路径平滑常用代码

路径平滑常用代码 | 沉默杀手

/**
 * 平均分割区间 [start, end] 为num段，num+1 个点，存入sliced
 * start and end 为sliced的首尾元素
 */
template <typename T>
void uniform_slice(const T start, const T end, uint32_t num,
                   std::vector<T>* sliced)
{
  if (!sliced || num == 0)
        return;
  const T delta = (end - start) / num;
  sliced->resize(num + 1);
  T  s = start;
  for (uint32_t i = 0; i < num; ++i, s += delta)
  {
      sliced->at(i) = s;
  }
  sliced->at(num) = end;
}

/**
 * Check if two points u and v are the same point on XY dimension.
 * @param u one point that has member function x() and y().
 * @param v one point that has member function x() and y().
 * @return sqrt((u.x-v.x)^2 + (u.y-v.y)^2) < epsilon, i.e., the Euclid distance
 * on XY dimension.
 */
template <typename U, typename V>
bool SamePointXY(const U& u, const V& v)
{
    static constexpr double kMathEpsilonSqr = 1e-8 * 1e-8;
    return (u.x() - v.x()) * (u.x() - v.x()) < kMathEpsilonSqr &&
         (u.y() - v.y()) * (u.y() - v.y()) < kMathEpsilonSqr;
}

PathPoint GetWeightedAverageOfTwoPathPoints(const PathPoint& p1,
                                            const PathPoint& p2,
                                            const double w1, const double w2)
{
    PathPoint p;
    p.set_x(p1.x() * w1 + p2.x() * w2);
    p.set_y(p1.y() * w1 + p2.y() * w2);
    p.set_z(p1.z() * w1 + p2.z() * w2);
    p.set_theta(p1.theta() * w1 + p2.theta() * w2);
    p.set_kappa(p1.kappa() * w1 + p2.kappa() * w2);
    p.set_dkappa(p1.dkappa() * w1 + p2.dkappa() * w2);
    p.set_ddkappa(p1.ddkappa() * w1 + p2.ddkappa() * w2);
    p.set_s(p1.s() * w1 + p2.s() * w2);
    return p;
}

// Test whether two float or double numbers are equal.
template <typename T>
typename std::enable_if<!std::numeric_limits<T>::is_integer, bool>::type
IsFloatEqual(T x, T y, int ulp = 2)
{
  // the machine epsilon has to be scaled to the magnitude of the values used
  // and multiplied by the desired precision in ULPs (units in the last place)
  return std::fabs(x - y) <
             std::numeric_limits<T>::epsilon() * std::fabs(x + y) * ulp
         // unless the result is subnormal
         || std::fabs(x - y) < std::numeric_limits<T>::min();
}