Better than an Xbee and cheaper Hobby King 433Mhz Radio Telemetry Kit 100mW

Ran this wee puppy at 57,600 full duplex no issues at 1/4 mile with the RX inside my neighbors brick post box. Seems to penetrate the masonry better than a 2.4Ghz Xbee and its half to a quarter of the price the price especially if you buy from Sparkfun. 

Like the Xbee it resumes comms very quickly after a power cycle which is pretty essential for RC usage. 

Arduino Xbee Receiver Arduino Nano V3.0 Microcontroller Board from hobby king

 http://kiwitricopter.blogspot.co.nz/2013/10/rx-tx-csharp-to-arduino.html
Features:
• Very small size
• Light weight (under 4 grams without antenna)
• Receiver sensitivity to -121 dBm
• Transmit power up to 20dBm (100mW)
• Transparent serial link
• Air data rates up to 250kbps
• Range of approx 1 mile
• MAVLink protocol framing and status reporting
• Frequency hopping spread spectrum (FHSS)
• Adaptive time division multiplexing (TDM)
• Support for LBT and AFA
• Configurable duty cycle
• Built in error correcting code (can correct up to 25% data bit errors)
• Demonstrated range of several kilometers with a small omni antenna
• Can be used with a bi-directional amplifier for even more range
• Open source firmware
• AT commands for radio configuration
• RT commands for remote radio configuration
• Adaptive flow control when used with APM
• Based on the HopeRF HM-TRP radio module, featuring an SiLabs Si1000 RF microcontroller

A quick test at 57,600 Baud seems like a great product and well priced at US$29.99

XBee Pro 60mW Wire Antenna - Series 1 (802.15.4) 

US$37.95 AND YOU NEED 2

FPV 433Mhz Radio Telemetry Kit 100mW
US$29.99 AND YOU GET A PAIR

An interesting price point comparison between Sparkfun and HobbyKing on another useful and in this case identical product. HK are almost 80% cheaper

Arduino 9DOF ArduIMU Controller ATmega328 (ACCEL/MAG/GYRO)

 US$29.99

Same product from Sparkfun 9 Degrees of Freedom - Razor IMU 

US$124.95

So HK sell this identical device for almost 80% less

But it get worse if are a Kiwi you buy from our local Sparkfun reseller9 Degrees of Freedom - Razor IMU - AHRS compatible NZ$180.49

 

To be fair on Mind Kits they do buy from Sparkfun but that said the bloke at Mind Kits has a way worse supply deal then Hobby King 

200 mW TX on a 120mAh Lipo runs about 30 mins. Total weight with Lipoly 6.2 Grams, only 3.6 Grams with a 5V regulator so it runs of the main battery. The image is not great on a single Lipo cell. I will try it connected to a spare port on the RX see what the signal is like.

Generate video and OSD with Arduino

This setup could be used with Arduino and this Video overlay shield

And this very small light Arduino its possible  to create a OSD and FPV system under 10 grams

Femtoduino, Smallest Arduino compatible board 

Could reduce the size and weight of my MK1 Arduino / Xbee remote significantly

Simple Arduino Xbee Remote Control TX RX

With this camera you need to block out the light from the back of this camera of the PCB tracks show in the video feed. It needs a light enclosure for the whole assembly, nice and thin so it won't drag too much on top of a wing of where ever.The wires on the camera are a little fragile so I potted them in hot glue so they don't fatigue.

 

• Overlay text and graphics onto a video signal from a camera, DVR, DVD player, VCR or any other source of composite video.
• Capture low-res video image frames for display or video processing. Give your Arduino the gift of sight!
• Perform object detection for computer vision projects.
• Decode NTSC closed captioning or XDS (extended data services) data embedded in television broadcasts.
• Works with NTSC (North America, parts of South America and Asia) or PAL (most of the rest of the world) television standards. For more info on what TV standards see the map here and this list of countries and their standards
• Uses digital pins 2, 6, 7, 8, and optionally 9. Uses analog pin 2
• Designed for Arduino Uno, Duemilanove and equivalents. Does not work on Leonardo or Mega (more info here).

All of these capabilities are demonstrated on the projects page.

How does it work?
The Video Experimenter uses an LM1881 video sync separator to detect the timing of the vertical and horizontal sync in a composite video signal. An enhanced version of the TVout library (available below) uses this sync timing information to overlay content onto the video signal. The ATmega328 microcontroller on the Arduino includes an analog comparator that can be used to detect the brightness of the video signal at any given point in time. Using this brightness information, low-res monochrome image capture into the TVout frame buffer is possible. The ability to capture image information in memory lets you implement simple computer vision experiments.
It's important to note that this shield will not work on the Arduino Mega. Read this for more information (it's not my fault!). The Video Experimenter will work on the Seeeduino Mega with some jumper wires. Read this for more information.

Kalman Filter Code for Yellow Plane 2 Special thanks to Kristian Lauszus, TKJ Electronics 

This is the code in the main loop UpdateServos()

<code>

unsigned long msDelta = LastMicros - micros();
LastMicros = micros();

//Measure time since last cycle
double dt = (double)msDelta / 1000000.0;


// The angle should be in degrees and the rate should be in degrees per second and the delta time in seconds
double X_Angle = (double)AnIn[0];
double X_Rate = (double)AnIn[4];
double Kalman_X = kalman[0].getAngle(X_Angle, X_Rate, dt);

double Y_Angle = (double)AnIn[1];
double Y_Rate = (double)AnIn[5];
double Kalman_Y = kalman[1].getAngle(Y_Angle, Y_Rate, dt);

double Z_Angle = (double)AnIn[2];
double Z_Rate = (double)AnIn[6];
double Kalman_Z = kalman[2].getAngle(Z_Angle, Z_Rate, dt);

</code>

kalman.h can be downloaded here

<code>

/* Copyright (C) 2012 Kristian Lauszus, TKJ Electronics. All rights reserved.

This software may be distributed and modified under the terms of the GNU
General Public License version 2 (GPL2) as published by the Free Software
Foundation and appearing in the file GPL2.TXT included in the packaging of
this file. Please note that GPL2 Section 2[b] requires that all works based
on this software must also be made publicly available under the terms of
the GPL2 ("Copyleft").

Contact information
-------------------

Kristian Lauszus, TKJ Electronics
Web : http://www.tkjelectronics.com
e-mail : kristianl@tkjelectronics.com
*/

#ifndef _Kalman_h
#define _Kalman_h

class Kalman {
public:
Kalman() {
/* We will set the varibles like so, these can also be tuned by the user */
Q_angle = 0.001;
Q_bias = 0.003;
R_measure = 0.03;

bias = 0; // Reset bias
P[0][0] = 0; // Since we assume tha the bias is 0 and we know the starting angle (use setAngle), the error covariance matrix is set like so - see: http://en.wikipedia.org/wiki/Kalman_filter#Example_application.2C_technical
P[0][1] = 0;
P[1][0] = 0;
P[1][1] = 0;
};
// The angle should be in degrees and the rate should be in degrees per second and the delta time in seconds
double getAngle(double newAngle, double newRate, double dt) {
// KasBot V2 - Kalman filter module - http://www.x-firm.com/?page_id=145
// Modified by Kristian Lauszus
// See my blog post for more information: http://blog.tkjelectronics.dk/2012/09/a-practical-approach-to-kalman-filter-and-how-to-implement-it

// Discrete Kalman filter time update equations - Time Update ("Predict")
// Update xhat - Project the state ahead
/* Step 1 */
rate = newRate - bias;
angle += dt * rate;

// Update estimation error covariance - Project the error covariance ahead
/* Step 2 */
P[0][0] += dt * (dt*P[1][1] - P[0][1] - P[1][0] + Q_angle);
P[0][1] -= dt * P[1][1];
P[1][0] -= dt * P[1][1];
P[1][1] += Q_bias * dt;

// Discrete Kalman filter measurement update equations - Measurement Update ("Correct")
// Calculate Kalman gain - Compute the Kalman gain
/* Step 4 */
S = P[0][0] + R_measure;
/* Step 5 */
K[0] = P[0][0] / S;
K[1] = P[1][0] / S;

// Calculate angle and bias - Update estimate with measurement zk (newAngle)
/* Step 3 */
y = newAngle - angle;
/* Step 6 */
angle += K[0] * y;
bias += K[1] * y;

// Calculate estimation error covariance - Update the error covariance
/* Step 7 */
P[0][0] -= K[0] * P[0][0];
P[0][1] -= K[0] * P[0][1];
P[1][0] -= K[1] * P[0][0];
P[1][1] -= K[1] * P[0][1];

return angle;
};
void setAngle(double newAngle) { angle = newAngle; }; // Used to set angle, this should be set as the starting angle
double getRate() { return rate; }; // Return the unbiased rate

/* These are used to tune the Kalman filter */
void setQangle(double newQ_angle) { Q_angle = newQ_angle; };
void setQbias(double newQ_bias) { Q_bias = newQ_bias; };
void setRmeasure(double newR_measure) { R_measure = newR_measure; };

private:
/* variables */
double Q_angle; // Process noise variance for the accelerometer
double Q_bias; // Process noise variance for the gyro bias
double R_measure; // Measurement noise variance - this is actually the variance of the measurement noise

double angle; // The angle calculated by the Kalman filter - part of the 2x1 state matrix
double bias; // The gyro bias calculated by the Kalman filter - part of the 2x1 state matrix
double rate; // Unbiased rate calculated from the rate and the calculated bias - you have to call getAngle to update the rate

double P[2][2]; // Error covariance matrix - This is a 2x2 matrix
double K[2]; // Kalman gain - This is a 2x1 matrix
double y; // Angle difference - 1x1 matrix
double S; // Estimate error - 1x1 matrix
};

#endif

</code>

The Arduino code originally written by Kristian Lauszus, TKJ Electronics can be
downloaded here

I have a test harness written in C# there is a C# version of the Kalman Filter class which could very easyly be addapted for use with Fex Panda or Netduino Tiny CLR projects

The C# code for the test harness shown below can be downloaded here 

The above could be modified to accept input from a IMU or Accelerometers and Gyros

Yellow Plane 2 with inverted V tail software modified and tested stability gyros

Missing battery and camera box have a design which should weigh 140 grams empty.

The assembly shown below weighs 684 Grams no motor or electronics.

Electronics shown weigh 110 grams ESC Arduino board, Xbee, antenna & Gyro board

Motor & prop another 120 Grams

Yellow Plane 2 with inverted V tail Video 

RX Arduino code with mixing and closed loop stability
void UpdateServos()
{

//Digital inputs TX code helper
//TxVal[8] |= (digitalRead(5) << 0);//joy 2 push
//TxVal[8] |= (digitalRead(6) << 1);//pb
//TxVal[8] |= (digitalRead(7) << 2);//slide
//TxVal[8] |= (digitalRead(8) << 3);//toggle

//Throttle TxVal[1]
//Rotary pot TxVal[2]
//Joy 1 X TxVal[3]
//Joy 1 Y TxVal[4]
//Joy 2 X TxVal[5]
//Joy 2 Y TxVal[6]
//rssi TxVal[7]
//digital TxVal[8]
//micros() TxVal[9]

//Use the pot as the gain for all channels for now
float GainPot = (float)(TxVal[2]) * 0.001f;

//Get the target values from the TX
int PitchTarg = (TxVal[3] / 10);
int RollTarg = (TxVal[4] / 10);
int YawTarg = (TxVal[6] / 10);


//Prime the Target WOZ values
if(PitchTargWOZ == 9999)
PitchTargWOZ = PitchTarg;

if(RollTargWOZ == 9999)
RollTargWOZ = RollTarg;

if(YawTargWOZ == 9999)
YawTargWOZ = YawTarg;


//Get the Centered target values
float PitchTargCentred = (float)(PitchTarg - PitchTargWOZ);
float RollTargCentred = (float)(RollTarg - RollTargWOZ);
float YawTargCentred = (float)(YawTarg - YawTargWOZ);

//Calculate gains
float PitchGain = GainPot * 1.0f;
float RollGain = GainPot * 1.0f;
float YawGain = GainPot * 1.0f;

//Get Gyro values
float PitchGyro = (float)(AnIn[2] - AnInWOZ[2]);
float RollGyro = (float)(AnIn[1] - AnInWOZ[1]);
float YawGyro = (float)(AnIn[0] - AnInWOZ[0]);

//Calc P error
float PitchError = (float)PitchTargCentred + PitchGyro;
float RollError = (float)RollTargCentred + RollGyro;
float YawError = (float)YawTargCentred + YawGyro;

//Apply gains
int PitchTrim = (int)(PitchError * PitchGain);
int RollTrim = (int)(RollError * RollGain);
int YawTrim = (int)(YawError * YawGain);

//Constaring trim authority
PitchTrim = constrain(PitchTrim, -30, 30);
RollTrim = constrain(RollTrim, -30, 30);
YawTrim = constrain(YawTrim, -30, 30);

//Dump the trim value
if((TxVal[9] & 0x4) == 0)
{
PitchTrim = 0;
RollTrim = 0;
YawTrim = 0;
}



//Calc flap anglke
int Flaps = 0;

//Apply flaps
if((TxVal[9] & 0x8) == 0)
Flaps = -25;



//Throttle
val = TxVal[1] / 10;
val = map(val, 1, 179, 30, 179);
val = constrain(val, 1, 165); // scale it to use it with the servo (value between 0 and 180)
servo[0].write(val); // sets the servo position according to the scaled value


//Vee tail

//Left Elevator Joy 1 Y TxVal[4]
val = (YawTarg + YawTrim) + (PitchTargCentred + PitchTrim);
val = constrain(val, 15, 165);
val = map(val, 0, 179, 135, 45); // scale it to use it with the servo (value between 0 and 180)
servo[1].write(val); // sets the servo position according to the scaled value


//Right Elevator Joy 1 Y TxVal[4]
val = (YawTarg + YawTrim) - (PitchTargCentred + PitchTrim);
val = constrain(val, 15, 165);
val = map(val, 0, 179, 135, 45); // scale it to use it with the servo (value between 0 and 180)
servo[2].write(val); // sets the servo position according to the scaled value



//Left Flaperon
val = 90 + (RollTargCentred + Flaps) + RollTrim;
val = constrain(val, 15, 165);
val = map(val, 0, 179, 165, 15); // scale it to use it with the servo (value between 0 and 180)
servo[3].write(val); // sets the servo position according to the scaled value

//Right Flaperon
val = 90 + (RollTargCentred - Flaps) + RollTrim;
val = constrain(val, 15, 165);
val = map(val, 0, 179, 165, 15); // scale it to use it with the servo (value between 0 and 180)
servo[4].write(val); // sets the servo position according to the scaled value


//Joy 2 x nose Wheel
val = (TxVal[6] / 10);
val = map(val, 0, 179, 55, 125);
servo[5].write(val); // sets the servo position according to the scaled value

}

Revised Yellow FPV Plane with gyro stability system added, Worked best with analogue inputs from Murata piezo gyro sensors of a dead KK board filtered taking a 10 point average. Yaw compensation is currently not used as there is no rudder presently.

Gyro stability code in action

https://www.youtube.com/watch?v=IrSxP9YsLpY&hd=1

The RX board using the Arduino Nano weighs 12 grams

The code on Google Drive

:) IT FLY'S :) Maiden flight of Yellow Plane Hextronic DT850 Turnigy 2200mAh Xbee Arduino Controller

YouTube

Maiden flight of Yellow Plane flown by a local pilot Richard to avoid instant crash I would cause. A little tail heavy but flew pretty well on a gusty day, I'm told control was good. Ended in a crash but not too badly damaged, learned a lot. I'm just chuffed if flew looks pretty good on such a windy, which is pretty standard for the south island this time of year.

My scratch built FPV platform. Took around 30 hours to build mostly Corriboard with some ply, aluminium and carbon fiber spars. Total material cost around 50 US$. Got a DT700 (see tests data here) which hopefully will be an adequate power source. Its a modular design based around an armature, so wings and tail etc are bolted on and can be exchanged for testing parts and ideas. Have a pair of KM3 wings and the Corriboard one shown below.

Please see the spread sheet here Yellow Plane Data 

Based around a stiff wooden armature and two aluminium tail spars the wings are removable for transportation. According to my calculations the wing loading is 15.5 Oz/Ft² at a flight weight of 1700 Grams. A glass fiber nose has been molded and is curing now which is around 80 grams, which will contain the FPV gear and the main battery.

Home brew Arduino Xbee remote control 

Cobbled together 90 mm fan with 250 Watt  Turnigy L2210-1650 Bell Style Motor (250w) seeing if I can get decent efficiency from a small fan turning slower. 

On 14.8 Volts its pushing almost 500 Grams, not so bad thrust mapping is as follows.

100 Grams 1.9 A 27.6 Watts
156 Grams 3.0 A 42.9 Watts
197 Grams 3.9 A 55.1 Watts
257 Grams 5.5 A 76.0 Watts
296 Grams 6.7 A 90.9 Watts
340 Grams 7.9 A 105.5 Watts
432 Grams 10.7 A 138.1 Watts
492 Grams 12.5 A 155.7 Watts

The data in a spread sheet

The tests were run on two 7.4V 1300mAh Turnigy 20C Lipo's in series, I figure the motor will survive full throttle bursts on 4C and its 10 Amps short of the max, 100 Watts below its spec.

Its surprising as the same motor with a 8 X 6 prop pulled 23.3 Amps on a 3C yielding 520 Grams of thrust at 232.3 Watts.

Weighs around 150 grams.

Need a plane for it should be pretty ugly with such a big fan

Building the Arduino Receiver. The whole board and micro weighs in at 22 grams. The supply will be a 3C Lipolly

The Xbee Vin (max 16V) and Arduino VIN (max 20V) hare both powered from the supply battery 11.1 V directly as the both have internal regulators.  This helps isolate any noise from the Arduino and ore servos from being superimposed on the Xbee supply rail.

The Xbee need around 220mA and the Arduino say 100 mA driving the servo PWM signals, and not the motors. All up say 750mA in a 750mAh 3C

Working on Yellow Plane

Better Battery Box For Yellow FPV Plane

An improved battery box for my FPV plane project.  The front wheel need mounting on a spring piece, as do the rear struts. I don't like the idea of having no suspension at all, so will probably put springy trailing arms to let the rear wheels soak up some bumps without transmitting the landing/crashing forces directly to the frame.

Will be using a 2.5 liter Coke bottle as an aero shield with some foam board  internals to support the camera OSD GPS ect

pyXY - Synapse SM700 Dev Board May Be better than Xbee and seems cost effective
8 X 12 bit analogue inputs could do a RC controller without Arduino's  

This Data Sheet details the SM700PC1 module, which includes:

• Powerful 32-bit TDMI ARM7 microprocessor      
• Large on-board memory resources
• 2.4 GHz RF Frequency (2400 - 2483.5 MHz)      
• -96 dBm Rx sensitivity
• Up to 100mW output power      
• +20dBm Tx output power
• 16 RF Channels      
• 2.0 to 3.6 Volts Vcc
• Small footprint: 1” x 1.4” (25.4mm x 36.5mm)      
• Low power consumption:
• Operating temperature: -40°C to +85°C        
• Transmit mode……193mA
• Over 1.5 miles range        
• Receive mode………30mA
• FCC, CE and IC certified      
• Integrated F-antenna
• Accurate 12-bit ADC for precision sensors      
• Small surface-mount IC footprint

Datasheet Sparkfun ($69)

Description: It may look like a regular ol' Arduino shield, but don't be fooled, the pyXY (pronounced 'pixie') is a full blown shield-compatible development board. The heart of the pyXY is the Synapse SM700 wireless network module, a mesh network powerhouse that packs a 32-bit ARM7 processor with plenty of on-board memory. What's more, the SM700 can be programmed in SNAPpy, a Python derivative that makes building interactive networks a snap.