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Revert "improve sensor fusion" -- DO NOT MERGE

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This reverts commit bdf277355d.
This reverts commit dc5b63e40e.

it might be responsible for a regression that makes the
rotation vector spin.

Bug: 7267330
Change-Id: Ifb10e933537e70c1d85a7ba73a7e3ae59002fe62
This commit is contained in:
Mathias Agopian 2012-10-01 20:23:55 -07:00
parent 0c2a25c11c
commit 2ae7bec770
1 changed files with 9 additions and 56 deletions
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65
services/sensorservice/Fusion.cpp
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@ -201,15 +201,15 @@ void Fusion::initFusion(const vec4_t& q, float dT)
// q11 = su^2.dt
//
const float dT2 = dT*dT;
const float dT3 = dT2*dT;
// variance of integrated output at 1/dT Hz (random drift)
const float q00 = gyroVAR * dT + 0.33333f * biasVAR * dT3;
// variance of integrated output at 1/dT Hz
// (random drift)
const float q00 = gyroVAR * dT;
// variance of drift rate ramp
const float q11 = biasVAR * dT;
const float q10 = 0.5f * biasVAR * dT2;
const float u = q11 / dT;
const float q10 = 0.5f*u*dT*dT;
const float q01 = q10;
GQGt[0][0] = q00; // rad^2
@ -220,22 +220,6 @@ void Fusion::initFusion(const vec4_t& q, float dT)
// initial covariance: Var{ x(t0) }
// TODO: initialize P correctly
P = 0;
// it is unclear how to set the initial covariance. It does affect
// how quickly the fusion converges. Experimentally it would take
// about 10 seconds at 200 Hz to estimate the gyro-drift with an
// initial covariance of 0, and about a second with an initial covariance
// of about 1 deg/s.
const float covv = 0;
const float covu = 0.5f * (float(M_PI) / 180);
mat33_t& Pv = P[0][0];
Pv[0][0] = covv;
Pv[1][1] = covv;
Pv[2][2] = covv;
mat33_t& Pu = P[1][1];
Pu[0][0] = covu;
Pu[1][1] = covu;
Pu[2][2] = covu;
}
bool Fusion::hasEstimate() const {
@ -373,11 +357,6 @@ mat33_t Fusion::getRotationMatrix() const {
mat34_t Fusion::getF(const vec4_t& q) {
mat34_t F;
// This is used to compute the derivative of q
// F = | [q.xyz]x |
// | -q.xyz |
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;
@ -389,18 +368,10 @@ 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);
// q(k+1) = O(we)*q(k)
// --------------------
//
// O(w) = | cos(0.5*||w||*dT)*I33 - [psi]x psi |
// | -psi' cos(0.5*||w||*dT) |
//
// psi = sin(0.5*||w||*dT)*w / ||w||
//
//
// P(k+1) = Phi(k)*P(k)*Phi(k)' + G*Q(k)*G'
// ----------------------------------------
//
// G = | -I33 0 |
// | 0 I33 |
@ -421,26 +392,13 @@ void Fusion::predict(const vec3_t& w, float dT) {
const mat33_t wx(crossMatrix(we, 0));
const mat33_t wx2(wx*wx);
const float lwedT = length(we)*dT;
const float hlwedT = 0.5f*lwedT;
const float ilwe = 1/length(we);
const float k0 = (1-cosf(lwedT))*(ilwe*ilwe);
const float k1 = sinf(lwedT);
const float k2 = cosf(hlwedT);
const vec3_t psi(sinf(hlwedT)*ilwe*we);
const mat33_t O33(crossMatrix(-psi, k2));
mat44_t O;
O[0].xyz = O33[0]; O[0].w = -psi.x;
O[1].xyz = O33[1]; O[1].w = -psi.y;
O[2].xyz = O33[2]; O[2].w = -psi.z;
O[3].xyz = psi; O[3].w = k2;
Phi[0][0] = I33 - wx*(k1*ilwe) + wx2*k0;
Phi[1][0] = wx*k0 - I33dT - wx2*(ilwe*ilwe*ilwe)*(lwedT-k1);
x0 = O*q;
if (x0.w < 0)
x0 = -x0;
P = Phi*P*transpose(Phi) + GQGt;
checkState();
@ -467,12 +425,7 @@ void Fusion::update(const vec3_t& z, const vec3_t& Bi, float sigma) {
K[1] = transpose(P[1][0])*LtSi;
// update...
// P = (I-K*H) * P
// P -= K*H*P
// | K0 | * | L 0 | * P = | K0*L 0 | * | P00 P10 | = | K0*L*P00 K0*L*P10 |
// | K1 | | K1*L 0 | | P01 P11 | | K1*L*P00 K1*L*P10 |
// Note: the Joseph form is numerically more stable and given by:
// P = (I-KH) * P * (I-KH)' + K*R*R'
// 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];