示例#1
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// rotate and derivatives
inline Point2 rotate_(const Rot2 & R, const Point2& p) {return R.rotate(p);}
示例#2
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int main() {

	/**
	 *    Step 1: Create a factor to express a unary constraint
	 * The "prior" in this case is the measurement from a sensor,
	 * with a model of the noise on the measurement.
	 *
	 * The "Key" created here is a label used to associate parts of the
	 * state (stored in "RotValues") with particular factors.  They require
	 * an index to allow for lookup, and should be unique.
	 *
	 * In general, creating a factor requires:
	 *  - A key or set of keys labeling the variables that are acted upon
	 *  - A measurement value
	 *  - A measurement model with the correct dimensionality for the factor
	 */
	Rot2 prior = Rot2::fromAngle(30 * degree);
	prior.print("goal angle");
	noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(1, 1 * degree);
	Symbol key('x',1);
	PriorFactor<Rot2> factor(key, prior, model);

	/**
	 *    Step 2: Create a graph container and add the factor to it
	 * Before optimizing, all factors need to be added to a Graph container,
	 * which provides the necessary top-level functionality for defining a
	 * system of constraints.
	 *
	 * In this case, there is only one factor, but in a practical scenario,
	 * many more factors would be added.
	 */
	NonlinearFactorGraph graph;
	graph.add(factor);
	graph.print("full graph");

	/**
	 *    Step 3: Create an initial estimate
	 * An initial estimate of the solution for the system is necessary to
	 * start optimization.  This system state is the "RotValues" structure,
	 * which is similar in structure to a STL map, in that it maps
	 * keys (the label created in step 1) to specific values.
	 *
	 * The initial estimate provided to optimization will be used as
	 * a linearization point for optimization, so it is important that
	 * all of the variables in the graph have a corresponding value in
	 * this structure.
	 *
	 * The interface to all RotValues types is the same, it only depends
	 * on the type of key used to find the appropriate value map if there
	 * are multiple types of variables.
	 */
	Values initial;
	initial.insert(key, Rot2::fromAngle(20 * degree));
	initial.print("initial estimate");

	/**
	 *    Step 4: Optimize
	 * After formulating the problem with a graph of constraints
	 * and an initial estimate, executing optimization is as simple
	 * as calling a general optimization function with the graph and
	 * initial estimate.  This will yield a new RotValues structure
	 * with the final state of the optimization.
	 */
	Values result = LevenbergMarquardtOptimizer(graph, initial).optimize();
	result.print("final result");

	return 0;
}
示例#3
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/* ************************************************************************* */
Rot2 Rot2betweenOptimized(const Rot2& r1, const Rot2& r2) {
  // Same as compose but sign of sin for r1 is reversed
  return Rot2::fromCosSin(r1.c() * r2.c() + r1.s() * r2.s(), -r1.s() * r2.c() + r1.c() * r2.s());
}
示例#4
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void go() {

  typedef Vec4<T> Vec;
  typedef Vec2<T> Vec2D;

  std::cout << std::endl;
  std::cout << sizeof(Vec) << std::endl;
  std::vector<Vec> vec1; vec1.reserve(50);
  std::vector<T> vect(23);
  std::vector<Vec> vec2(53);
  std::vector<Vec> vec3; vec3.reserve(50234);


  Vec x(2.0,4.0,5.0);
  Vec y(-3.0,2.0,-5.0);
  std::cout << x << std::endl;
  std::cout << Vec4<float>(x) << std::endl;
  std::cout << Vec4<double>(x) << std::endl;
  std::cout << -x << std::endl;
  std::cout << x.template get1<2>() << std::endl;
  std::cout << y << std::endl;
  std::cout << T(3.)*x << std::endl;
  std::cout << y*T(0.1) << std::endl;
  std::cout << (Vec(1) - y*T(0.1)) << std::endl;
  std::cout <<  mathSSE::sqrt(x) << std::endl;


  std::cout << dot(x,y) << std::endl; 
  std::cout << dotSimple(x,y) << std::endl;

  std::cout << "equal" << (x==x ? " " : " not ") << "ok" << std::endl;
  std::cout << "not equal" << (x==y ? " not " : " ") << "ok" << std::endl;
 
  Vec z = cross(x,y);
  std::cout << z << std::endl;


  std::cout << "rotations" << std::endl;

  T a = 0.01;
  T ca = std::cos(a);
  T sa = std::sin(a);

  Rot3<T> r1( ca, sa, 0,
	      -sa, ca, 0,
	      0,  0, 1);

  Rot2<T> r21( ca, sa,
	       -sa, ca);

  Rot3<T> r2(Vec( 0, 1 ,0), Vec( 0, 0, 1), Vec( 1, 0, 0));
  Rot2<T> r22(Vec2D( 0, 1), Vec2D( 1, 0));

  {
    std::cout << "\n3D rot" << std::endl;
    Vec xr = r1.rotate(x);
    std::cout << x << std::endl;
    std::cout << xr << std::endl;
    std::cout << r1.rotateBack(xr) << std::endl;
    
    Rot3<T> rt = r1.transpose();
    Vec xt = rt.rotate(xr);
    std::cout << x << std::endl;
    std::cout << xt << std::endl;
    std::cout << rt.rotateBack(xt) << std::endl;
    
    std::cout << r1 << std::endl;
    std::cout << rt << std::endl;
    std::cout << r1*rt << std::endl;
    std::cout << r2 << std::endl;
    std::cout << r1*r2 << std::endl;
    std::cout << r2*r1 << std::endl;
    std::cout << r1*r2.transpose() << std::endl;
    std::cout << r1.transpose()*r2 << std::endl;
  }

  {
    std::cout << "\n2D rot" << std::endl;
    Vec2D xr = r21.rotate(x.xy());
    std::cout << x.xy() << std::endl;
    std::cout << xr << std::endl;
    std::cout << r21.rotateBack(xr) << std::endl;
    
    Rot2<T> rt = r21.transpose();
    Vec2D xt = rt.rotate(xr);
    std::cout << x.xy() << std::endl;
    std::cout << xt << std::endl;
    std::cout << rt.rotateBack(xt) << std::endl;
    
    std::cout << r21 << std::endl;
    std::cout << rt << std::endl;
    std::cout << r21*rt << std::endl;
    std::cout << r22 << std::endl;
    std::cout << r21*r22 << std::endl;
    std::cout << r22*r21 << std::endl;
    std::cout << r21*r22.transpose() << std::endl;
    std::cout << r21.transpose()*r22 << std::endl;
  }


}
示例#5
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/* ************************************************************************* */
Rot2 Rot2betweenDefault(const Rot2& r1, const Rot2& r2) {
  return r1.inverse() * r2;
}