):  
            comando = "<{0}#{1}#{2}#{3}#{4}#{5}#{6}#{7}#{8}#{9}#{10}#{11}>" #Input
            command=comando.format(int(pulse[0]), int(pulse[1]), int(pulse[2]), 
                                       int(pulse[3]), int(pulse[4]), int(pulse[5]), 
                                       int(pulse[6]), int(pulse[7]), int(pulse[8]), 
                                       int(pulse[9]), int(pulse[10]), int(pulse[11]))
            self.arduino.write(bytes(command , encoding='utf8'))
    
        def serialRecive(self):
            try:
                startMarker = 60
                endMarker = 62
                getSerialValue = bytes()
                x = "z" # any value that is not an end- or startMarker
                byteCount = -1 # to allow for the fact that the last increment will be one too many
                # wait for the start character
                while  ord(x) != startMarker: 
                    x = self.arduino.read()
                    # save data until the end marker is found
                while ord(x) != endMarker:
                    if ord(x) != startMarker:
                        getSerialValue = getSerialValue + x 
                        byteCount += 1
                    x = self.arduino.read()
                loopTime , Xacc , Yacc , roll , pitch  = numpy.fromstring(getSerialValue.decode('ascii', errors='replace'), sep = '#' )  
    


    Connecting PS3 controller to the Raspberry Pi and reading its events.

    • Then events are read on the joystick.py file, using evdev python library. In this set up, the events are read every time the read() function is called, ignoring the others ongoing events. Also there isn't any queue method or filtering.
    from evdev import InputDevice, categorize, ecodes
    from select import select
    import numpy as np
    
    class Joystick:
        def __init__(self , event):
            #python3 /usr/local/lib/python3.8/dist-packages/evdev/evtest.py for identify event
            self.gamepad = InputDevice(event)
    
        def read(self):
            r,w,x = select([self.gamepad.fd], [], [], 0.)
            if r:
                for event in self.gamepad.read():
                    if event.type == ecodes.EV_KEY:
                        if event.value == 1:
                            if event.code == 544:#up arrow
                                self.T += 0.05
                            if event.code == 545:#down arrow
                                self.T -= 0.05
                            if event.code == 308:#square
                                if self.compliantMode == True:
                                    self.compliantMode = False
                                elif self.compliantMode == False:
                                    self.compliantMode = True    
                        else:
                            print("boton soltado")
    
                    elif event.type == ecodes.EV_ABS:
                        absevent = categorize(event)
                        if ecodes.bytype[absevent.event.type][absevent.event.code] == "ABS_X":  
                            self.L3[0]=absevent.event.value-127
                        elif ecodes.bytype[absevent.event.type][absevent.event.code] == "ABS_Y":
                            self.L3[1]=absevent.event.value-127
                        elif ecodes.bytype[absevent.event.type][absevent.event.code] == "ABS_RX":
                            self.R3[0]=absevent.event.value-127
                        elif ecodes.bytype[absevent.event.type][absevent.event.code] == "ABS_RY":
                            self.R3[1]=absevent.event.value-127
    

  • A simple walking method.

    Miguel Ayuso Parrilla06/15/2020 at 00:39 0 comments

    This experimet was the first one done on the robot, it consist on a very simple arduino sketch, implementing the IK equations and a simple creep gait loop with 4 points bezier curves.

    This only walks forward to the infinite, but is a useful example of the IK equations written on arduino language, here is the Arduino-quadruped-robot-loop repositorie from my github.

  • Role of Arduino and Serial Communication.

    Miguel Ayuso Parrilla06/12/2020 at 21:34 0 comments

    Working frequencies.

    Arduino is used as a pwm signal generator for the servos, so the main loop must run at the duty frequency of the servos (in my case 50Hz, 20ms loop). Of course, arduino is more powerful than that, so after sending a first pulse and before the next pulse is sent, arduino will read the different sensors, send their data and recive the next pulse command from the raspberry pi (via bidirectional serial commands).

    As the arduino loop is limited by the frequency of the servos, the main python code will also work at that frequency. As far as i know, this is because if the model gives a solution every 5ms and the actuators can only read a solution every 20ms, there will be 'useless' solutions given, resulting with the system not behaving as desired.

    Arduino sketch.

    The arduino code is very simple, but a bit long. Basically, it is composed by two files, main program: arduino_com.ino and the IMU functions: gy_521_send_serial.ino (Code by "Krodal"), this includes a low pass filter for the orientation. It works very well, without any fiffo problems but there is lot of drift on the yaw angle. Which is normal for these gyro+acc sensors.

    About the main code:

    void loop() {
      unsigned long currentMillis = millis();
        if (currentMillis - previousMillis >= interval) {
          previousMillis = currentMillis;
    
          readAngles();          
          recvWithStartEndMarkers();
          newData = false;
          moveServos(pulse0, pulse1, pulse2, pulse3, pulse4, pulse5, pulse6, pulse7, pulse8, pulse9, pulse10, pulse11);
      }
    }

     Is basically what i exaplined, it only works when 20ms has passed and then it reads the angles from IMU, read the incoming pulses via serial command, switch newData flag off and write the new pulses command.

    The pulses are given on microseconds, the translation of angles to microseconds is done in the python code.

    recvWithStartEndMarkers().

    How commands are read and then converted to an integer is made with this function, which is from: Serial Input Basics - updated.

    Here there is the example i used:

    // Example 3 - Receive with start- and end-markers
    
    const byte numChars = 32;
    char receivedChars[numChars];
    
    boolean newData = false;
    
    void setup() {
        Serial.begin(9600);
        Serial.println("<Arduino is ready>");
    }
    
    void loop() {
        recvWithStartEndMarkers();
        showNewData();
    }
    
    void recvWithStartEndMarkers() {
        static boolean recvInProgress = false;
        static byte ndx = 0;
        char startMarker = '<';
        char endMarker = '>';
        char rc;
     
        while (Serial.available() > 0 && newData == false) {
            rc = Serial.read();
    
            if (recvInProgress == true) {
                if (rc != endMarker) {
                    receivedChars[ndx] = rc;
                    ndx++;
                    if (ndx >= numChars) {
                        ndx = numChars - 1;
                    }
                }
                else {
                    receivedChars[ndx] = '\0'; // terminate the string
                    recvInProgress = false;
                    ndx = 0;
                    newData = true;
                }
            }
    
            else if (rc == startMarker) {
                recvInProgress = true;
            }
        }
    }

     What i have done is to add an spacer ('#') to differentiate each pulse and a counter, that is in charge of saving the numeric string to its correspoding integer pulse.

  • Hitting the robot.

    Miguel Ayuso Parrilla06/12/2020 at 11:30 0 comments

    I manage to make the robot a bit compliant by reading acceleration meassurements on the IMU, when a big acceleration is showed, a velocity command (in direction of the perturbance) is hold in order to soften that disturbance.

    In the video the model is reading raw acceleration data, thats why sometimes its has random movements.

  • Step Trajectory and Gait Planner (from MIT cheetah)

    Miguel Ayuso Parrilla05/31/2020 at 13:17 0 comments

    As in the kinematic_model.py you can change the foot position, you can make a time varying system by changing the feet position describing a bezier curve.

    So building a parametric bezier curve (11 points for now) you can follow a closed step loop, i drew this curve on this bezier curve generator: https://www.desmos.com/calculator/xlpbe9bgll

    This can by written by an equation dependant of the N point and a parameter going from 0 to 1 in order to describe the trajectory.

    In the the gaitPlanner.py file is known as phi and the start-end point is [0,1). This parameter is important, because it tells you where the foot is located, these coordinates are defined in the foot frame.

    The equations are based on the paper Leg Trajectory Planning for Quadruped Robots with High-Speed Trot Gait from the MIT cheetah robot (equations 11-23-24-TABLE II).

    But in my case, i chose similar points but with 10 points (removing P6 and P4) and i'm just multiplying all points by a velocity command in order to make the trajectory wider. This way i have a very simple solution to the stance and swing controller.

                                                                      Trajectory of step at different speeds

    Also for every loop, the swing and stance loops are running, each from 0 to 1, first stance phase then swing, with an offset between them which, if it is set at 0.5, both phases last the same. In another case, for creep gait, this offset must be set at 0.75, meaning that stance phase will last 3/4 of the step.

    The code for each leg goes as follow, where most of the code is just to define the signs of vectors needed for the rotation steps as this is defines inside cylindrical coordinates.

    def stepTrajectory(self , phi , V , angle , Wrot , centerToFoot): #phi belong [0,1), angles in degrees
            if (phi >= 1):
                phi = phi - 1.
    
    
    #step describes a circuference in order to rotate,
    #makes the step plane to be inside a circunference. 
            r = np.sqrt(centerToFoot[0]**2 + centerToFoot[1]**2) #radius of the ciscunscribed circle
            footAngle = np.arctan2(centerToFoot[1],centerToFoot[0]) 
            
            if Wrot >= 0.:#As it is defined inside cylindrical coordinates, when Wrot < 0, this is the same as rotate it 180ª
                circleTrayectory = 90. - np.rad2deg(footAngle - self.alpha)
            else:
                circleTrayectory = 270. - np.rad2deg(footAngle - self.alpha)
            
    
    #then calculate the coordinates to follow the step trajectory
    #for both ongitudinal and rotational steps.
    #Here is where the offset between STANCE and SWING is defined. 
            stepOffset = 0.5
            if phi <= stepOffset: #stance phase
                phiStance = phi/stepOffset
                stepX_long , stepY_long , stepZ_long = self.calculateStance(phiStance , V , angle)#longitudinal step
                stepX_rot , stepY_rot , stepZ_rot = self.calculateStance(phiStance , Wrot , circleTrayectory)#rotational step
    
            else: #swing phase
                phiSwing = (phi-stepOffset)/(1-stepOffset)
                stepX_long , stepY_long , stepZ_long = self.calculateBezier_swing(phiSwing , V , angle)#longitudinal step
                stepX_rot , stepY_rot , stepZ_rot = self.calculateBezier_swing(phiSwing , Wrot , circleTrayectory)#rotational step
    
    
    #define the sign of every cuadrant, angle at which the foot is located,
    #which is saved in order to know the last position of the rotational step.
            if (centerToFoot[1] > 0): 
                if (stepX_rot < 0):
                    self.alpha = -np.arctan2(np.sqrt(stepX_rot**2 + stepY_rot**2) , r)
                else:
                    self.alpha = np.arctan2(np.sqrt(stepX_rot**2 + stepY_rot**2) , r)   
            else:
                if (stepX_rot < 0):
                    self.alpha = np.arctan2(np.sqrt(stepX_rot**2 + stepY_rot**2) , r)
                else:
                    self.alpha = -np.arctan2(np.sqrt(stepX_rot**2 + stepY_rot**2) , r)   
    
            coord = np.empty...
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  • Lets talk about the kinematic model.

    Miguel Ayuso Parrilla05/14/2020 at 12:10 0 comments

    In this first log i'm going to explain how the kinematic model works.

    First thing to take into account is the robot geometry and its DOFs, to ilustrate this, in the next image you see where are they and how they transform. This model is very looking forward, in real robotics first is to make a robust state stimator so you can have smooth meassurements of robots states.

    NOTE: All vector are defined inside the robot frame, no world frame is used for now.

    So, we have 4 frames on each leg and one which is commun for all, which is the geometric center of the robot (very close to the CoM).

    For our setup, there are 2 important frames on the leg, which are the frame0 (coxa frame or first frame on the leg) and frame4 (foot frame or last frame on the leg).

    So now, we are going to calculate Inverse Kinematics between those frames. If you want more information on how to calculate IK you can read this article: https://www.researchgate.net/publication/320307716_Inverse_Kinematic_Analysis_Of_A_Quadruped_Robot

    As u can see the setup is a bit diferent, but it only change the simetry of the legs, so the analytic function is the same.

    Inverse Kinematics are solved on the IK_solver.py file, which is basically two functions, one for right legs and the other for the left legs. These functions works as shown:

    And the code goes as follow:

    def solve_R(coord , coxa , femur , tibia): 
        D = (coord[1]**2+(-coord[2])**2-coxa**2+(-coord[0])**2-femur**2-tibia**2)/(2*tibia*femur)  
        D = checkdomain(D) #This is just to deal with NaN solutions
        gamma = numpy.arctan2(-numpy.sqrt(1-D**2),D)
        tetta = -numpy.arctan2(coord[2],coord[1])-numpy.arctan2(numpy.sqrt(coord[1]**2+(-coord[2])**2-coxa**2),-coxa)
        alpha = numpy.arctan2(-coord[0],numpy.sqrt(coord[1]**2+(-coord[2])**2-coxa**2))-numpy.arctan2(tibia*numpy.sin(gamma),femur+tibia*numpy.cos(gamma))
        angles = numpy.array([-tetta, alpha, gamma])
        return angles
    

     Now, we can locate foot in the 3D space, inside the frame0.

    Next step is to move the body frame in relation with the feet. Which is essentialy the kinematic model i built, kinematic_model.py file in the code.

    For this, we need to define 3 vectors, the first is a 'constant' vector, which is the vector from the center to the frame0 or coxa frame, this vector is going to be rotated and translated with the desired body position.

    The next is the vector from body frame to frame4 or foot frame, this vector is where we want the foot to stay.

    With this two vector we can calculate the IK vector needed for the inverse kinematics just by subtracting body to frame4 and body to frame0.

    Now, we want the body to rotate on its 3 dofs and its 3 logitudinal movements, for this, we just multiply the body to frame0 vector by the rototranslation matrix.

    You can see how this woks on the geometrics.py file, where the fuctions for the rototranslations are defined. Here there is a figure to ilustrate the rotation of the body with respect to the feet in the pitch rotation:

    As the the principal frame is transformed, all other child frames are also transformed,  so in order to keep feet still, we need to undo the fransformation for the frame0 to frame4 vector (IK vector) before IK are solved.

    Here is the code solving that:

        def solve(self, orn , pos , bodytoFeet):
            bodytoFR4 = np.asarray([bodytoFeet[0,0],bodytoFeet[0,1],bodytoFeet[0,2]])
            bodytoFL4 = np.asarray([bodytoFeet[1,0],bodytoFeet[1,1],bodytoFeet[1,2]])
            bodytoBR4 = np.asarray([bodytoFeet[2,0],bodytoFeet[2,1],bodytoFeet[2,2]])
            bodytoBL4 = np.asarray([bodytoFeet[3,0],bodytoFeet[3,1],bodytoFeet[3,2]])
    
            """defines 4 vertices which rotates with the body"""
            _bodytoFR0 = geo.transform(self.bodytoFR0 , orn, pos)
            _bodytoFL0 = geo.transform(self.bodytoFL0 , orn, pos)
            _bodytoBR0 = geo.transform(self.bodytoBR0 , orn, pos)
            _bodytoBL0 = geo.transform(self.bodytoBL0 , orn, pos)
            """defines coxa_frame to foot_frame leg vector neccesary for IK"""
            FRcoord = bodytoFR4 - _bodytoFR0
     FLcoord...
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View all 10 project logs

  • 1
    Building premises.

    I'm going to enumerate some important concepts i have taken into account for the robot design.

    • This robots depends hardly on its mass distribution and dynamics of the moving parts (legs). Thats why i decided to go for this servo configuration, having the coxa servo on the body, the femur servo on the coxa and tibia servo on the the femur, so there is only 2 servos moving with the legs.
    • This way, the less leg weight the less unexpected inertia, causing a better dynamic behavior.
    • Also the robot weight should be as less as posible becouse hobby servos can be overcharged easily.
    • About the mass distribution, this would define the Center of Mass which should be the closest to the Geometric Center, for this the building must be as simetric as posible, this way CoM is easier to locate and the control would be more predictable.
    • The lenght of the leg is defined at 100 mm for both tibia a femur, this way, a motor with 20 Kg/cm will hold 2 kg at a 10 cm arm. So the longer the arm, the less force the motor can support.
    • Avoid plastic vs plastic joints, this would involve unnecessary friction forces.

    Printing premises.

    • This is simple but is important to take this into account, at the time of printing, these parts are not supporting much mechanical forces, for this and taking into account building premises, the 3D printed parts should be printed with ~10-20% infill , 1-2 outer perimeters and 2-3 solid layers.
  • 2
    Building and printing the robot.

    For building this i have made this tutorial, as there are some tricky parts.

    In the file section, each STL is named with the quantity of parts you need to print, if none just one needs to be printed.

    Also you can download files all at once at the file section, file STL_files.zip.

    Bolt list:

    • M3 x45 mm: quantity 12
    • M3 x30 mm: quantity 26
    • M3 x25 mm: quantity 16
    • M3 x20 mm: quantity 8
    • M3 x15 mm: quantity 16
    • M3 x7 mm: quantity 4
    • M3 threaded rod x 42 mm: quantity 4
    • M3 threaded rod x 74 mm: quantity 8

    Plus its respectives nuts and washers where is needed.

  • 3
    Electronics.

    Here is the electronics setup i have:

    You can download the full size PDF file of the scheme at the file section.

    As you can see, appart from the 4 power lines in order to power the servomotors, there is also a voltage divider in order to read the batterie voltage in the arduino from an analog pin and then 5 LEDs will indicate the batterie status. Finally, IMU is connected via I2C interface. Raspberry pi is powered via another bulk converter at 5V 3A, that i miss (i will correct this in the next updates) and arduino communicates via USB cable (which also power it) to raspberry pi.

    I made two modular small boards in order to easily connect and disconnect servos, these boards are conected to the big one, which will supply all the pins to the arduino, being the 12 pwm signals with its commun ground and the I2C interface for the IMU. Also here, i can add sensors (FRS) the same way for the future.

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Charan wrote 5 days ago point

Hi sir! I'm completely new to hardware and I'd like to learn how to build cool robots like these. 

Can you please cite some good resources (books/websites/videos/courses/hands-on learning projects or whatever you can think of) for kickstarting hardware hacking ?

Btw, here's a brief of my background

I'm a mech engg. undergrad and I  am familiar with a bit of Python and MATLAB. I can do CAD stuff well.

(I'm not sure if it's appropriate to ask this here, since it's unrelated to the project...I just thought maybe if there's someone else like me, they'll find this comment thread useful...)

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Miguel Ayuso Parrilla wrote 3 days ago point

Hi! Nice question, as there is lot of people asking me that and my advise is as simple as read. For that is important to know the level you are at so you can understand the reading.

It is truth that if you are a beginner, there is lot of videos at youtube that are very useful, but they are just introductions.

Now the question is, what to read? Personally i read lot of other people's projects, these are personal projects but now i'm also reading profesional projects or cientific researchments, where the information is trully tested and you can take the right solutions for what you are searching.

Also we can't forget to read code, because for learning coding we need to practice but at first stage we need to learn structures by reading.

About the resources, for now i can recommend you Ignite robots academy for learning ROS because it is what i'm using now. If you are interested on the resources i used for the robot, they are named along the explaining logs.

I'm sorry not to tell you specific resources, but there are tones of them on internet and along you read projects you will find the resources used.

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Charan wrote 2 days ago point

Thanks a lot for your suggestion!

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OilSpigot wrote 5 days ago point

I made some robot shoes out of foam and rubber that have greatly improved traction on wood floors. I'll test them out on a couple other surfaces this week. Let me know if you want a pair and I can mail them to you as a thanks for putting out all this great info.

https://www.youtube.com/watch?v=KT2_h3yJYxA&feature=youtu.be

I have some comments for the code: 

In robot_main_RPI.py, T is defined as the step period, but it is redefined in src/joystick.py that overwrites the value. So if you want to change T you have to do it in joystick.py

If I change height will this have the effect of raising the robot up 4 cm?

Xdist = 0.25

height = 0.16 #increase to 0.20

#body frame to foot frame vector (0.08/-0.11 , -0.07 , -height)

Also, I may want to experiment with changing the bezier curve. Do I just change these values in gaitPlanner.py with help from https://www.desmos.com/calculator/xlpbe9bgll?

X = np.abs(V)*c*np.array([-0.05 ,-0.06 ,-0.07 , -0.07 ,0. ,0. , 0.07 ,0.07 ,.06 ,0.05 ])

Y = np.abs(V)*s*np.array([ 0.05 ,0.06 ,.07 , 0.07 ,0. ,-0. , -0.07 ,0.07 ,-0.06 ,-0.05 ])

Z = np.abs(V)*np.array([0. ,0. ,0.05 , 0.05 ,.05 ,0.06 , 0.06 ,0.06 ,0. ,0. ])

I changed some of the values and it caused the program to crash, so i'm wondering if I did something like assign the leg to an out of bounds position. Might be nice to have a way to round out of bounds coordinate values to the nearest in-bounds point.

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Miguel Ayuso Parrilla wrote 3 days ago point

Hi man! As you asking very in deep question, we can told easier at the public chat of the project, this way we don't overflow the comments section.

Nice shoes man, but i have redesigned them for having more grip but maybe a solution like that will be needed as TPU isn't as grippy as gum.

The code: yes T is redefined, this is just to show that T must be defined but the one that is used is at joystick.py, i'll write a log showing the bottons used and what they do, as T can by changed with right-left arrows.

You are right with redifining the heigh, as those dimentions are the definition of initial position of CenterToFoot vectors, be careful as 20cm in some cases is not reacheable, you can see in the console when one position of IK is out of blounds it prints __OUT OF DOMAIN__ (this means there is a NaN solution at the IKs and last real solution is used), so you can try the limits empirically.

About the gait trajectory i don't really recommend you changing it as you can see in the olders code versions, the best i have tried is the MIT one, anyway, yes there is where the bezier points are defined, you can see the drawing at that page.

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OilSpigot wrote 08/02/2020 at 06:01 point

Can you give me some pointers on if I did the calibration correctly? It tends to fall forward over its front legs when I walk forward or backwards.

https://www.youtube.com/watch?v=h2wGVGGim3o

Thank you for putting this page together, I have learned a ton so far.

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Miguel Ayuso Parrilla wrote 08/02/2020 at 10:17 point

It seems the calibrarion is good but now you have to precisly calibrate it, what version of code are you running? I always recommend to run my last code version at github as it would be the most stable one. Are you running it on raspberry pi? Check last log and the calibration file, what i did for precise calibration, with a bubble level and putting the joints at zero position, difine each offset at the angleToPulse.py. On the calibration file you can also define other angles in order to check of the calibration is correct. Here, for going a bit faster i was adding a variable to the offset, adding +-10 microseconds each time click a botton on the joystick controller, finally printing the new offset. I'll explain this in details in some days with more visual explanatios of the calibrarion.

About the video, it seems really nice but there are some power supply problems, at some times there is a tibia that is not even powered.

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RileyWilliam83 wrote 07/30/2020 at 05:28 point

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OilSpigot wrote 07/24/2020 at 17:33 point

Finished printing most of the parts and i'm now moving on to electronics.

https://hackaday.io/project/173974/gallery#5505dbf9dcb2f21484781965f23c5154

Why do you use 4x Bulk converter boards? They can do 12A each, which should be enough to power the robot using 1.

Could I use some 500F ultracapacitors to buffer the output instead?

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Miguel Ayuso Parrilla wrote 07/25/2020 at 08:11 point

Wow!! That's really nice man!! During the next weeks i'm upgrading the tibia as background renders suggest. You will notice, the actual tibia setup makes the redirect forces to a weak point at the femur.

About the power comsution, i have calculated 3Amps peak for each servo thats why i have chosen 4 of them, also i will upgrade to bigger servos. Maybe 2 of them would be enough but i but this just to be sure it is safe.

About the supercapacitors, can't tell you, i haven't experimented with those.

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Dan10110 wrote 07/26/2020 at 02:55 point

I am glad to hear the improvement. Right now, there aren't a lot of material around the hole at the femur. I will be waiting for it. Thanks

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OilSpigot wrote 08/01/2020 at 01:24 point

I got all 12 servos plugged in and the RPI script running and responding to joystick inputs. It looks pretty funny right now, the arms are flailing in all different directions.

https://www.youtube.com/watch?v=8ugPX-Q6lbI

Can you make a diagram that shows which servo goes to which pin? I will need to do some calibrations, but its looking great so far.

I am interested in redesigning the legs, but want to use the software and electronics as a starting point.

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OilSpigot wrote 08/01/2020 at 03:26 point

Just to follow up, I am using buck converter board to step the voltage down and it seems to be working. It is pushing about 10A to run all the motors, though there may be some cases where power draw goes above that amount.

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Miguel Ayuso Parrilla wrote 08/01/2020 at 09:02 point

Hi man! You are so close to make it walk, there are just some points left i haven't had the time to explain.

I'll make a log on how to mount and the pin setup of the servos. I'm doing it right now.

So when you have already the servos on its correct pins. As you are using same servos, calibration would be the same, but you will need you adjust your own offset (explained at the new log), also as this servos doesn't have any mecanical stop, for calibrating i dissasembled all legs, then turn on the robot, so all servos goes to its position and then assembly the legs at their correct position. Maybe not the fastest way but worked really well for me. I'll share also the calibration script i used in order to put the servos to their zero angle.

About your powering... 10A wont be enough for walking, maybe 20/30A would be ok and for fast walking i recommend to go for the 48A setup. If servos doesn't have the power they need they can burn.

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pjgrommit wrote 07/22/2020 at 20:51 point

Nice project.  I have built a spotmicro but there is no software.  Been looking at Stanfords pupper, but I like the idea of having an IMU.  Saw this the other day, reminded me of your bezier diagrams - https://youtu.be/FFS-2axFo1Y.  There's nothing new in the world. !

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Dan10110 wrote 07/23/2020 at 04:44 point

Hi, I built the spotmirco too. It looks pretty nice and I got a lot of fun out of it. I got it walking using mike4192's SW from github. He has a very nice servo calibration procedure. I like Miquel's design because it reduces the weight and inertia issues. Spotmicro has all 3 servos in the leg and total weight of each leg including servos is about 300g(120+3x60). This causes some stability issue in motion unless you do a good job in static and dynamic balance. Pupper's design also addresses these issue but it is very expensive. I almost wanted to built it.

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Miguel Ayuso Parrilla wrote 07/23/2020 at 09:32 point

About the software, as i'm at beginer level at programming, maybe my code will be a bit hard to tune and my calibration is made just by the hard way. Anyway, the calibration is done just by aproximating it to a line (representing angle vs pulse) so you can just write a simple sketch on arduino in order to identify that line, taking some point with an angle ruler and saving that pulses and then put it on the angletoPulse.py file, if it is done properly everything should work. I'll work for it to make it easier for you to calibrate the servos.

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Miguel Ayuso Parrilla wrote 07/23/2020 at 09:21 point

Yeah maybe this gait is the more natural one, which as i have experimented this one is the most stable one.

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Dan10110 wrote 07/21/2020 at 02:45 point

Hi, I appreciate you took the time to share your great project. It is a lot of work. I like your division of HW between Arduino and RPi. It makes a lot of sense for division of works to optimize CPU usage and power. Your partition of SW makes it easy to follow. I am in the process of building it. I have printed the 3 femur parts and found the ridge on servo mounting tab interferes with the inner femur. There seems to be no indentation to receive the ridge. Am I missing something? Thanks again.

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Miguel Ayuso Parrilla wrote 07/21/2020 at 08:36 point

Thanks mate, this makes me so happy to know it is easy to follow along.

What servos are you using?

I did cut all the ridges from the servos with a cutter, sorry for that i forgot to notice that.

Also i want you to warn about the tibias, as i'm changing them, this change only affects to the tibia and the femur orientation, you can see it at the backgraund render. This change is because of how forces are distributed along the femur, so i need to flip the femur to solve that week point. Anyway this actual version works but there is a posibility of braking the femur.

Thanks for your comment and enjoy the build, feel free to ask what you need.

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Dan10110 wrote 07/21/2020 at 22:00 point

Thanks for the clarification. I will remove the servo ridge. I plan to use PDI-HV5523MG servos as I have them from another project. Since they are HV, I can connect them directly to battery.  I really like your light weight design of the robot. As you know, high torque servos are expansive. Will let you know how my build goes.

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Miguel Ayuso Parrilla wrote 07/21/2020 at 22:21 point

I reply here, as i can't reply your latest response.

About the servo ridge, if you won't cut them, you can just sand the 3d part with a small needle file.

Those servos are very nice, would be nice to try the design with diferent servos, hope there won't be dimension problems.

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Sergio Gugliandolo wrote 07/19/2020 at 22:15 point

What have you used to prevent over-discharging or things like that for your batteries? Isn't it dangerous to use them without protection circuit?

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Miguel Ayuso Parrilla wrote 07/19/2020 at 23:22 point

I chose quality batteries with quality protection circuit on each (SONY brand in my case) and appart from that i meassure the voltage in the arduino with a voltage divider and with 5 leds i display that meassurement, with that i don't let the batterie to go below 5'6 volts, which is when the last led is off.

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OilSpigot wrote 07/15/2020 at 21:31 point

Great work. I plan on making one myself, just got a Raspberry Pi yesterday and am working through the several days worth of printing. 

I get an error when I try to run "walking_simulation_example.py" on the Raspberry Pi, saying "...GSLS 1.5 is not supported..."

Is that code supposed to be run on a computer, or can I run it on the Pi?

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Miguel Ayuso Parrilla wrote 07/15/2020 at 22:35 point

This code was last ran on the pc, i have to update the code with my last version running on raspberry pi that doesn't need pybullet (becouse this error seems to be caused by the pybullet installation) as pybullet at GUI mode woudn't run properly.

Also in order to run "walking_simulation_example.py" you will need to specify the port of the arduino and the route of the controller's events

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Miguel Ayuso Parrilla wrote 07/31/2020 at 18:55 point

New RPI code is updated, now it must run without problems on the Raspberry Pi, as long as you have all the libraries, plus arduino with its code and controller conected

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Caleb wrote 07/12/2020 at 20:12 point

Do you cut the threaded rod to length (42 mm, 74 mm), or are you purchasing them in those lengths?

What washers are you using (as shown in the build video), what are the specifications?

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Caleb wrote 07/12/2020 at 20:25 point

Sorry, not washers, bearings -- ball/flange bearings?

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Miguel Ayuso Parrilla wrote 07/13/2020 at 08:58 point

I cut them, as i have the tools needed at home. About the bearings, as components sugest, they are the typical ball bearing with 3mm inner x 8mm outer x 4mm width.

Anyway Caleb, at this repo there is the STEP model, if you want to check bolt dimentions or what needed (this repo is from the awesome spot micro community, there is lot of research there): https://gitlab.com/Miguelasd/3dprinting/-/tree/master/User%20MiguelAsd%20custom%20models

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Caleb wrote 07/07/2020 at 04:02 point

Where are the batteries in the V2 design -- is that the red underbelly area?

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Miguel Ayuso Parrilla wrote 07/07/2020 at 15:20 point

Just under the body, you can check how it goes at the building video

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Nicola Russo wrote 07/05/2020 at 14:10 point

Hello! I just want to let you know that your project largely inspired the kinematics model for my experiment (https://github.com/nicrusso7/rex-gym). Of course I've put your name and the link to this project in the credits section. Hopefully I can inspire you as well! :)

Well done!!

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Miguel Ayuso Parrilla wrote 07/06/2020 at 12:39 point

Hi Nicola. This is amazing!! Your project is also very well documented, i will take a look at it! I'm happy to know it has been useful for you and thanks for spending your time reading my project. Together we are building something very big!

Regards.

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dev1122 wrote 07/02/2020 at 16:12 point

what is the use of kinematic_model.py file, please help regarding that.

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Chamika Ekanayaka wrote 06/29/2020 at 21:35 point

Hey there! Good job on the project, I was wondering if I could replicate this whole system, but I couldn't find any files for the 3D parts or any schematics to follow up, would these ever be available and how long would it take?

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Miguel Ayuso Parrilla wrote 07/02/2020 at 15:47 point

I'm just working on it! i promise you to release all the 3d model files in 2 weeks max, i have just finished printing the final version and i'm starting to documentate all the building process, stay tuned man!

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Alan Churichi wrote 06/20/2020 at 18:04 point

Hi! Really nice work!

Do you have schematics files for the connections?

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Miguel Ayuso Parrilla wrote 06/21/2020 at 21:01 point

Thanks Alan! I'm working on it, as soon as i solder the new electronics i will post the schematics.

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albertson.chris wrote 05/15/2020 at 00:40 point

Will you post th CAD files?   Already I'd like to try building just one leg for testing and I can think of a few changes.

One other question:  It looks like the prototype in the video was missing the Pi and batteries.  How much weight could be added?   Certainly the Pi4, batteries and see DC/DC regulator will need to be addd but also some sensors.

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Miguel Ayuso Parrilla wrote 05/15/2020 at 10:07 point

Yes! i'm finishing them, i think in the next 3 month i will print all the parts left, correct them if there are mistakes and then share them.

Yes, batteries, raspi and its cables are taken into account in the design, they add about 500-700 g, but also i'm removing weight in the design. Another diference between prototype and wireless version is that cable is going at 5V and batteries at 7.4V.

So i think, there will be no problem with this extra weight

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Mustafa wrote 05/14/2020 at 18:11 point

If you prepare a basic udemy course we can buy it

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Mustafa wrote 05/14/2020 at 16:50 point

Miguel I am following your project, thanks for those precious informations.. Please continue..

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Miguel Ayuso Parrilla wrote 05/15/2020 at 10:08 point

Thanks a lot man! Of course i'll be documenting all the project.

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Comedicles wrote 05/14/2020 at 06:17 point

Does it have accelerometers and inertial orientation? Put the poor thing out of its misery and place it on a  rubber surface so that leg motion can correspond to movement through space. I can tell it is miserable!

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Steve wrote 05/13/2020 at 17:23 point

I loaded the STLs into Ideamaker(3D-printer slicer) and it shows up super-tiny, like it's in inches not millimeters. What are the dimensions supposed to be  if we wanted to print this out ?
Thanks

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Miguel Ayuso Parrilla wrote 05/13/2020 at 22:40 point

Those files are not printable, are only for show them on the simulation, thats why u see them very small as they are meassured on meters. If you look closer to them, there is no way to build or mount them with the hardware

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Steve wrote 05/14/2020 at 00:10 point

Is there a way to print it out if we wanted to work on one ourselves or is that not ready yet ?

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Steve wrote 05/14/2020 at 00:14 point

Anyway, this is still very cool and I'm looking forward to reading about it more as it progresses along.

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