Raspberry Pi Zero bakes in a camera connector

The cheapest and most compact version of the Raspberry Pi has just seen a rather nifty little addition in the form of a camera connector.

As announced on the Pi blog, the new connector for the Pi Zero fits snugly onto the right-hand side of the board, as you can see in the image above.

And the good news is the price of the Pi Zero remains the same, so it'll still run you to just £4 ($5). To hook up your camera, you'll also need a custom 6-inch adapter cable, which goes under the name of the Camera Cable: Raspberry Pi Zero Edition, and will cost a further £4.

Size matters

The camera connector is smaller on the Pi Zero, unsurprisingly, so you won't be able to use an existing cable from your normal-sized Raspberry Pi.

If you missed it, a new camera board was also launched for the Raspberry Pi last month, which is an eight megapixel affair and it comes in a normal visible light version and an infrared flavor with both being pitched at £19 ($25).

So you can now hook up this new snapper featuring a Sony IMX219 sensor to the Pi Zero.

The Pi Foundation says it has shipped out 30,000 more units of the Zero, but we doubt that stock will last that long, as given the minimal outlay, these have proven to be extremely popular. 

IoT Vehicle Simulation System

The OBDII breakout module connected to the Vehicle Simulator/Recorder module:

Here is a picture showing the card stack making up the vehicle simulator/recorder module:

A little additional perspective :

When thinking about how the internet-of-things will evolve, it is easy to predict vehicles will be a significant focal point for consumer applications, since vehicles currently represent by far the biggest technology expenditure/investment by the average consumer. Vehicles are very complex machines incorporating multiple micro-controllers communicating via on-board buses. The level of electronic technology in vehicles has exploded and there is a large amount of vehicle data readily available on the diagnostic bus which is used locally, but not yet used for the vast number of potential external applications.

      There will be whole sectors of applications such as :

• safer driver operation of the vehicle, fewer distractions, more automation
• more effective driving methods
• ways to save fuel
• safer mechanical performance, better & more timely maintenance warnings
• lower cost operation and lower maintenance costs
• better and more timely driver information
• better advanced traffic warnings and route planning
• vehicles better designed to address owner needs and habits
• accident response applications
• vehicle-to-internet applications
• vehicle-to-vehicle communications
• applications that use data from multiple vehicles

Initial Simulator Concept :

Initially the system will need to be able to provide OBD2 data just as a real vehicle would in response to queries on a CAN bus or K-Line interface. To ensure realistic data, trip data will be collected from real vehicles the project will include a data collection system as well as a playback / simulation system. During a simulated trip, previously recorded data can be interpolated to provide appropriate data to any bus queries.

An attempt will be made to keep the software modular enough that it won't be difficult to replace fault code simulations with better simulations when more is understood about their behavior and also to replace recorded trip scenarios with computed simulations, if and when they get developed.

Objectives :

The primary objective for this project is to provide a vehicle simulator system that provides realistic enough data, primarily in electronic form, to allow developers to test their OBD2 reader prototypes & data applications in a lab instead of needing to test in a vehicle.

An secondary objective is to make the vehicle simulator such that it can be used to demonstrate new products and applications indoors at trade shows or sales presentations.

A third objective is to make the vehicle simulation system a modular platform that can be extended and upgraded to become a more accurate simulation for more vehicles.

An auxiliary objective is to create a data collection system that will continuously query a vehicle during a trip and record real data with time stamps.

VTR Block Diagram :

System Platform :

In order to make a compact open system that can be easily setup for testing or demonstration at any location the Beagle bone Black (BBB) has been chosen as the platform. Several of them are being supplied by the project sponsors Texas Instruments, Cisco and element. This will allow a data collection system (RTR) to collect trip data from a real vehicle, then a simulator system VTR can simulate this trip for the same data collection unit to see if it collects the same data from the simulation as it did from the real trip. This dual system provides an easy way to validate the system.

System Design :

OBD2 data provides a lot of information about what is occurring inside vehicle systems, but it does not necessarily provide everything desired in a simulation, such as location and orientation of the vehicle, distance traveled, and time stamps on all data.

The Beagle bone Black (BBB) has a CAN bus capability, but a custom cape will be needed to translate this to OBD2 signals and add in a K-Line interface. This cape will also include a GPS module and a 10 channel sensor suite - 3 orthogonal linear accelerometers, 3 orthogonal angular rate sensors, 3 orthogonal magnetometers and an absolute pressure sensor. These sensors are not needed in the simulator system, but will allow more sophisticated sensor data to be collected when the device is used for recording real trips and this data can later be presented by the simulator. The VTR/RTR cape will also include a Bluetooth module - when in VTR mode it will allow generation of fault codes and control of the VTR from a smart phone, when in RTR mode it will allow connection to a Bluetooth OBD2 interface or possibly a smart phone.

RTR Block Diagram  :

Project Plan :

The first major task is to set up 2 Beagle bone Blacks to communicate with each other over a CAN bus. This will allow us to gain an understanding of CAN bus messages and protocol. There are a bunch of associated sub tasks such as obtaining appropriate hardware, organizing software development tools, researching what is available on open source, writing some test code, etc.

• Design, build and test an OBD2 cape for the BBB.
• Connect a BBB to a vehicle and send and receive OBD2 messages.
• Write the RTR data collection firmware.
• Write VTR simulation firmware.
• Test and validate system.

Both vehicle simulator and vehicle recorder systems have been built and they communicate with each other fine over the CAN bus.

We are still having a devil of a time sorting out OBDII communications with a real vehicle. This is the main reason for such a long delay since our last posting, however I figured we need to post at least an update.

This screen shows location coordinates when the GPS finds enough satellites. Right now it is still showing UTC time.

This is a little warm because I have some bright lights shining directly on the module.

We are still sorting out some of the analog channels...

The LCD updates "instantly" in response to the keypad scroll buttons because it is interfaced via SPI.

Dusk-Dawn Controller

Solar streetlights can be easily integrated with a dusk-dawn controller by simply employing a pnp transistor and a few resistors where the solar panel itself works as the sensor. But what about other lighting sources that do not employ solar panels such as automatic lighting systems in small wind turbines, automatic lighting in cars or battery based systems where automatic lighting is necessary?

A simple, low-cost, yet an effective solution for the dusk-dawn controller circuit is described here.(a) dawn mode, (b) dusk mode and (c) prototype

Circuit and working

Circuit diagram of the dusk-dawn controller is shown in Fig. It is built around a light-dependent resistor (LDR), n-channel MOSFET IRF640 (T1), 12V LED light or a small inverter (100W) and a few other components.

The 12V battery-operated circuit is designed such that the common battery supply is used for operating the circuit as well as for load, that is, for power LED/small inverter circuit. Resistors R1 and R2 are used as a voltage divider and a current limiter in the circuit, respectively. LED is used as circuit de-activation indicator. LDR is the main component for actuation of the dusk-to-dawn sensing. The n-channel MOSFET IRF640 is for the switching action of the LED light or the small inverter connected to the system through switches S1 and S2, respectively.

With daylight falling on LDR , resistance of LDR becomes low, a small current flows through LED and it glows. At the same time, due to low voltage across LDR, MOSFET IRF640 does not trigger. So load  remains off.

But when the surrounding area of LDR (dusk mode) is dark (at night), resistance of LDR becomes very high, no current flows through LED and it does not glow. At the same time, due to higher voltage across LDR, IRF640 triggers. So load light comes on, provided switch S1 or S2 is on.

IRF640 can handle a maximum current of approximately 18A, but you can limit its application to approximately 8A-9A only, based on which the heat-sink is attached to the 

MOSFET.

PCB and component layout

After assembling the circuit, enclose it in a suitable box. The unit should be fixed on the pillar in such a way that the daylight falls directly on LDR.

How to Motor Speed Control

In many applications it is required to precisely control speed of DC motor to an exact RPM. In such application it is required to control as well as measure DC motor speed. In close loop control system speed of DC motor is controlled at the same time its actual speed is also measured and given as feedback. The system compares require speed and actual speed and takes necessary action if deviation is found. So simultaneously DC motor speed is increased or decreased by applying PWM and its actual speed is measured means two tasks are performed simultaneously, generating PWM and measuring RPM.

It generates PWM to vary speed of DC motor and at the same time it continuously measures RPM of it. The project is built using AVR micro controller ATMega16. It increases pulse width from 10% to 99% and measures DC motor RPM and displays pulse width as well as RPS (revolution per second) on LCD.

Circuit diagram:

Circuit is built using AVR ATMega16, 16x2 LCD, darlington NPN transistor TIP122, opto interrupt sensor MOC7811 and few additional components.

The internal IR LED of MOC7811 is forward biased by giving direct 5 V supply through 330E current limiting resistor. The photo transistor is connected in switch configuration. The output of sensor is taken from collector of photo transistor

This output is given to timer/counter 0 input pin PB0 of ATMega16

The LCD is connected to PORTD in 4-bit mode. Its data pins D4-D7 are connected to PD0 – PD3 and control pins Rs and En are connected to PD4 and PD5 respectively. RW pin is connected to ground to make write enable. 1 K pot is connected to brightness control pin VEE to vary LCD brightness

The PWM output pin PD7 is given at the input of TIP122 through limiting resistor 470E. DC motor is connected to collector output of TIP122 as shown. Thus PD7 pin drives DC motor through TIP122

A crystal 8 MHz is connected to crystal input pins along with two 22 pF capacitors. It will provide clock signal for all micro controller internal operations

A reset push button is connected to reset input pin to provide manual reset to controller

Circuit working and operation:

Initially motor is at rest. A strip is attached to motor shaft such that as motor rotates the strip passes through the gap of MOC7811. So this will generate a pulse. So revolution of motor is converted into pulse

The micro controller starts generating PWM on PD7 pin. The duty – pulse width increases from 10% to 99% and again it reduces to 10% and this cycle continuous.

Micro controller sets 10% pulse width, display it on LCD and apply it to motor. The motor starts rotating slowly. Then it waits for 2-3 seconds for motor to settle down to new speed.

Then micro controller starts counting pulses coming from sensor and counts it for 1 sec only. After 1 sec It directly displays the pulse count as RPS on LCD

Then it waits for 2-3 sec. Again it increases pulse width to 20% and display it. Wait for motor to attain stable speed and measures the pulse count. After 1 sec updates the pulse count as new RPS (speed).

Again after 2-3 second the cycle repeats. Every time the pulse width is increased in step of 10% and new RPS is displayed.

The pulse width is increased upto 99% and after that once again it is reduced to 10% and whole cycle repeats continuously

So micro controller continuously increases motor speed by generating PWM and also counts RPS and display them on LCD

Above working is based on the program embedded into internal FLASH memory of ATmega16 micro controller

Software program:

The program is written in C language. It is compiled using AVR studio software tool. It is simulated using AVR simulator 2 for ATmega16 device available with AVR studio software. Here is the C program code

#include <avr/io.h>
#include<string.h>
#include <util/delay.h>




 void senddata(unsigned char data)
 {
   _delay_ms(2);
   unsigned char d;
   d = data & 0xF0;
   PORTD |= 0x10;
   PORTD = (0x10) | (d>>4);
   PORTD |= 0x20;
   PORTD &= 0xDF;
   d= data & 0x0F;
   PORTD = (0x10) | d;
   PORTD |= 0x20;
   PORTD &= 0xDF;
 }

 void sendcmd(unsigned char cmd)
 {
   _delay_ms(2);
   unsigned char d;
   d = cmd & 0xF0;
   PORTD &= 0xEF;
   PORTD = d>>4;
   PORTD |= 0x20;
   PORTD &= 0xDF;
   d= cmd & 0x0F;
   PORTD = d;
   PORTD |= 0x20;
   PORTD &= 0xDF;
 }

 void lcd_init()
{
  sendcmd(0x02);
  sendcmd(0x28);
  sendcmd(0x0E);
  sendcmd(0x01);
  printstr("Duty:");
  sendcmd(0xC0);
  printstr("Speed(RPS):");
}

void display_duty(unsigned int duty)
{
  unsigned int d;
  unsigned char ascii[2];
  d=duty%10;
  ascii[1]=d+0x30;
  duty=duty/10;
  ascii[0]=duty+0x30;
  sendcmd(0x85);
  senddata(ascii[0]); 

  senddata(ascii[1]);
  senddata('%');
}

 void display_rps_value()
{
  unsigned int t1,a,t;
  unsigned char asci[3];
  unsigned char tmp1,tmp2;
  tmp1 = (TCNT0 & 0x0F);
  tmp2 = TCNT0 & 0xF0;
  tmp2 = tmp2>>4;
  t = tmp1+tmp2*16;
  

   if(t>=100)
  {
    a=2;
    while(t>=10)
    {
     t1=t%10;
     asci[a]=t1+0x30;
     t=t/10;
     a--;
    }

 asci[0]=t+0x30;
}

 else
{
 t1=t%10;
 asci[2]=t1+0x30;
 t=t/10;
 asci[1]=t+0x30;
 asci[0]=0x20;
}

 sendcmd(0xCB);
 senddata(asci[0]);
 senddata(asci[1]);
 senddata(asci[2]);
}

 int main(void)
{
  DDRD = 0xFF;
  DDRB = 0x00;
  PORTD = 0x00;
  TCCR2=0x6B;
  lcd_init();
  

   while(1)
   {
    display_duty(duty);
    OCR2 = duty_cycle;
    _delay_ms(2500);
    TCNT0 = 0x00;
    TCCR0 = 0x06;
    _delay_ms(1000);
    TCCR0 = 0x00;
    display_rps_value();
    _delay_ms(2500);

    if(duty_cycle<250) {duty_cycle+=25;duty+=10;}
    else if(duty_cycle==250) {duty_cycle=25;duty=10;}
    if(duty==100) duty-=1;
  }

}

Beaming Internet From Space Through Astronomer

The Internet is now considered a necessary portal for the flow of information, sixty eight per cent of the population of our country still does not have access to it. Hence a change in this scenario requires undivided attention. From the founders’ perspective, the only way to solve this pain point was by introducing Astronomer to the world.

Terrestrial Internet requires infrastructure like laying a lot of cable to reach all locations and obtaining the necessary ‘right of way’ clearance to install the cable. This is not only slow and problematic but quite expensive, too. For example, it costs about ` 210,000 to lay optical fiber cable for one kilometer in India.

Reaching three thousand gram penchants by laying only terrestrial cables is not an easy task. An initiative called Bharat-Net is trying to extend its fiber-optic connectivity but it has a very limited scope too, considering the terrain and geographic constraints.

Satellite based Internet doesn’t require expensive ground infrastructure. Since we are not laying optical fiber cables, the cost of providing the Internet to semi-urban and rural locations is hundred times lower than that in terrestrial technology.

Though the Internet penetration rates are growing rapidly, the statistics provided on November 30, 2015 by the Broadband Commission showed that, more than half of the world population is not connected to the Internet yet.

Space based solutions are practically cost-effective in the long run compared to their terrestrial counterparts. Terrestrial technologies (cables, fiber optics) provide high capacity at high cost in a concentrated fashion, and could be customized where a large number of users are present. But space based solutions provide distributed capacity at lower cost. These are best suited for the businesses scattered across regions that are sparsely populated.

How Astronomer works

The floating routers concept used by Astronomer makes use of some low orbital satellites, which act as routers working similar to a DTH streaming system. The on-ground subscribers can get high-speed Internet using a simple dish antenna on a rooftop.

Over the next few years Astronomer would send a constellation of hundred micro satellites in the low Earth orbit (LEO). LEO is preferred to the geosynchronous orbits, because geosynchronous orbits are distant too far to relay two-way communication with acceptable propagation delays. Propagation delay in a geosynchronous orbit is about forty times longer than in an LEO.

The satellites take up their positions on the lower orbits covering 1200-1800 kilometers in diameter. It is estimated that four to five satellites are enough to ensure broadband at one point of time all across the Indian geographical region.

Packed with a bandwidth of 100Gbps per satellite, the users on Earth can have up to 50Mbps and 400Mbps for business users. The beauty of it is that, this speed does not depend on the geographical location of the user. The speed at which the Internet streams for people accessing from a crowded city or a remote hamlet in the Himalayas remains the same.

The vision we witness here is similar to the telecommunication revolution where people linked up to the mobile-phone technology and discarded the old immobile telephones. In time this technology is capable of providing a major leap of accomplishment for the Internet connectivity.

The ground nodes would be set up on strategic locations on the ground, though most of the infrastructure would be floating in space. The ground nodes would connect and talk to servers that are located on the Earth’s surface.

Other competing ideas

Providing the Internet from air or space is of much interest these days. But Astronomer is a little different from the other players in this space. Google’s ‘Project Loon’ plans to make the Internet available to remote locations via balloons moving in the jet stream at 18km altitude from ground. Facebook has plans to beam broadband signals from drones and satellites. Another player, SpaceX, plans to build a network of four thousand satellites in LEO by 2030.

There is also One Web, backed by Bharti Enterprises in India, who would be placing 648 satellites in LEO by 2018. Viasat is planning to provide the Internet service with up to 1Tbps by launching three GEO satellites (Viasat-3).

Our approach to the problem is quite different from the other players like OneWeb and ViaSat. What differentiates Astronomer from OneWeb and ViaSat is that Astronomer operates in the millimeter wave region of the electromagnetic spectrum, which is between 30GHz and 300GHz. Millimeter waves have very narrow transmission beam width and high bandwidth band allocations. This allows it to have significantly higher capacity per satellite.

Future plans

Astronomer wants to involve individuals and organisations to build a strong team and become a collaborative effort. Their talks with ISRO for launching the satellites are already on. By 2018, Astronomer, hand in hand with ISRO, plans to take help of experienced satellite design and manufacturing companies to create a satellite assembly line.

Astronomer also plans to actively engage with the Internet of Things (IoT) industry, which is expected to significantly influence the technology landscape in the next five years. It intends to provide their IoT devices with location-free, reliable, high-bandwidth Internet from as early as 2019.

The Indian space programmer shows a road map for science and technology to improve the quality of life of the masses. At Astronomer, it is considered a coincidence that, together with ISRO, an ambitious idea like this is taking shape to use space technology for providing location-free, high-speed Internet. Astronomer is being incubated at IISc, a place where the foundations for the Indian space programmer were laid way back in the 1950s.

Colour-Sensing Robot with MATLAB

A camera is one of the most powerful and accurate sensors if you know how to process the images taken by it for the information you want. You can process subsequent images and extract a variety of information using image-processing techniques. MATLAB is a very powerful tool and plays an important role in image processing. 

Image processing is converting an image into digital form and performing some mathematical operations on it, in order to get an enhanced image or to extract some useful information out of it. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it.

Presented here is a MATLAB-based project where images taken by the camera are processed for colours and the position of a red-coloured object is extracted out of the image. Based on the position of the red coloured object in the image, different data are sent via COM port. The serial data are received by the robot and corresponding movement is done. You can change the code for any colour that you find suitable.

This project is just an example and you can use this for various industrial applications such as controlling heavy load-lifting machines with some object of a specific colour in your hand.
Co loured object can be held in your hand, which instructs the robot to move right, left, forward or backward as per the position of your hand, as shown in Fig.

Circuit and working

The circuit of the robot, which uses micro-controller P89V51RD2  to receive serial data from the computer through driver IC MAX232 . The received data is analysed by the micro-controller IC1 and the motors are controlled through motor-driver IC L293D . The power supply for the robot comes from a 9V battery which is regulated to 5V by regulator 7805 . 9V is also connected to pin 8 for IC2 for the motors.

The USB port of the computer is connected to the robot through USB-to-serial converter. Controlling commands to the robot are sent via serial port and the signal levels are converted into 5V TTL/CMOS type by IC3. These signals are directly fed to micro-controller IC1 for controlling motors M1 and M2 to move the robot in all directions. Port pins P1.0 through P1.3 of IC1 are connected to the inputs of IN4 through IN1 of IC2, respectively, to give driving inputs. EN1 and EN2 are connected to Vcc to keep IC2 always enabled.

The application running on the computer interprets the position of the colored object and sends corresponding commands to the robot through the serial port. As shown in the pictures in Fig. 1, if the operator stands in front of the computer’s camera, holds a red-colored object in his hand and raises his hand up, the MATLAB application running in the computer interprets the position of the colored object and sends ‘a’ to the serial port. The robot is programmed to move forward if it receives ‘a’ from the serial port. Similarly, for other positions, the letters are listed in the table, which are sent through the serial port to the robot.

Software

The program for the robot is written in C language using Keil compiler and the hex file is programmed in the micro-controller chip with a suitable programmer. The application running on the computer to interpret the position of colored object is designed using MATLAB. The application uses colour-detection algorithm to detect the colored object and then finds out its coordinates to detect the position.

Colour detection algorithm.

In colour-detection algorithm, the primary-colour (red, green and blue) objects can be detected easily. The algorithm used for colour detection actually works in separate steps as follows:

1. Take the snapshot (image) from the real video
2. Convert that original snapshot to grey
3. Extract the red coloured components from the original snapshot
4. Now subtract the red coloured components from the grey coloured snapshot
5. Remove the noise from the image by using filter command
6. Convert that filtered image into binary image and you will get an image that is bright at 

     the place of red object
7. Then find the coordinates of the bright portion

MATLAB program.

Some important functions used in the program are:

data = getsnapshot(vid). This function immediately returns single-image frame from the video input object

img = rgb2gray(data). Converts the true-colour image RGB to the grey-scale intensity image

data(:,:,1). Extracts all the red colored components from the real image

Similarly, for green: data(:,:,2) and for blue: data(:,:,3)

diff_im = imsubtract(data(:,:,1), rgb2gray(data)). Used to subtract red components from the grey image

B = medfilt2(diff_im, [3,3]). Median filtering is a non-linear operation often used in image processing to reduce ‘salt and pepper’ noise. A median filter is more effective than convolution when the goal is to simultaneously reduce noise and preserve edges

diff_im = im2bw(diff_im, 0.18). Converts the greyscale image to a binary image. The output image ‘diff_im’ replaces all pixels in the input image with luminance greater than level with the value 1 (white) and replaces all other pixels with the value 0 (black)

stats = regionprops(diff_im, ‘BoundingBox’,’Centroid’). Measures a set of properties for each connected component (object) in the binary image. The image stats is a logical array and can have any dimension

By using ‘regionprops ( )’ function, we find the coordinates of centroid and bounding box as follows:

The ‘Centroid’ in the code specifies the centre of mass of the region. Note that the first element of centroid is the horizontal coordinate (or x-coordinate) of the centre of mass, and the second element is the vertical coordinate (or y-coordinate). Once we get the coordinates, we define conditions for the object’s position and corresponding data to be sent to the robot as follows:

the position of the object in the defined centre range and Fig. 5 indicates that the object is raised to give a forward signal. The same is done for left, right, forward and backward movement.

PCB and Component Layout

single-side PCB for the robot is shown in Fig. and its component layout in Fig. Assemble the components on the PCB and connect the motors and battery to build the robot. Use suitable bases for the ICs. Before inserting the MCU in the circuit burn the code into it using a suitable programmer. Connect the robot to the computer either through the serial port or USB port (using USB-to-serial converter) and check whether the USB-to-serial converter is detected or not in the device manager and change the COM port with respect to it.

Download Source Code: click here

Install MATLAB 7.10 or higher version in your system. Once it is installed, connect it to the robot. Also check which COM port you are using and write the same COM port in the code.

Run application

Once the setup is ready, follow the below-mentioned steps:

1. Download the required source code folder from this month’s EFY DVD.

2. Run the program gesture.m and a GUI will appear as shown in Fig. 3.

3. Click on COM OPEN button to open the COM port.

4. click on START and stand in front of the computer’s camera or webcam with the red-   

    coloured object in your hand.

5. move the object up, down, left and right, and MATLAB program will send the data to the 

    micro-controller according to the position of the object and the robot will move according 

    to the values the micro-controller is receiving.

Arduino Powered Hexapod Robot

Descriptions:

-- This Hexapod Robot, which can be made by yourself has a natural looking. - Its articulate 

   leg and body design enhances the perfection of DIY robot.

-- This robot can walk in any direction with the help of three DOF (degree of freedom) leg   

   design

-- It has not only perfect looks but is best in performance and also commercially available.

--32 servo controller and remote control handle is used.

-- Material:. Alumnium alooy blasting processed. 

Features

The Robot is a complex walker in nature and is available for Wireless Wifi / Bluetooth / RF control using the USB SSC-32 Servo Motors Controller.

18x TowerPro MG995/MG996R/LD1501MG Servo

12x Aluminum Multi-Purpose Servo Bracket

6x Large Aluminum hexapod robot legs

6x Small Aluminum hexapod robot legs

2x Hexapod robot main mounting plate

1 Set Hexapod Accessories

Dimension:

When it comes to dimension, its single leg straight about 23cm, torso shell length 17.5cm and width of 15.5cm. Further, each robot leg has three joints which can be moved forward and backward and can be tuned to turn, dance and climb. It can also perform other kinds of actions. The kit available for parts are easy to install and learn robotics. Their purchase and installation drawings can be sent as an exclusive learning materials.

Package

1 set of 6-foot robot full-metal stents accessories

MG995/MG996R/LD-1501MG servos x18

32 Servo Controller x1

A high-quality USB cable x1

A high-power chip buck x1

A balance charger x1

A high-power rocker switch x1

Cable ties x1

Copper Cylinder x1

About Control Systems

The 32 servo controller board can move simultaneously. The robot has only 18 servo, which allows customers to choose 18 interface. Specific function control panel are elaborated below.

-- Internal control board have all the underlying code that helps customers to avoid writing  

    C code.

-- The three most important features of the servo control board is the online debugging,

    offline campaign and PS2 remote control handle facilities

-- Offline campaign in a Good PC software action after tune provides "Download" button to

    download the dashboard.

-- The PS2 handle remote control, it means that If the PC software has compiled a good 

    number of the action group that is sequentially downloaded to the control panel inside 

    the handle above the key corresponding to the download of independent action groups

-- The control panel reserved communications and other micro-controller TTL level serial 

    communications can send commands to the control panel by another micro-controller. 

    This will help achieve six legged robot more intelligent movement

-- The control board and switch can be directly fixed to the robot housing.