【脑洞大赛】第6组老少爷们队
本帖最后由 longxchen 于 2016-7-24 16:41 编辑神经元探索车
用Genuino 101 (神经元)模块通过wifi带视屏和抓手的小车远程控制取物排障，基本原理见原理图。
拓展：可以用四驱飞机投放到更加复杂地形进行排障，救援工作。
神经元部分代码：
#include "BLESerial.h"
#include "CurieIMU.h"
int ax, ay, az; // accelerometer values
int gx, gy, gz; // gyrometer values
int calibrateOffsets = 1; // int to determine whether calibration takes place or not
#include <CurieNeurons.h>
CurieNeurons hNN;
int catL=0; // category to learn
int prevcat=0; // previously recognized category
int dist, cat, nid, nsr, ncount; // response from the neurons
//
// Variables used for the calculation of the feature vector
//
#define sampleNbr 10// number of samples to assemble a vector
#define signalNbr6// ax,ay,az,gx,gy,gz
int raw_vector; // vector accumulating the raw sensor data
byte vector; // vector holding the pattern to learn or recognize
int mina=0xFFFF, maxa=0, ming=0xFFFF, maxg=0, da, dg;
void setup()
{
pinMode(13,OUTPUT);
Serial.begin(9600); // initialize Serial communication
BLESerial.setName("Bluno101");
BLESerial.begin();
//Serial.println("Bluetooth device active, waiting for connections...");
while(!BLESerial);
//while(!Serial); //Not need Serial while Demo zkp // wait for the serial port to open
// initialize device
Serial.println("Initializing IMU device...");
CurieIMU.begin();
// use the code below to calibrate accel/gyro offset values
if (calibrateOffsets == 1)
{
Serial.println("About to calibrate. Make sure your board is stable and upright");
delay(5000);
Serial.print("Starting Gyroscope calibration and enabling offset compensation...");
CurieIMU.autoCalibrateGyroOffset();
Serial.println(" Done");
Serial.print("Starting Acceleration calibration and enabling offset compensation...");
CurieIMU.autoCalibrateAccelerometerOffset(X_AXIS, 0);
CurieIMU.autoCalibrateAccelerometerOffset(Y_AXIS, 0);
CurieIMU.autoCalibrateAccelerometerOffset(Z_AXIS, 1);
Serial.println(" Done");
}
// Initialize the neurons and set a conservative Max Influence Field
hNN.Init();
hNN.Forget(1000); //set a conservativeMax Influence Field prior to learning
//int value=hNN.MAXIF(); // read the MAXIF back to verify proper SPI communication
//Serial.print("\nMaxif register=");Serial.print(value);
Serial.print("\n\nEntering loop...");
Serial.print("\nMove the module vertically or horizontally...");
Serial.print("\ntype 1 + Enter if vertical motion");
Serial.print("\ntype 2 + Enter if horizontal motion");
Serial.print("\ntype 0 + Enter for any other motion");
}
void loop()
{
// Learn if push button depressed and report if a new neuron is committed
if (Serial.available() == 2)
{
catL = Serial.read();
char inChar = (char)Serial.read();
if (inChar == '\n')
{
catL = catL - 48;
Serial.print("\nLearning motion category "); Serial.print(catL);
// learn 5 consecutive sample vectors
for (int i=0; i<5; i++)
{
getVector(); // the vector array is a global
//Serial.print("\nVector = ");
//for (int i=0; i<signalNbr*sampleNbr; i++) {Serial.print(vector);Serial.print("\t");}
ncount=hNN.Learn(vector, sampleNbr*signalNbr, catL);
}
Serial.print("\tNeurons="); Serial.print(ncount);
}
}
else
{
// Recognize
getVector(); // the vector array is a global
hNN.Classify(vector, sampleNbr*signalNbr,&dist, &cat, &nid);
if (cat!=prevcat && BLESerial.operator bool())
{
digitalWrite(13,HIGH);
if (cat!=0x7FFF)
{
Serial.print("\nMotion category #"); Serial.print(cat);
//BLESerial.write("\nMotion category # ");BLESerial.println(cat);
switch(cat) {
case 1: BLESerial.println("F"); break;
case 2: BLESerial.println("B"); break;
case 3: BLESerial.println("L"); break;
case 4: BLESerial.println("R"); break;
case 5: BLESerial.println("S"); break;
default: BLESerial.println(cat); break;
}
delay(100);
}
else
{
Serial.print("\nMotion unknown");
//BLESerial.write("\nMotion unknown ");
}
prevcat=cat;
}
}
}
void getVector()
{
// the reset of the min and max values is optional depending if you want to
// use a running min and max from the launch of the script or not
mina=0xFFFF, maxa=0, ming=0xFFFF, maxg=0, da, dg;
for (int sampleId=0; sampleId<sampleNbr; sampleId++)
{
//Build the vector over sampleNbr and broadcast to the neurons
CurieIMU.readMotionSensor(ax, ay, az, gx, gy, gz);
// update the running min/max for the a signals
if (ax>maxa) maxa=ax; else if (ax<mina) mina=ax;
if (ay>maxa) maxa=ay; else if (ay<mina) mina=ay;
if (az>maxa) maxa=az; else if (az<mina) mina=az;
da= maxa-mina;
// update the running min/max for the g signals
if (gx>maxg) maxg=gx; else if (gx<ming) ming=gx;
if (gy>maxg) maxg=gy; else if (gy<ming) ming=gy;
if (gz>maxg) maxg=gz; else if (gz<ming) ming=gz;
dg= maxg-ming;
// accumulate the sensor data
raw_vector= ax;
raw_vector[(sampleId*signalNbr)+1]= ay;
raw_vector[(sampleId*signalNbr)+2]= az;
raw_vector[(sampleId*signalNbr)+3]= gx;
raw_vector[(sampleId*signalNbr)+4]= gy;
raw_vector[(sampleId*signalNbr)+5]= gz;
}
// normalize vector
for(int sampleId=0; sampleId < sampleNbr; sampleId++)
{
for(int i=0; i<3; i++)
{
vector= (((raw_vector - mina) * 255)/da) & 0x00FF;
vector= (((raw_vector - ming) * 255)/dg) & 0x00FF;
}
}
}
就是视频WIFI小车对吧 可以理解成探索神经元模块的视频WIFI小车:) 大人小孩在一起工作什么的就是那么的有意思。
欢迎你们继续在蘑菇云里玩耍。 神经元究竟是啥意思？ 好像是通过捕获神经上的生物电来驱动小车，然后进行前进后退什么的，挺有趣的。
这个我觉得很有意思，哈哈，如果机械臂能够和四轴结合起来更好玩儿吧。
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