use quaternions instead of MRPs

also use correct time propagation equation
disable the fused sensors when gyro is not present since
they were unusable in practice.

Change-Id: Iad797425784e67dc6c5690e97c71c583418cc5b5
This commit is contained in:
Mathias Agopian 2011-05-27 18:18:13 -07:00
parent 984826cc15
commit 3301542828
16 changed files with 366 additions and 548 deletions

View File

@ -8,7 +8,6 @@ LOCAL_SRC_FILES:= \
LinearAccelerationSensor.cpp \
OrientationSensor.cpp \
RotationVectorSensor.cpp \
SecondOrderLowPassFilter.cpp \
SensorDevice.cpp \
SensorFusion.cpp \
SensorInterface.cpp \

View File

@ -45,7 +45,7 @@ bool CorrectedGyroSensor::process(sensors_event_t* outEvent,
const sensors_event_t& event)
{
if (event.type == SENSOR_TYPE_GYROSCOPE) {
const vec3_t bias(mSensorFusion.getGyroBias() * mSensorFusion.getEstimatedRate());
const vec3_t bias(mSensorFusion.getGyroBias());
*outEvent = event;
outEvent->data[0] -= bias.x;
outEvent->data[1] -= bias.y;

View File

@ -24,15 +24,14 @@ namespace android {
// -----------------------------------------------------------------------
template <typename TYPE>
static inline TYPE sqr(TYPE x) {
return x*x;
}
static const float gyroSTDEV = 3.16e-4; // rad/s^3/2
static const float accSTDEV = 0.05f; // m/s^2 (measured 0.08 / CDD 0.05)
static const float magSTDEV = 0.5f; // uT (measured 0.7 / CDD 0.5)
static const float biasSTDEV = 3.16e-5; // rad/s^1/2 (guessed)
template <typename T>
static inline T clamp(T v) {
return v < 0 ? 0 : v;
}
static const float FREE_FALL_THRESHOLD = 0.981f;
// -----------------------------------------------------------------------
template <typename TYPE, size_t C, size_t R>
static mat<TYPE, R, R> scaleCovariance(
@ -71,33 +70,6 @@ static mat<TYPE, 3, 3> crossMatrix(const vec<TYPE, 3>& p, OTHER_TYPE diag) {
return r;
}
template <typename TYPE>
static mat<TYPE, 3, 3> MRPsToMatrix(const vec<TYPE, 3>& p) {
mat<TYPE, 3, 3> res(1);
const mat<TYPE, 3, 3> px(crossMatrix(p, 0));
const TYPE ptp(dot_product(p,p));
const TYPE t = 4/sqr(1+ptp);
res -= t * (1-ptp) * px;
res += t * 2 * sqr(px);
return res;
}
template <typename TYPE>
vec<TYPE, 3> matrixToMRPs(const mat<TYPE, 3, 3>& R) {
// matrix to MRPs
vec<TYPE, 3> q;
const float Hx = R[0].x;
const float My = R[1].y;
const float Az = R[2].z;
const float w = 1 / (1 + sqrtf( clamp( Hx + My + Az + 1) * 0.25f ));
q.x = sqrtf( clamp( Hx - My - Az + 1) * 0.25f ) * w;
q.y = sqrtf( clamp(-Hx + My - Az + 1) * 0.25f ) * w;
q.z = sqrtf( clamp(-Hx - My + Az + 1) * 0.25f ) * w;
q.x = copysignf(q.x, R[2].y - R[1].z);
q.y = copysignf(q.y, R[0].z - R[2].x);
q.z = copysignf(q.z, R[1].x - R[0].y);
return q;
}
template<typename TYPE, size_t SIZE>
class Covariance {
@ -128,11 +100,8 @@ public:
// -----------------------------------------------------------------------
Fusion::Fusion() {
// process noise covariance matrix
const float w1 = gyroSTDEV;
const float w2 = biasSTDEV;
Q[0] = w1*w1;
Q[1] = w2*w2;
Phi[0][1] = 0;
Phi[1][1] = 1;
Ba.x = 0;
Ba.y = 0;
@ -146,25 +115,46 @@ Fusion::Fusion() {
}
void Fusion::init() {
// initial estimate: E{ x(t0) }
x = 0;
// initial covariance: Var{ x(t0) }
P = 0;
mInitState = 0;
mGyroRate = 0;
mCount[0] = 0;
mCount[1] = 0;
mCount[2] = 0;
mData = 0;
}
void Fusion::initFusion(const vec4_t& q, float dT)
{
// initial estimate: E{ x(t0) }
x0 = q;
x1 = 0;
// process noise covariance matrix
// G = | -1 0 |
// | 0 1 |
const float v = gyroSTDEV;
const float u = biasSTDEV;
const float q00 = v*v*dT + 0.33333f*(dT*dT*dT)*u*u;
const float q10 = 0.5f*(dT*dT) *u*u;
const float q01 = q10;
const float q11 = u*u*dT;
GQGt[0][0] = q00;
GQGt[1][0] = -q10;
GQGt[0][1] = -q01;
GQGt[1][1] = q11;
// initial covariance: Var{ x(t0) }
P = 0;
}
bool Fusion::hasEstimate() const {
return (mInitState == (MAG|ACC|GYRO));
}
bool Fusion::checkInitComplete(int what, const vec3_t& d) {
if (mInitState == (MAG|ACC|GYRO))
bool Fusion::checkInitComplete(int what, const vec3_t& d, float dT) {
if (hasEstimate())
return true;
if (what == ACC) {
@ -176,7 +166,8 @@ bool Fusion::checkInitComplete(int what, const vec3_t& d) {
mCount[1]++;
mInitState |= MAG;
} else if (what == GYRO) {
mData[2] += d;
mGyroRate = dT;
mData[2] += d*dT;
mCount[2]++;
if (mCount[2] == 64) {
// 64 samples is good enough to estimate the gyro drift and
@ -199,37 +190,29 @@ bool Fusion::checkInitComplete(int what, const vec3_t& d) {
east *= 1/length(east);
vec3_t north(cross_product(up, east));
R << east << north << up;
x[0] = matrixToMRPs(R);
const vec4_t q = matrixToQuat(R);
// NOTE: we could try to use the average of the gyro data
// to estimate the initial bias, but this only works if
// the device is not moving. For now, we don't use that value
// and start with a bias of 0.
x[1] = 0;
// initial covariance
P = 0;
initFusion(q, mGyroRate);
}
return false;
}
void Fusion::handleGyro(const vec3_t& w, float dT) {
const vec3_t wdT(w * dT); // rad/s * s -> rad
if (!checkInitComplete(GYRO, wdT))
if (!checkInitComplete(GYRO, w, dT))
return;
predict(wdT);
predict(w, dT);
}
status_t Fusion::handleAcc(const vec3_t& a) {
if (length(a) < 0.981f)
// ignore acceleration data if we're close to free-fall
if (length(a) < FREE_FALL_THRESHOLD)
return BAD_VALUE;
if (!checkInitComplete(ACC, a))
return BAD_VALUE;
// ignore acceleration data if we're close to free-fall
const float l = 1/length(a);
update(a*l, Ba, accSTDEV*l);
return NO_ERROR;
@ -251,20 +234,6 @@ status_t Fusion::handleMag(const vec3_t& m) {
const float l = 1 / length(north);
north *= l;
#if 0
// in practice the magnetic-field sensor is so wrong
// that there is no point trying to use it to constantly
// correct the gyro. instead, we use the mag-sensor only when
// the device points north (just to give us a reference).
// We're hoping that it'll actually point north, if it doesn't
// we'll be offset, but at least the instantaneous posture
// of the device will be correct.
const float cos_30 = 0.8660254f;
if (dot_product(north, Bm) < cos_30)
return BAD_VALUE;
#endif
update(north, Bm, magSTDEV*l);
return NO_ERROR;
}
@ -273,7 +242,7 @@ bool Fusion::checkState(const vec3_t& v) {
if (isnanf(length(v))) {
LOGW("9-axis fusion diverged. reseting state.");
P = 0;
x[1] = 0;
x1 = 0;
mInitState = 0;
mCount[0] = 0;
mCount[1] = 0;
@ -284,145 +253,89 @@ bool Fusion::checkState(const vec3_t& v) {
return true;
}
vec3_t Fusion::getAttitude() const {
return x[0];
vec4_t Fusion::getAttitude() const {
return x0;
}
vec3_t Fusion::getBias() const {
return x[1];
return x1;
}
mat33_t Fusion::getRotationMatrix() const {
return MRPsToMatrix(x[0]);
return quatToMatrix(x0);
}
mat33_t Fusion::getF(const vec3_t& p) {
const float p0 = p.x;
const float p1 = p.y;
const float p2 = p.z;
// f(p, w)
const float p0p1 = p0*p1;
const float p0p2 = p0*p2;
const float p1p2 = p1*p2;
const float p0p0 = p0*p0;
const float p1p1 = p1*p1;
const float p2p2 = p2*p2;
const float pp = 0.5f * (1 - (p0p0 + p1p1 + p2p2));
mat33_t F;
F[0][0] = 0.5f*(p0p0 + pp);
F[0][1] = 0.5f*(p0p1 + p2);
F[0][2] = 0.5f*(p0p2 - p1);
F[1][0] = 0.5f*(p0p1 - p2);
F[1][1] = 0.5f*(p1p1 + pp);
F[1][2] = 0.5f*(p1p2 + p0);
F[2][0] = 0.5f*(p0p2 + p1);
F[2][1] = 0.5f*(p1p2 - p0);
F[2][2] = 0.5f*(p2p2 + pp);
mat34_t Fusion::getF(const vec4_t& q) {
mat34_t F;
F[0].x = q.w; F[1].x =-q.z; F[2].x = q.y;
F[0].y = q.z; F[1].y = q.w; F[2].y =-q.x;
F[0].z =-q.y; F[1].z = q.x; F[2].z = q.w;
F[0].w =-q.x; F[1].w =-q.y; F[2].w =-q.z;
return F;
}
mat33_t Fusion::getdFdp(const vec3_t& p, const vec3_t& we) {
void Fusion::predict(const vec3_t& w, float dT) {
const vec4_t q = x0;
const vec3_t b = x1;
const vec3_t we = w - b;
const vec4_t dq = getF(q)*((0.5f*dT)*we);
x0 = normalize_quat(q + dq);
// dF = | A = df/dp -F |
// | 0 0 |
// P(k+1) = F*P(k)*Ft + G*Q*Gt
mat33_t A;
A[0][0] = A[1][1] = A[2][2] = 0.5f * (p.x*we.x + p.y*we.y + p.z*we.z);
A[0][1] = 0.5f * (p.y*we.x - p.x*we.y - we.z);
A[0][2] = 0.5f * (p.z*we.x - p.x*we.z + we.y);
A[1][2] = 0.5f * (p.z*we.y - p.y*we.z - we.x);
A[1][0] = -A[0][1];
A[2][0] = -A[0][2];
A[2][1] = -A[1][2];
return A;
}
// Phi = | Phi00 Phi10 |
// | 0 1 |
const mat33_t I33(1);
const mat33_t I33dT(dT);
const mat33_t wx(crossMatrix(we, 0));
const mat33_t wx2(wx*wx);
const float lwedT = length(we)*dT;
const float ilwe = 1/length(we);
const float k0 = (1-cosf(lwedT))*(ilwe*ilwe);
const float k1 = sinf(lwedT);
void Fusion::predict(const vec3_t& w) {
// f(p, w)
vec3_t& p(x[0]);
Phi[0][0] = I33 - wx*(k1*ilwe) + wx2*k0;
Phi[1][0] = wx*k0 - I33dT - wx2*(ilwe*ilwe*ilwe)*(lwedT-k1);
// There is a discontinuity at 2.pi, to avoid it we need to switch to
// the shadow of p when pT.p gets too big.
const float ptp(dot_product(p,p));
if (ptp >= 2.0f) {
p = -p * (1/ptp);
}
const mat33_t F(getF(p));
// compute w with the bias correction:
// w_estimated = w - b_estimated
const vec3_t& b(x[1]);
const vec3_t we(w - b);
// prediction
const vec3_t dX(F*we);
if (!checkState(dX))
return;
p += dX;
const mat33_t A(getdFdp(p, we));
// G = | G0 0 | = | -F 0 |
// | 0 1 | | 0 1 |
// P += A*P + P*At + F*Q*Ft
const mat33_t AP(A*transpose(P[0][0]));
const mat33_t PAt(P[0][0]*transpose(A));
const mat33_t FPSt(F*transpose(P[1][0]));
const mat33_t PSFt(P[1][0]*transpose(F));
const mat33_t FQFt(scaleCovariance(F, Q[0]));
P[0][0] += AP + PAt - FPSt - PSFt + FQFt;
P[1][0] += A*P[1][0] - F*P[1][1];
P[1][1] += Q[1];
P = Phi*P*transpose(Phi) + GQGt;
}
void Fusion::update(const vec3_t& z, const vec3_t& Bi, float sigma) {
const vec3_t p(x[0]);
vec4_t q(x0);
// measured vector in body space: h(p) = A(p)*Bi
const mat33_t A(MRPsToMatrix(p));
const mat33_t A(quatToMatrix(q));
const vec3_t Bb(A*Bi);
// Sensitivity matrix H = dh(p)/dp
// H = [ L 0 ]
const float ptp(dot_product(p,p));
const mat33_t px(crossMatrix(p, 0.5f*(ptp-1)));
const mat33_t ppt(p*transpose(p));
const mat33_t L((8 / sqr(1+ptp))*crossMatrix(Bb, 0)*(ppt-px));
const mat33_t L(crossMatrix(Bb, 0));
// update...
// gain...
// K = P*Ht / [H*P*Ht + R]
vec<mat33_t, 2> K;
const mat33_t R(sigma*sigma);
const mat33_t S(scaleCovariance(L, P[0][0]) + R);
const mat33_t Si(invert(S));
const mat33_t LtSi(transpose(L)*Si);
vec<mat33_t, 2> K;
K[0] = P[0][0] * LtSi;
K[1] = transpose(P[1][0])*LtSi;
const vec3_t e(z - Bb);
const vec3_t K0e(K[0]*e);
const vec3_t K1e(K[1]*e);
if (!checkState(K0e))
return;
if (!checkState(K1e))
return;
x[0] += K0e;
x[1] += K1e;
// update...
// P -= K*H*P;
const mat33_t K0L(K[0] * L);
const mat33_t K1L(K[1] * L);
P[0][0] -= K0L*P[0][0];
P[1][1] -= K1L*P[1][0];
P[1][0] -= K0L*P[1][0];
P[0][1] = transpose(P[1][0]);
const vec3_t e(z - Bb);
const vec3_t dq(K[0]*e);
const vec3_t db(K[1]*e);
q += getF(q)*(0.5f*dq);
x0 = normalize_quat(q);
x1 += db;
}
// -----------------------------------------------------------------------

View File

@ -19,42 +19,39 @@
#include <utils/Errors.h>
#include "vec.h"
#include "quat.h"
#include "mat.h"
#include "vec.h"
namespace android {
typedef mat<float, 3, 4> mat34_t;
class Fusion {
/*
* the state vector is made of two sub-vector containing respectively:
* - modified Rodrigues parameters
* - the estimated gyro bias
*/
vec<vec3_t, 2> x;
quat_t x0;
vec3_t x1;
/*
* the predicated covariance matrix is made of 4 3x3 sub-matrices and it
* semi-definite positive.
*
* P = | P00 P10 | = | P00 P10 |
* | P01 P11 | | P10t Q1 |
* | P01 P11 | | P10t P11 |
*
* Since P01 = transpose(P10), the code below never calculates or
* stores P01. P11 is always equal to Q1, so we don't store it either.
* stores P01.
*/
mat<mat33_t, 2, 2> P;
/*
* the process noise covariance matrix is made of 2 3x3 sub-matrices
* Q0 encodes the attitude's noise
* Q1 encodes the bias' noise
* the process noise covariance matrix
*/
vec<mat33_t, 2> Q;
static const float gyroSTDEV = 1.0e-5; // rad/s (measured 1.2e-5)
static const float accSTDEV = 0.05f; // m/s^2 (measured 0.08 / CDD 0.05)
static const float magSTDEV = 0.5f; // uT (measured 0.7 / CDD 0.5)
static const float biasSTDEV = 2e-9; // rad/s^2 (guessed)
mat<mat33_t, 2, 2> GQGt;
public:
Fusion();
@ -62,23 +59,25 @@ public:
void handleGyro(const vec3_t& w, float dT);
status_t handleAcc(const vec3_t& a);
status_t handleMag(const vec3_t& m);
vec3_t getAttitude() const;
vec4_t getAttitude() const;
vec3_t getBias() const;
mat33_t getRotationMatrix() const;
bool hasEstimate() const;
private:
mat<mat33_t, 2, 2> Phi;
vec3_t Ba, Bm;
uint32_t mInitState;
float mGyroRate;
vec<vec3_t, 3> mData;
size_t mCount[3];
enum { ACC=0x1, MAG=0x2, GYRO=0x4 };
bool checkInitComplete(int, const vec3_t&);
bool checkInitComplete(int, const vec3_t& w, float d = 0);
void initFusion(const vec4_t& q0, float dT);
bool checkState(const vec3_t& v);
void predict(const vec3_t& w);
void predict(const vec3_t& w, float dT);
void update(const vec3_t& z, const vec3_t& Bi, float sigma);
static mat33_t getF(const vec3_t& p);
static mat33_t getdFdp(const vec3_t& p, const vec3_t& we);
static mat34_t getF(const vec4_t& p);
};
}; // namespace android

View File

@ -31,10 +31,7 @@ namespace android {
GravitySensor::GravitySensor(sensor_t const* list, size_t count)
: mSensorDevice(SensorDevice::getInstance()),
mSensorFusion(SensorFusion::getInstance()),
mAccTime(0),
mLowPass(M_SQRT1_2, 1.5f),
mX(mLowPass), mY(mLowPass), mZ(mLowPass)
mSensorFusion(SensorFusion::getInstance())
{
for (size_t i=0 ; i<count ; i++) {
if (list[i].type == SENSOR_TYPE_ACCELEROMETER) {
@ -50,30 +47,14 @@ bool GravitySensor::process(sensors_event_t* outEvent,
const static double NS2S = 1.0 / 1000000000.0;
if (event.type == SENSOR_TYPE_ACCELEROMETER) {
vec3_t g;
if (mSensorFusion.hasGyro()) {
if (!mSensorFusion.hasEstimate())
return false;
const mat33_t R(mSensorFusion.getRotationMatrix());
// FIXME: we need to estimate the length of gravity because
// the accelerometer may have a small scaling error. This
// translates to an offset in the linear-acceleration sensor.
g = R[2] * GRAVITY_EARTH;
} else {
const double now = event.timestamp * NS2S;
if (mAccTime == 0) {
g.x = mX.init(event.acceleration.x);
g.y = mY.init(event.acceleration.y);
g.z = mZ.init(event.acceleration.z);
} else {
double dT = now - mAccTime;
mLowPass.setSamplingPeriod(dT);
g.x = mX(event.acceleration.x);
g.y = mY(event.acceleration.y);
g.z = mZ(event.acceleration.z);
}
g *= (GRAVITY_EARTH / length(g));
mAccTime = now;
}
if (!mSensorFusion.hasEstimate())
return false;
const mat33_t R(mSensorFusion.getRotationMatrix());
// FIXME: we need to estimate the length of gravity because
// the accelerometer may have a small scaling error. This
// translates to an offset in the linear-acceleration sensor.
g = R[2] * GRAVITY_EARTH;
*outEvent = event;
outEvent->data[0] = g.x;
outEvent->data[1] = g.y;
@ -86,42 +67,24 @@ bool GravitySensor::process(sensors_event_t* outEvent,
}
status_t GravitySensor::activate(void* ident, bool enabled) {
status_t err;
if (mSensorFusion.hasGyro()) {
err = mSensorFusion.activate(this, enabled);
} else {
err = mSensorDevice.activate(this, mAccelerometer.getHandle(), enabled);
if (err == NO_ERROR) {
if (enabled) {
mAccTime = 0;
}
}
}
return err;
return mSensorFusion.activate(this, enabled);
}
status_t GravitySensor::setDelay(void* ident, int handle, int64_t ns)
{
if (mSensorFusion.hasGyro()) {
return mSensorFusion.setDelay(this, ns);
} else {
return mSensorDevice.setDelay(this, mAccelerometer.getHandle(), ns);
}
status_t GravitySensor::setDelay(void* ident, int handle, int64_t ns) {
return mSensorFusion.setDelay(this, ns);
}
Sensor GravitySensor::getSensor() const {
sensor_t hwSensor;
hwSensor.name = "Gravity Sensor";
hwSensor.vendor = "Google Inc.";
hwSensor.version = mSensorFusion.hasGyro() ? 3 : 2;
hwSensor.version = 3;
hwSensor.handle = '_grv';
hwSensor.type = SENSOR_TYPE_GRAVITY;
hwSensor.maxRange = GRAVITY_EARTH * 2;
hwSensor.resolution = mAccelerometer.getResolution();
hwSensor.power = mSensorFusion.hasGyro() ?
mSensorFusion.getPowerUsage() : mAccelerometer.getPowerUsage();
hwSensor.minDelay = mSensorFusion.hasGyro() ?
mSensorFusion.getMinDelay() : mAccelerometer.getMinDelay();
hwSensor.power = mSensorFusion.getPowerUsage();
hwSensor.minDelay = mSensorFusion.getMinDelay();
Sensor sensor(&hwSensor);
return sensor;
}

View File

@ -23,7 +23,6 @@
#include <gui/Sensor.h>
#include "SensorInterface.h"
#include "SecondOrderLowPassFilter.h"
// ---------------------------------------------------------------------------
namespace android {
@ -36,10 +35,6 @@ class GravitySensor : public SensorInterface {
SensorDevice& mSensorDevice;
SensorFusion& mSensorFusion;
Sensor mAccelerometer;
double mAccTime;
SecondOrderLowPassFilter mLowPass;
CascadedBiquadFilter<float> mX, mY, mZ;
public:
GravitySensor(sensor_t const* list, size_t count);

View File

@ -50,9 +50,10 @@ bool OrientationSensor::process(sensors_event_t* outEvent,
g[0] += 360;
*outEvent = event;
outEvent->data[0] = g.x;
outEvent->data[1] = g.y;
outEvent->data[2] = g.z;
outEvent->orientation.azimuth = g.x;
outEvent->orientation.pitch = g.y;
outEvent->orientation.roll = g.z;
outEvent->orientation.status = SENSOR_STATUS_ACCURACY_HIGH;
outEvent->sensor = '_ypr';
outEvent->type = SENSOR_TYPE_ORIENTATION;
return true;

View File

@ -27,11 +27,6 @@
namespace android {
// ---------------------------------------------------------------------------
template <typename T>
static inline T clamp(T v) {
return v < 0 ? 0 : v;
}
RotationVectorSensor::RotationVectorSensor()
: mSensorDevice(SensorDevice::getInstance()),
mSensorFusion(SensorFusion::getInstance())
@ -43,29 +38,12 @@ bool RotationVectorSensor::process(sensors_event_t* outEvent,
{
if (event.type == SENSOR_TYPE_ACCELEROMETER) {
if (mSensorFusion.hasEstimate()) {
const mat33_t R(mSensorFusion.getRotationMatrix());
// matrix to rotation vector (normalized quaternion)
const float Hx = R[0].x;
const float My = R[1].y;
const float Az = R[2].z;
float qw = sqrtf( clamp( Hx + My + Az + 1) * 0.25f );
float qx = sqrtf( clamp( Hx - My - Az + 1) * 0.25f );
float qy = sqrtf( clamp(-Hx + My - Az + 1) * 0.25f );
float qz = sqrtf( clamp(-Hx - My + Az + 1) * 0.25f );
qx = copysignf(qx, R[2].y - R[1].z);
qy = copysignf(qy, R[0].z - R[2].x);
qz = copysignf(qz, R[1].x - R[0].y);
// this quaternion is guaranteed to be normalized, by construction
// of the rotation matrix.
const vec4_t q(mSensorFusion.getAttitude());
*outEvent = event;
outEvent->data[0] = qx;
outEvent->data[1] = qy;
outEvent->data[2] = qz;
outEvent->data[3] = qw;
outEvent->data[0] = q.x;
outEvent->data[1] = q.y;
outEvent->data[2] = q.z;
outEvent->data[3] = q.w;
outEvent->sensor = '_rov';
outEvent->type = SENSOR_TYPE_ROTATION_VECTOR;
return true;
@ -86,7 +64,7 @@ Sensor RotationVectorSensor::getSensor() const {
sensor_t hwSensor;
hwSensor.name = "Rotation Vector Sensor";
hwSensor.vendor = "Google Inc.";
hwSensor.version = mSensorFusion.hasGyro() ? 3 : 2;
hwSensor.version = 3;
hwSensor.handle = '_rov';
hwSensor.type = SENSOR_TYPE_ROTATION_VECTOR;
hwSensor.maxRange = 1;
@ -97,6 +75,55 @@ Sensor RotationVectorSensor::getSensor() const {
return sensor;
}
// ---------------------------------------------------------------------------
GyroDriftSensor::GyroDriftSensor()
: mSensorDevice(SensorDevice::getInstance()),
mSensorFusion(SensorFusion::getInstance())
{
}
bool GyroDriftSensor::process(sensors_event_t* outEvent,
const sensors_event_t& event)
{
if (event.type == SENSOR_TYPE_ACCELEROMETER) {
if (mSensorFusion.hasEstimate()) {
const vec3_t b(mSensorFusion.getGyroBias());
*outEvent = event;
outEvent->data[0] = b.x;
outEvent->data[1] = b.y;
outEvent->data[2] = b.z;
outEvent->sensor = '_gbs';
outEvent->type = SENSOR_TYPE_ACCELEROMETER;
return true;
}
}
return false;
}
status_t GyroDriftSensor::activate(void* ident, bool enabled) {
return mSensorFusion.activate(this, enabled);
}
status_t GyroDriftSensor::setDelay(void* ident, int handle, int64_t ns) {
return mSensorFusion.setDelay(this, ns);
}
Sensor GyroDriftSensor::getSensor() const {
sensor_t hwSensor;
hwSensor.name = "Gyroscope Bias (debug)";
hwSensor.vendor = "Google Inc.";
hwSensor.version = 1;
hwSensor.handle = '_gbs';
hwSensor.type = SENSOR_TYPE_ACCELEROMETER;
hwSensor.maxRange = 1;
hwSensor.resolution = 1.0f / (1<<24);
hwSensor.power = mSensorFusion.getPowerUsage();
hwSensor.minDelay = mSensorFusion.getMinDelay();
Sensor sensor(&hwSensor);
return sensor;
}
// ---------------------------------------------------------------------------
}; // namespace android

View File

@ -24,7 +24,6 @@
#include "SensorDevice.h"
#include "SensorInterface.h"
#include "SecondOrderLowPassFilter.h"
#include "Fusion.h"
#include "SensorFusion.h"
@ -47,6 +46,20 @@ public:
virtual bool isVirtual() const { return true; }
};
class GyroDriftSensor : public SensorInterface {
SensorDevice& mSensorDevice;
SensorFusion& mSensorFusion;
public:
GyroDriftSensor();
virtual bool process(sensors_event_t* outEvent,
const sensors_event_t& event);
virtual status_t activate(void* ident, bool enabled);
virtual status_t setDelay(void* ident, int handle, int64_t ns);
virtual Sensor getSensor() const;
virtual bool isVirtual() const { return true; }
};
// ---------------------------------------------------------------------------
}; // namespace android

View File

@ -1,103 +0,0 @@
/*
* Copyright (C) 2010 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <stdint.h>
#include <sys/types.h>
#include <math.h>
#include <cutils/log.h>
#include "SecondOrderLowPassFilter.h"
#include "vec.h"
// ---------------------------------------------------------------------------
namespace android {
// ---------------------------------------------------------------------------
SecondOrderLowPassFilter::SecondOrderLowPassFilter(float Q, float fc)
: iQ(1.0f / Q), fc(fc)
{
}
void SecondOrderLowPassFilter::setSamplingPeriod(float dT)
{
K = tanf(float(M_PI) * fc * dT);
iD = 1.0f / (K*K + K*iQ + 1);
a0 = K*K*iD;
a1 = 2.0f * a0;
b1 = 2.0f*(K*K - 1)*iD;
b2 = (K*K - K*iQ + 1)*iD;
}
// ---------------------------------------------------------------------------
template<typename T>
BiquadFilter<T>::BiquadFilter(const SecondOrderLowPassFilter& s)
: s(s)
{
}
template<typename T>
T BiquadFilter<T>::init(const T& x)
{
x1 = x2 = x;
y1 = y2 = x;
return x;
}
template<typename T>
T BiquadFilter<T>::operator()(const T& x)
{
T y = (x + x2)*s.a0 + x1*s.a1 - y1*s.b1 - y2*s.b2;
x2 = x1;
y2 = y1;
x1 = x;
y1 = y;
return y;
}
// ---------------------------------------------------------------------------
template<typename T>
CascadedBiquadFilter<T>::CascadedBiquadFilter(const SecondOrderLowPassFilter& s)
: mA(s), mB(s)
{
}
template<typename T>
T CascadedBiquadFilter<T>::init(const T& x)
{
mA.init(x);
mB.init(x);
return x;
}
template<typename T>
T CascadedBiquadFilter<T>::operator()(const T& x)
{
return mB(mA(x));
}
// ---------------------------------------------------------------------------
template class BiquadFilter<float>;
template class CascadedBiquadFilter<float>;
template class BiquadFilter<vec3_t>;
template class CascadedBiquadFilter<vec3_t>;
// ---------------------------------------------------------------------------
}; // namespace android

View File

@ -1,77 +0,0 @@
/*
* Copyright (C) 2010 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef ANDROID_SECOND_ORDER_LOW_PASS_FILTER_H
#define ANDROID_SECOND_ORDER_LOW_PASS_FILTER_H
#include <stdint.h>
#include <sys/types.h>
// ---------------------------------------------------------------------------
namespace android {
// ---------------------------------------------------------------------------
template<typename T>
class BiquadFilter;
/*
* State of a 2nd order low-pass IIR filter
*/
class SecondOrderLowPassFilter {
template<typename T>
friend class BiquadFilter;
float iQ, fc;
float K, iD;
float a0, a1;
float b1, b2;
public:
SecondOrderLowPassFilter(float Q, float fc);
void setSamplingPeriod(float dT);
};
/*
* Implements a Biquad IIR filter
*/
template<typename T>
class BiquadFilter {
T x1, x2;
T y1, y2;
const SecondOrderLowPassFilter& s;
public:
BiquadFilter(const SecondOrderLowPassFilter& s);
T init(const T& in);
T operator()(const T& in);
};
/*
* Two cascaded biquad IIR filters
* (4-poles IIR)
*/
template<typename T>
class CascadedBiquadFilter {
BiquadFilter<T> mA;
BiquadFilter<T> mB;
public:
CascadedBiquadFilter(const SecondOrderLowPassFilter& s);
T init(const T& in);
T operator()(const T& in);
};
// ---------------------------------------------------------------------------
}; // namespace android
#endif // ANDROID_SECOND_ORDER_LOW_PASS_FILTER_H

View File

@ -25,9 +25,7 @@ ANDROID_SINGLETON_STATIC_INSTANCE(SensorFusion)
SensorFusion::SensorFusion()
: mSensorDevice(SensorDevice::getInstance()),
mEnabled(false), mHasGyro(false), mGyroTime(0), mRotationMatrix(1),
mLowPass(M_SQRT1_2, 1.0f), mAccData(mLowPass),
mFilteredMag(0.0f), mFilteredAcc(0.0f)
mEnabled(false), mGyroTime(0)
{
sensor_t const* list;
size_t count = mSensorDevice.getSensorList(&list);
@ -42,55 +40,32 @@ SensorFusion::SensorFusion()
mGyro = Sensor(list + i);
// 200 Hz for gyro events is a good compromise between precision
// and power/cpu usage.
mTargetDelayNs = 1000000000LL/200;
mGyroRate = 1000000000.0f / mTargetDelayNs;
mHasGyro = true;
mGyroRate = 200;
mTargetDelayNs = 1000000000LL/mGyroRate;
}
}
mFusion.init();
mAccData.init(vec3_t(0.0f));
}
void SensorFusion::process(const sensors_event_t& event) {
if (event.type == SENSOR_TYPE_GYROSCOPE && mHasGyro) {
if (event.type == SENSOR_TYPE_GYROSCOPE) {
if (mGyroTime != 0) {
const float dT = (event.timestamp - mGyroTime) / 1000000000.0f;
const float freq = 1 / dT;
const float alpha = 2 / (2 + dT); // 2s time-constant
mGyroRate = mGyroRate*alpha + freq*(1 - alpha);
if (freq >= 100 && freq<1000) { // filter values obviously wrong
const float alpha = 1 / (1 + dT); // 1s time-constant
mGyroRate = freq + (mGyroRate - freq)*alpha;
}
}
mGyroTime = event.timestamp;
mFusion.handleGyro(vec3_t(event.data), 1.0f/mGyroRate);
} else if (event.type == SENSOR_TYPE_MAGNETIC_FIELD) {
const vec3_t mag(event.data);
if (mHasGyro) {
mFusion.handleMag(mag);
} else {
const float l(length(mag));
if (l>5 && l<100) {
mFilteredMag = mag * (1/l);
}
}
mFusion.handleMag(mag);
} else if (event.type == SENSOR_TYPE_ACCELEROMETER) {
const vec3_t acc(event.data);
if (mHasGyro) {
mFusion.handleAcc(acc);
mRotationMatrix = mFusion.getRotationMatrix();
} else {
const float l(length(acc));
if (l > 0.981f) {
// remove the linear-acceleration components
mFilteredAcc = mAccData(acc * (1/l));
}
if (length(mFilteredAcc)>0 && length(mFilteredMag)>0) {
vec3_t up(mFilteredAcc);
vec3_t east(cross_product(mFilteredMag, up));
east *= 1/length(east);
vec3_t north(cross_product(up, east));
mRotationMatrix << east << north << up;
}
}
mFusion.handleAcc(acc);
mAttitude = mFusion.getAttitude();
}
}
@ -116,40 +91,31 @@ status_t SensorFusion::activate(void* ident, bool enabled) {
mSensorDevice.activate(ident, mAcc.getHandle(), enabled);
mSensorDevice.activate(ident, mMag.getHandle(), enabled);
if (mHasGyro) {
mSensorDevice.activate(ident, mGyro.getHandle(), enabled);
}
mSensorDevice.activate(ident, mGyro.getHandle(), enabled);
const bool newState = mClients.size() != 0;
if (newState != mEnabled) {
mEnabled = newState;
if (newState) {
mFusion.init();
mGyroTime = 0;
}
}
return NO_ERROR;
}
status_t SensorFusion::setDelay(void* ident, int64_t ns) {
if (mHasGyro) {
mSensorDevice.setDelay(ident, mAcc.getHandle(), ns);
mSensorDevice.setDelay(ident, mMag.getHandle(), ms2ns(20));
mSensorDevice.setDelay(ident, mGyro.getHandle(), mTargetDelayNs);
} else {
const static double NS2S = 1.0 / 1000000000.0;
mSensorDevice.setDelay(ident, mAcc.getHandle(), ns);
mSensorDevice.setDelay(ident, mMag.getHandle(), max(ns, mMag.getMinDelayNs()));
mLowPass.setSamplingPeriod(ns*NS2S);
}
mSensorDevice.setDelay(ident, mAcc.getHandle(), ns);
mSensorDevice.setDelay(ident, mMag.getHandle(), ms2ns(20));
mSensorDevice.setDelay(ident, mGyro.getHandle(), mTargetDelayNs);
return NO_ERROR;
}
float SensorFusion::getPowerUsage() const {
float power = mAcc.getPowerUsage() + mMag.getPowerUsage();
if (mHasGyro) {
power += mGyro.getPowerUsage();
}
float power = mAcc.getPowerUsage() +
mMag.getPowerUsage() +
mGyro.getPowerUsage();
return power;
}
@ -159,17 +125,17 @@ int32_t SensorFusion::getMinDelay() const {
void SensorFusion::dump(String8& result, char* buffer, size_t SIZE) {
const Fusion& fusion(mFusion);
snprintf(buffer, SIZE, "Fusion (%s) %s (%d clients), gyro-rate=%7.2fHz, "
"MRPS=< %g, %g, %g > (%g), "
"BIAS=< %g, %g, %g >\n",
mHasGyro ? "9-axis" : "6-axis",
snprintf(buffer, SIZE, "9-axis fusion %s (%d clients), gyro-rate=%7.2fHz, "
"q=< %g, %g, %g, %g > (%g), "
"b=< %g, %g, %g >\n",
mEnabled ? "enabled" : "disabled",
mClients.size(),
mGyroRate,
fusion.getAttitude().x,
fusion.getAttitude().y,
fusion.getAttitude().z,
dot_product(fusion.getAttitude(), fusion.getAttitude()),
fusion.getAttitude().w,
length(fusion.getAttitude()),
fusion.getBias().x,
fusion.getBias().y,
fusion.getBias().z);

View File

@ -27,7 +27,6 @@
#include <gui/Sensor.h>
#include "Fusion.h"
#include "SecondOrderLowPassFilter.h"
// ---------------------------------------------------------------------------
@ -45,15 +44,10 @@ class SensorFusion : public Singleton<SensorFusion> {
Sensor mGyro;
Fusion mFusion;
bool mEnabled;
bool mHasGyro;
float mGyroRate;
nsecs_t mTargetDelayNs;
nsecs_t mGyroTime;
mat33_t mRotationMatrix;
SecondOrderLowPassFilter mLowPass;
BiquadFilter<vec3_t> mAccData;
vec3_t mFilteredMag;
vec3_t mFilteredAcc;
vec4_t mAttitude;
SortedVector<void*> mClients;
SensorFusion();
@ -62,9 +56,9 @@ public:
void process(const sensors_event_t& event);
bool isEnabled() const { return mEnabled; }
bool hasGyro() const { return mHasGyro; }
bool hasEstimate() const { return !mHasGyro || mFusion.hasEstimate(); }
mat33_t getRotationMatrix() const { return mRotationMatrix; }
bool hasEstimate() const { return mFusion.hasEstimate(); }
mat33_t getRotationMatrix() const { return mFusion.getRotationMatrix(); }
vec4_t getAttitude() const { return mAttitude; }
vec3_t getGyroBias() const { return mFusion.getBias(); }
float getEstimatedRate() const { return mGyroRate; }

View File

@ -18,6 +18,8 @@
#include <math.h>
#include <sys/types.h>
#include <cutils/properties.h>
#include <utils/SortedVector.h>
#include <utils/KeyedVector.h>
#include <utils/threads.h>
@ -46,6 +48,16 @@
namespace android {
// ---------------------------------------------------------------------------
/*
* Notes:
*
* - what about a gyro-corrected magnetic-field sensor?
* - option to "hide" the HAL sensors
* - run mag sensor from time to time to force calibration
* - gravity sensor length is wrong (=> drift in linear-acc sensor)
*
*/
SensorService::SensorService()
: mDump("android.permission.DUMP"),
mInitCheck(NO_INIT)
@ -59,6 +71,7 @@ void SensorService::onFirstRef()
SensorDevice& dev(SensorDevice::getInstance());
if (dev.initCheck() == NO_ERROR) {
bool hasGyro = false;
uint32_t virtualSensorsNeeds =
(1<<SENSOR_TYPE_GRAVITY) |
(1<<SENSOR_TYPE_LINEAR_ACCELERATION) |
@ -69,6 +82,9 @@ void SensorService::onFirstRef()
for (int i=0 ; i<count ; i++) {
registerSensor( new HardwareSensor(list[i]) );
switch (list[i].type) {
case SENSOR_TYPE_GYROSCOPE:
hasGyro = true;
break;
case SENSOR_TYPE_GRAVITY:
case SENSOR_TYPE_LINEAR_ACCELERATION:
case SENSOR_TYPE_ROTATION_VECTOR:
@ -82,21 +98,26 @@ void SensorService::onFirstRef()
// registered)
const SensorFusion& fusion(SensorFusion::getInstance());
// Always instantiate Android's virtual sensors. Since they are
// instantiated behind sensors from the HAL, they won't
// interfere with applications, unless they looks specifically
// for them (by name).
if (hasGyro) {
// Always instantiate Android's virtual sensors. Since they are
// instantiated behind sensors from the HAL, they won't
// interfere with applications, unless they looks specifically
// for them (by name).
registerVirtualSensor( new RotationVectorSensor() );
registerVirtualSensor( new GravitySensor(list, count) );
registerVirtualSensor( new LinearAccelerationSensor(list, count) );
registerVirtualSensor( new RotationVectorSensor() );
registerVirtualSensor( new GravitySensor(list, count) );
registerVirtualSensor( new LinearAccelerationSensor(list, count) );
// if we have a gyro, we have the option of enabling these
// "better" orientation and gyro sensors
if (fusion.hasGyro()) {
// FIXME: OrientationSensor buggy when not pointing north
// these are optional
registerVirtualSensor( new OrientationSensor() );
registerVirtualSensor( new CorrectedGyroSensor(list, count) );
// virtual debugging sensors...
char value[PROPERTY_VALUE_MAX];
property_get("debug.sensors", value, "0");
if (atoi(value)) {
registerVirtualSensor( new GyroDriftSensor() );
}
}
run("SensorService", PRIORITY_URGENT_DISPLAY);

View File

@ -0,0 +1,98 @@
/*
* Copyright (C) 2011 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef ANDROID_QUAT_H
#define ANDROID_QUAT_H
#include <math.h>
#include "vec.h"
#include "mat.h"
// -----------------------------------------------------------------------
namespace android {
// -----------------------------------------------------------------------
template <typename TYPE>
mat<TYPE, 3, 3> quatToMatrix(const vec<TYPE, 4>& q) {
mat<TYPE, 3, 3> R;
TYPE q0(q.w);
TYPE q1(q.x);
TYPE q2(q.y);
TYPE q3(q.z);
TYPE sq_q1 = 2 * q1 * q1;
TYPE sq_q2 = 2 * q2 * q2;
TYPE sq_q3 = 2 * q3 * q3;
TYPE q1_q2 = 2 * q1 * q2;
TYPE q3_q0 = 2 * q3 * q0;
TYPE q1_q3 = 2 * q1 * q3;
TYPE q2_q0 = 2 * q2 * q0;
TYPE q2_q3 = 2 * q2 * q3;
TYPE q1_q0 = 2 * q1 * q0;
R[0][0] = 1 - sq_q2 - sq_q3;
R[0][1] = q1_q2 - q3_q0;
R[0][2] = q1_q3 + q2_q0;
R[1][0] = q1_q2 + q3_q0;
R[1][1] = 1 - sq_q1 - sq_q3;
R[1][2] = q2_q3 - q1_q0;
R[2][0] = q1_q3 - q2_q0;
R[2][1] = q2_q3 + q1_q0;
R[2][2] = 1 - sq_q1 - sq_q2;
return R;
}
template <typename TYPE>
vec<TYPE, 4> matrixToQuat(const mat<TYPE, 3, 3>& R) {
// matrix to quaternion
struct {
inline TYPE operator()(TYPE v) {
return v < 0 ? 0 : v;
}
} clamp;
vec<TYPE, 4> q;
const float Hx = R[0].x;
const float My = R[1].y;
const float Az = R[2].z;
q.x = sqrtf( clamp( Hx - My - Az + 1) * 0.25f );
q.y = sqrtf( clamp(-Hx + My - Az + 1) * 0.25f );
q.z = sqrtf( clamp(-Hx - My + Az + 1) * 0.25f );
q.w = sqrtf( clamp( Hx + My + Az + 1) * 0.25f );
q.x = copysignf(q.x, R[2].y - R[1].z);
q.y = copysignf(q.y, R[0].z - R[2].x);
q.z = copysignf(q.z, R[1].x - R[0].y);
// guaranteed to be unit-quaternion
return q;
}
template <typename TYPE>
vec<TYPE, 4> normalize_quat(const vec<TYPE, 4>& q) {
vec<TYPE, 4> r(q);
if (r.w < 0) {
r = -r;
}
return normalize(r);
}
// -----------------------------------------------------------------------
typedef vec4_t quat_t;
// -----------------------------------------------------------------------
}; // namespace android
#endif /* ANDROID_QUAT_H */

View File

@ -207,6 +207,15 @@ TYPE PURE length(const V<TYPE, SIZE>& v) {
return sqrt(dot_product(v, v));
}
template <
template<typename T, size_t S> class V,
typename TYPE,
size_t SIZE
>
V<TYPE, SIZE> PURE normalize(const V<TYPE, SIZE>& v) {
return v * (1/length(v));
}
template <
template<typename T, size_t S> class VLHS,
template<typename T, size_t S> class VRHS,