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gpu_process.cu
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gpu_process.cu
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/*
* gpu_process.cu
*
* Created on: Aug 1, 2019
* Author: YiYuan PAN, Peter XU
* Institute: ZJU, Robotics 104
*/
#include <cuda_runtime.h>
#include <stdio.h>
#include <iostream>
#include<cmath>
#include<iomanip>
// Eigen
#include <Eigen/Core>
#include <Eigen/Geometry>
using namespace std;
__device__ float *map_lowest;
__device__ float *map_elevation;
__device__ float *map_variance;
__device__ float *map_intensity;
__device__ float *map_traver;
__device__ int *map_colorR;
__device__ int *map_colorG;
__device__ int *map_colorB;
__device__ float central_coordinate[2];
__device__ int start_indice[2];
__device__ float sensorZatLowestScan;
__constant__ int Length;
__constant__ float Resolution;
__constant__ float obstacle_threshold;
//points_
__constant__ int C_point_num;
__constant__ float C_min_r;
__constant__ float C_beam_a;
__constant__ float C_beam_c;
__constant__ float C_factor_a;
__constant__ float C_factor_b;
__constant__ float C_factor_c;
__constant__ float C_factor_d;
__constant__ float C_factor_e;
__constant__ float C_lateral_factor;
//remove point
__constant__ double C_relativeLowerThreshold;
__constant__ double C_relativeUpperThreshold;
//fuse
__constant__ float mahalanobisDistanceThreshold_;
struct Pos3
{
float x;
float y;
float z;
};
__device__ void computerEigenvalue(float *pMatrix,int nDim, float *maxvector, float dbEps,int nJt)
{
float pdblVects[9];
float pdbEigenValues[3];
for(int i = 0; i < nDim; i ++)
{
pdblVects[i*nDim+i] = 1.0f;
for(int j = 0; j < nDim; j ++)
{
if(i != j)
pdblVects[i*nDim+j]=0.0f;
}
}
int nCount = 0; //迭代次数
while(1)
{
//在pMatrix的非对角线上找到最大元素
float dbMax = pMatrix[1];
int nRow = 0;
int nCol = 1;
for (int i = 0; i < nDim; i ++) //行
{
for (int j = 0; j < nDim; j ++) //列
{
float d = fabs(pMatrix[i*nDim+j]);
if((i!=j) && (d> dbMax))
{
dbMax = d;
nRow = i;
nCol = j;
}
}
}
if(dbMax < dbEps) //精度符合要求
break;
if(nCount > nJt) //迭代次数超过限制
break;
nCount++;
float dbApp = pMatrix[nRow*nDim+nRow];
float dbApq = pMatrix[nRow*nDim+nCol];
float dbAqq = pMatrix[nCol*nDim+nCol];
//计算旋转角度
float dbAngle = 0.5*atan2(-2*dbApq,dbAqq-dbApp);
float dbSinTheta = sin(dbAngle);
float dbCosTheta = cos(dbAngle);
float dbSin2Theta = sin(2*dbAngle);
float dbCos2Theta = cos(2*dbAngle);
pMatrix[nRow*nDim+nRow] = dbApp*dbCosTheta*dbCosTheta +
dbAqq*dbSinTheta*dbSinTheta + 2*dbApq*dbCosTheta*dbSinTheta;
pMatrix[nCol*nDim+nCol] = dbApp*dbSinTheta*dbSinTheta +
dbAqq*dbCosTheta*dbCosTheta - 2*dbApq*dbCosTheta*dbSinTheta;
pMatrix[nRow*nDim+nCol] = 0.5*(dbAqq-dbApp)*dbSin2Theta + dbApq*dbCos2Theta;
pMatrix[nCol*nDim+nRow] = pMatrix[nRow*nDim+nCol];
for(int i = 0; i < nDim; i ++)
{
if((i!=nCol) && (i!=nRow))
{
int u = i*nDim + nRow; //p
int w = i*nDim + nCol; //q
dbMax = pMatrix[u];
pMatrix[u]= pMatrix[w]*dbSinTheta + dbMax*dbCosTheta;
pMatrix[w]= pMatrix[w]*dbCosTheta - dbMax*dbSinTheta;
}
}
for (int j = 0; j < nDim; j ++)
{
if((j!=nCol) && (j!=nRow))
{
int u = nRow*nDim + j; //p
int w = nCol*nDim + j; //q
dbMax = pMatrix[u];
pMatrix[u]= pMatrix[w]*dbSinTheta + dbMax*dbCosTheta;
pMatrix[w]= pMatrix[w]*dbCosTheta - dbMax*dbSinTheta;
}
}
//计算特征向量
for(int i = 0; i < nDim; i ++)
{
int u = i*nDim + nRow; //p
int w = i*nDim + nCol; //q
dbMax = pdblVects[u];
pdblVects[u] = pdblVects[w]*dbSinTheta + dbMax*dbCosTheta;
pdblVects[w] = pdblVects[w]*dbCosTheta - dbMax*dbSinTheta;
}
}
int min_id = 0;
float minEigenvalue;
for(int i = 0; i < nDim; i ++)
{
pdbEigenValues[i] = pMatrix[i*nDim+i];
if(i == 0)
minEigenvalue = pdbEigenValues[i];
else
{
if(minEigenvalue > pdbEigenValues[i])
{
minEigenvalue = pdbEigenValues[i];
min_id = i;
}
}
}
for(int i = 0; i < nDim; i ++)
{
maxvector[i] = pdblVects[min_id + nDim * i];
}
}
//geographic location to memory location index
__device__ int dev_IndexToRange(int *cell_p){
int d_index[2];
d_index[0] = (cell_p[0] - start_indice[0] + Length)%Length;
d_index[1] = (cell_p[1] - start_indice[1] + Length)%Length;
int index = d_index[0] * Length + d_index[1];
return index;
}
__global__ void G_Init_map()
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * Length ) {
map_intensity[i] = 0;
map_elevation[i] = -10;
map_variance[i] = -10;
map_lowest[i] = 100;
map_traver[i] = -10;
map_colorR[i] = 0;
map_colorG[i] = 0;
map_colorB[i] = 0;
}
}
__global__ void G_Clear_allmap()
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * Length) {
map_intensity[i] = 0;
map_elevation[i] = -10;
map_variance[i] = -10;
map_traver[i] = -10;
map_colorR[i] = 0;
map_colorG[i] = 0;
map_colorB[i] = 0;
//printf("%f ", map_elevation[i]);
}
}
__global__ void G_Clear_maplowest()
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * Length) {
map_lowest[i] = 10;
//printf("%f ", map_elevation[i]);
}
}
__global__ void G_Printf_map()
{
for(int i = 0; i < Length; i++)
for(int j = 0; j < Length; j++)
{
printf("%f ", map_elevation[i * Length + j]);
}
printf("P:start_indice:%d,%d\n",start_indice[0], start_indice[1]);
printf("P:central_coordinate:%f,%f\n",central_coordinate[0], central_coordinate[1]);
}
__global__ void G_Clear_map(int start, int shift, bool row_flag)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * shift) {
if(row_flag){
map_intensity[start * Length + i] = 0;
map_elevation[start * Length + i] = -10;
map_variance[start * Length + i] = -10;
map_colorR[start * Length + i] = 0;
map_colorG[start * Length + i] = 0;
map_colorB[start * Length + i] = 0;
}
else{
map_intensity[i / shift * Length + i % shift + start] = 0;
map_elevation[i / shift * Length + i % shift + start] = -10;
map_variance[i / shift * Length + i % shift + start] = -10;
map_colorR[i / shift * Length + i % shift + start] = 0;
map_colorG[i / shift * Length + i % shift + start] = 0;
map_colorB[i / shift * Length + i % shift + start] = 0;
}
}
}
__device__ Eigen::Vector3f cuda_Transpose(Eigen::RowVector3f A)
{
Eigen::Vector3f A_T;
A_T(0,0) = A(0,0);
A_T(1,0) = A(0,1);
A_T(2,0) = A(0,2);
return A_T;
}
template<typename PrimType_>
//inline static
__device__ Eigen::Matrix<PrimType_, 3, 3> GetSkewMatrixFromVector(const Eigen::Matrix<PrimType_, 3, 1>& vec) {
Eigen::Matrix<PrimType_, 3, 3> mat;
mat << 0, -vec(2), vec(1), vec(2), 0, -vec(0), -vec(1), vec(0), 0;
return mat;
}
__device__ float cuda_computer(Eigen::RowVector3f A, Eigen::Matrix3f B, Eigen::Vector3f C)
{
Eigen::RowVector3f A1 = A * B;
float result = A1(0,0) * C(0,0) + A1(0,1) * C(1,0) + A1(0,2) * C(2,0);
return result;
}
__device__ Eigen::Matrix3f SkewMatrixFromVector(Eigen::Vector3f vec)
{
Eigen::Matrix<float, 3, 3> mat;
mat << 0, -vec(2), vec(1), vec(2), 0, -vec(0), -vec(1), vec(0), 0;
return mat;
}
__device__ int PointsToIndex(float p_x, float p_y)
{
float shift_x = p_x - central_coordinate[0];
float shift_y = p_y - central_coordinate[1];
int index_x, index_y, index;
if(Length % 2 == 0)
{
index_x = (int)((float)(Length / 2) - shift_x / Resolution) ;
index_y = (int)((float)(Length / 2) - shift_y / Resolution);
}
else
{
index_x = Length / 2 - static_cast<int>(shift_x / Resolution +0.5 * (shift_x > 0 ? 1 : -1));
index_y = Length / 2 - static_cast<int>(shift_y / Resolution +0.5 * (shift_y > 0 ? 1 : -1));
}
if(index_x >= 0 && index_x < Length && index_y >= 0 && index_y < Length)
index = index_x * Length + index_y;
else
index = -1;
return index;
}
__device__ int PointsToMapIndex(float p_x, float p_y)
{
float shift_x = p_x - central_coordinate[0];
float shift_y = p_y - central_coordinate[1];
int index_x, index_y, index;
if(Length % 2 == 0)
{
index_x = (int)((float)(Length / 2) - shift_x / Resolution) ;
index_y = (int)((float)(Length / 2) - shift_y / Resolution);
}
else
{
index_x = Length / 2 - static_cast<int>(shift_x / Resolution +0.5 * (shift_x > 0 ? 1 : -1));
index_y = Length / 2 - static_cast<int>(shift_y / Resolution +0.5 * (shift_y > 0 ? 1 : -1));
}
if(index_x >= 0 && index_x < Length && index_y >= 0 && index_y < Length)
{
int storage_x = (index_x + start_indice[0]) % Length;
int storage_y = (index_y + start_indice[1]) % Length;
index = storage_x * Length + storage_y;
}
else
index = -1;
return index;
}
__device__ static float atomicMax(float* address, float val)
{
int* address_as_i = (int*) address;
int old = *address_as_i, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_i, assumed,
__float_as_int(::fmaxf(val, __int_as_float(assumed))));
} while (assumed != old);
return __int_as_float(old);
}
__device__ static float atomicMin(float* address, float val)
{
int* address_as_i = (int*) address;
int old = *address_as_i, assumed;
do {
assumed = old;
old = ::atomicCAS(address_as_i, assumed,
__float_as_int(::fminf(val, __int_as_float(assumed))));
} while (assumed != old);
return __int_as_float(old);
}
__global__ void G_pointsprocess(int* map_index, float *point_x, float *point_y, float *point_z, float *result_var, float *point_x_ts, float *point_y_ts, float *point_z_ts, Eigen::Matrix4f transform, int point_num, Eigen::RowVector3f C_sensorJacobian, Eigen::Matrix3f C_rotationVariance, Eigen::Matrix3f C_C_SB_transpose, Eigen::RowVector3f C_P_mul_C_BM_transpose, Eigen::Matrix3f C_B_r_BS_skew)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if(i < point_num)
{
float point_height = transform(2, 0) * point_x[i] + transform(2, 1) * point_y[i] + transform(2, 2) * point_z[i] + transform(2, 3);
int flag = 0;
// !!! IMPORTANT FILTER PARAMETERS
if((point_x[i] > -1.5 && point_x[i] < 1.5 && point_y[i] > -1.5 && point_y[i] < 1.5) || (point_y[i] > -1 && point_y[i] < 1) || point_y[i] > 0)
{
flag = 1;
}
if((point_height > C_relativeLowerThreshold && point_height < C_relativeUpperThreshold) && flag == 0)
{
point_x_ts[i] = transform(0, 0) * point_x[i] + transform(0, 1) * point_y[i] + transform(0, 2) * point_z[i] + transform(0, 3) ;
point_y_ts[i] = transform(1, 0) * point_x[i] + transform(1, 1) * point_y[i] + transform(1, 2) * point_z[i] + transform(1, 3) ;
point_z_ts[i] = point_height;
Eigen::Vector3f pointVector(point_x[i], point_y[i], point_z[i]); // S_r_SP
float heightVariance = 0.0; // sigma_p
// Measurement distance.
float measurementDistance = pointVector.norm();
// Compute sensor covariance matrix (Sigma_S) with sensor model.
float varianceNormal = pow(C_min_r, 2);
float varianceLateral = pow(C_beam_c + C_beam_a * measurementDistance, 2);
Eigen::Matrix3f sensorVariance = Eigen::Matrix3f::Zero();
sensorVariance.diagonal() << varianceLateral, varianceLateral, varianceNormal;
// Robot rotation Jacobian (J_q).
const Eigen::Matrix3f C_SB_transpose_times_S_r_SP_skew = SkewMatrixFromVector(Eigen::Vector3f(C_C_SB_transpose * pointVector));
Eigen::RowVector3f rotationJacobian = C_P_mul_C_BM_transpose * (C_SB_transpose_times_S_r_SP_skew + C_B_r_BS_skew);
// Measurement variance for map (error propagation law).
Eigen::Vector3f rotationJacobian_T = cuda_Transpose(rotationJacobian);
heightVariance = cuda_computer(rotationJacobian, C_rotationVariance, rotationJacobian_T);
Eigen::Vector3f C_sensorJacobian_T = cuda_Transpose(C_sensorJacobian);
heightVariance += cuda_computer(C_sensorJacobian, sensorVariance, C_sensorJacobian_T);
// Copy to list.
result_var[i] = heightVariance;
int grid_index = PointsToIndex(point_x_ts[i], point_y_ts[i]);
map_index[i] = PointsToMapIndex(point_x_ts[i], point_y_ts[i]);
if(grid_index != -1)
{
atomicMin(&map_lowest[grid_index], point_height);
if(point_height == map_lowest[grid_index])
{
map_lowest[grid_index] = map_lowest[grid_index] + 3 * heightVariance;
}
}
}
else
{
map_index[i] = -1;
point_x[i] = -1;
point_y[i] = -1;
point_z[i] = -1;
point_x_ts[i] = -1;
point_y_ts[i] = -1;
point_z_ts[i] = -1;
result_var[i] = -1;
}
}
// Debug
// printf("GPU points:i:%d;x:%f;y:%f;z:%f", i, point_x_ts[i], point_y_ts[i], point_z_ts[i]);
}
__global__ void G_get_mapinfo(int cell_num, float *dev_map_ele, float *dev_map_var)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if(i < cell_num)
{
dev_map_ele[i] = map_elevation[i];
dev_map_var[i] = map_variance[i];
}
}
__global__ void G_set_mapinfo(int cell_num, float *dev_map_ele, float *dev_map_var)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if(i < cell_num)
{
map_elevation[i] = dev_map_ele[i];
map_variance[i] = dev_map_var[i];
}
}
__global__ void G_fuse(int *point_index, int *points_colorR, int *points_colorG, int *points_colorB, float* points_intensity, float *points_h, float *points_v, int point_num){
int map_index = blockDim.x * blockIdx.x + threadIdx.x;
if(map_index < Length * Length){
for(int i = 0; i < point_num; i++)
{
if(point_index[i] != map_index || points_h[i] == -1)
continue;
if (map_elevation[map_index]== -10){
// No prior information in elevation map, use measurement.
map_elevation[map_index] = points_h[i];
map_variance[map_index] = points_v[i];
if(points_colorR[i] != 0 && points_colorG[i] != 0 && points_colorB[i] != 0 && points_intensity[i] != 0)
{
map_intensity[map_index] = points_intensity[i];
map_colorR[map_index] = points_colorR[i];
map_colorG[map_index] = points_colorG[i];
map_colorB[map_index] = points_colorB[i];
}
}
else{
// Deal with multiple heights in one cell.
// Debug fabs,sqrt！！！！！！！！！！！！！！！！！！
// printf("points height:%f;points var:%f;point_num:%d;cells height:%f, map_variance:%f\n", points_max[i], points_var[i], points_num[i], map_elevation[map_index], map_variance[map_index]);
const float mahalanobisDistance = fabs(points_h[i] - map_elevation[map_index]) / sqrt(map_variance[map_index]);
//printf("mahalanobisDistance:%f\n", mahalanobisDistance);
if (mahalanobisDistance > 5) {
if (map_elevation[map_index] < points_h[i]) {
map_elevation[map_index] = points_h[i];
map_variance[map_index] = points_v[i];
if(points_colorR[i] != 0 && points_colorG[i] != 0 && points_colorB[i] != 0 && points_intensity[i] != 0)
{
map_intensity[map_index] = points_intensity[i];
map_colorR[map_index] = points_colorR[i];
map_colorG[map_index] = points_colorG[i];
map_colorB[map_index] = points_colorB[i];
}
}
}
else{
map_elevation[map_index] = (map_variance[map_index] * points_h[i] + points_v[i] * map_elevation[map_index]) / (map_variance[map_index] + points_v[i]);
map_variance[map_index] = (points_v[i] * map_variance[map_index]) / (points_v[i] + map_variance[map_index]);
if(points_colorR[i] != 0 && points_colorG[i] != 0 && points_colorB[i] != 0 && points_intensity[i] != 0)
{
map_intensity[map_index] = points_intensity[i];
map_colorR[map_index] = points_colorR[i];
map_colorG[map_index] = points_colorG[i];
map_colorB[map_index] = points_colorB[i];
}
// Debug
//printf("point_var:%f, map_variance:%f\n", points_v[i], map_variance[map_index]);
}
}
}
if(map_variance[map_index] < 0.0001)
map_variance[map_index] = 0.0001;
}
}
//计算每块地图的X，Y,XY方差
__global__ void G_Mapvar_update(float var_update)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * Length) {
if(map_variance[i] != -10)
map_variance[i] += var_update;
}
}
__global__ void G_Mapfeature(int *d_colorR, int *d_colorG, int *d_colorB, float *d_elevation, float *d_var, float *d_rough, float *d_slope, float *d_traver, float *d_intensity)
{
int idx = threadIdx.x + blockDim.x * blockIdx.x;
if(idx >= Length * Length) return;
Pos3 point[25];
float s_z;
float px_mean = 0;
float py_mean = 0;
float pz_mean = 0;
int cell_x = idx / Length;
int cell_y = idx % Length;
int point_x;
int point_y;
int Ele_x;
int Ele_y;
// Debug
//slope[idx] = map_height[idx];
//printf("X:%d,Y:%d,height:%f", cell_x, cell_y, map_height[idx]);
d_elevation[idx] = map_elevation[idx];
d_colorR[idx] = map_colorR[idx];
d_colorG[idx] = map_colorG[idx];
d_colorB[idx] = map_colorB[idx];
d_intensity[idx] = map_intensity[idx];
d_var[idx] = map_variance[idx];
if(map_elevation[idx] == -10)
return ;
int p_n = 0;
for (int i = -2; i < 3 ;i ++)
{
for(int j = -2; j < 3; j++)
{
Ele_x = (cell_x + Length - start_indice[0]) % Length;
Ele_y = (cell_y + Length - start_indice[1]) % Length;
Ele_x = Ele_x + i;
Ele_y = Ele_y + j;
if( Ele_x >= 0 && Ele_x < Length && Ele_y >= 0 && Ele_y < Length)
{
point_x = cell_x + i;
point_y = cell_y + j;
point_x = (point_x + Length) % Length;
point_y = (point_y + Length) % Length;
s_z = map_elevation[point_x * Length + point_y];
if(s_z != -10)
{
point[p_n].x = point_x * Resolution;
point[p_n].y = point_y * Resolution;
point[p_n].z = s_z;
px_mean = px_mean + point[p_n].x;
py_mean = py_mean + point[p_n].y;
pz_mean = pz_mean + point[p_n].z;
p_n++;
}
}
}
}
if(p_n > 7)
{
px_mean = px_mean / p_n;
py_mean = py_mean / p_n;
pz_mean = pz_mean / p_n;
float pMatrix[9] = {0};
for(int i = 0; i < p_n; i ++)
{
pMatrix[0] = pMatrix[0] + (point[i].x - px_mean) * (point[i].x - px_mean);
pMatrix[4] = pMatrix[4] + (point[i].y - py_mean) * (point[i].y - py_mean);
pMatrix[8] = pMatrix[8] + (point[i].z - pz_mean) * (point[i].z - pz_mean);
pMatrix[1] = pMatrix[1] + (point[i].x - px_mean) * (point[i].y - py_mean);
pMatrix[2] = pMatrix[2] + (point[i].x - px_mean) * (point[i].z - pz_mean);
pMatrix[5] = pMatrix[5] + (point[i].y - py_mean) * (point[i].z - pz_mean);
pMatrix[3] = pMatrix[1];
pMatrix[6] = pMatrix[2];
pMatrix[7] = pMatrix[5];
}
float dbEps = 0.01;
int nJt = 30;
int nDim = 3;
float normal_vec[3];
float Slope;
computerEigenvalue(pMatrix, nDim, normal_vec, dbEps, nJt);
float height = map_elevation[idx];
float smooth_height = pz_mean;
if(normal_vec[2] > 0)
Slope = acos(normal_vec[2]);
else
Slope = acos(-normal_vec[2]);
float Rough = fabs(height - smooth_height);
float Traver = 0.5 * (1.0 - Slope / 0.6)+ 0.5 * (1.0 - (Rough / 0.2));
d_slope[idx] = Slope;
d_rough[idx] = Rough;
d_traver[idx] = Traver;
map_traver[idx] = Traver;
}
else
{
d_slope[idx] = 0;
d_rough[idx] = 0;
d_traver[idx] = -10;
map_traver[idx] = -10;
}
}
__device__ void StorageP2geoP(int index_s_x, int index_s_y, int *index_g){
index_g[0] = (index_s_x + Length - start_indice[0]) % Length;
index_g[1] = (index_s_y + Length - start_indice[1]) % Length;
}
__device__ int Storageindex(int index_g_x, int index_g_y){
int index_s = index_g_x * Length + index_g_y;
return index_s;
}
__device__ bool P_isVaild(int cell_index_x, int cell_index_y)
{
int storage_index = Storageindex(cell_index_x, cell_index_y);
//d_map_clean[storage_index] = 0;
if(map_lowest[storage_index] == 10)
return false;
else
return true;
}
__device__ float d_min_elevation(int cell_index_x, int cell_index_y, int obstacle_index_x, float robot_index_x)
{
float x1 = (float)(cell_index_x - obstacle_index_x);
float x2 = (float)cell_index_x - robot_index_x;
int storage_index = Storageindex(cell_index_x, cell_index_y);
// Debug
// map_lowest[storage_index] = 1;
// d_map_clean[storage_index] = 0;
float h2 = sensorZatLowestScan - map_lowest[storage_index];
float obstacle_max_ele = map_lowest[storage_index] + h2 / x2 * x1;
return obstacle_max_ele;
}
__global__ void G_Raytracing()
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < Length * Length){
if(map_traver[i] < obstacle_threshold && map_elevation[i] != -10)
{
// Debug
// printf("i:%d,map_traver:%f\n", i, map_traver[i]);
// d_map_clean[i] = -1;
int cell_x = i / Length;
int cell_y = i % Length;
int robot_index;
int obstacle_indice[2];
StorageP2geoP(cell_x, cell_y, obstacle_indice);
float obstacle_ele = map_elevation[i];
int current_indice[2];
float increment[2];
int increment_x, increment_y;
current_indice[0] = obstacle_indice[0];
current_indice[1] = obstacle_indice[1];
if(Length % 2 == 0)
{
robot_index = (float)(Length / 2 - 0.5);
increment[0] = obstacle_indice[0] - robot_index;
increment[1] = obstacle_indice[1] - robot_index;
}
else
{
robot_index = (float)(Length / 2);
increment[0] = obstacle_indice[0] - robot_index;
increment[1] = obstacle_indice[1] - robot_index;
}
if(increment[0] > 0)
increment_x = 1;
else if(increment[0] == 0)
increment_x = 0;
else
increment_x = -1;
if(increment[1] > 0)
increment_y = 1;
else if(increment[1] == 0)
increment_y = 0;
else
increment_y = -1;
float obstacle_max_ele;
float obstacle_restrict_ele = obstacle_ele;
if(increment_x == 0 && increment_y == 0)
return ;
else if(increment_x == 0)
{
current_indice[1] += increment_y;
while(current_indice[1] >= 0 && current_indice[1] < Length)
{
if(P_isVaild(current_indice[0], current_indice[1]))
{
obstacle_max_ele = d_min_elevation(current_indice[0], current_indice[1], obstacle_indice[0], robot_index);
//std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
if(obstacle_max_ele < obstacle_restrict_ele)
obstacle_restrict_ele = obstacle_max_ele;
}
current_indice[1] += increment_y;
}
return ;
}
else if(increment_y == 0)
{
current_indice[0] += increment_x;
while(current_indice[0] >= 0 && current_indice[0] < Length)
{
if(P_isVaild(current_indice[0], current_indice[1]))
{
obstacle_max_ele = d_min_elevation(current_indice[0], current_indice[1], obstacle_indice[0], robot_index);
//std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
if(obstacle_max_ele < obstacle_restrict_ele)
obstacle_restrict_ele = obstacle_max_ele;
}
current_indice[0] += increment_x;
}
return ;
}
float dis = sqrt(increment[0] * increment[0] + increment[1] * increment[1]);
float dir[2];
dir[0] = increment[0] /dis;
dir[1] = increment[1] /dis;
float threshold;
if(fabs(increment[0]) > fabs(increment[1]))
threshold = sqrt(0.5 * 0.5 + pow(0.5/increment[0]*increment[1], 2));
else
threshold = sqrt(0.5 * 0.5 + pow(0.5/increment[1]*increment[0], 2));
float dir_num_x;
float dir_num_y;
float bound_increment_x = (float)increment_x/2;
float bound_increment_y = (float)increment_y/2;
dir_num_x = bound_increment_x / dir[0];
dir_num_y = bound_increment_y / dir[1];
float dir_num_later = 0;
// Debug
// std::cout << "threshold" << threshold << std::endl;
// std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
while(current_indice[0] >= 0 && current_indice[0] < Length && current_indice[1] >= 0 && current_indice[1] < Length)
{
if(dir_num_x > dir_num_y)
{
if(dir_num_y - dir_num_later > threshold && current_indice[0] != obstacle_indice[0] && current_indice[1] != obstacle_indice[1])
{
if(P_isVaild(current_indice[0], current_indice[1]))
{
obstacle_max_ele = d_min_elevation(current_indice[0], current_indice[1], obstacle_indice[0], robot_index);
if(obstacle_max_ele < obstacle_restrict_ele)
obstacle_restrict_ele = obstacle_max_ele;
//std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
}
}
current_indice[1] += increment_y;
bound_increment_y += (float)increment_y;
dir_num_later = dir_num_y;
dir_num_y = bound_increment_y / dir[1];
}
else if(dir_num_x < dir_num_y)
{
if(dir_num_x - dir_num_later > threshold && current_indice[0] != obstacle_indice[0] && current_indice[1] != obstacle_indice[1])
{
if(P_isVaild(current_indice[0], current_indice[1]))
{
obstacle_max_ele = d_min_elevation(current_indice[0], current_indice[1], obstacle_indice[0], robot_index);
if(obstacle_max_ele < obstacle_restrict_ele)
obstacle_restrict_ele = obstacle_max_ele;
// Debug
// std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
}
}
current_indice[0] += increment_x;
bound_increment_x += (float)increment_x;
dir_num_later = dir_num_x;
dir_num_x = bound_increment_x / dir[0];
}
else
{
if(dir_num_x - dir_num_later > threshold && current_indice[0] != obstacle_indice[0] && current_indice[1] != obstacle_indice[1])
{
if(P_isVaild(current_indice[0], current_indice[1]))
{
obstacle_max_ele = d_min_elevation(current_indice[0], current_indice[1], obstacle_indice[0], robot_index);
if(obstacle_max_ele < obstacle_restrict_ele)
obstacle_restrict_ele = obstacle_max_ele;
// Debug
// std::cout << "x:"<<current_indice[0] << " y:" << current_indice[1]<< std::endl;
}
}
current_indice[0] += increment_x;
current_indice[1] += increment_y;
bound_increment_x += (float)increment_x;
bound_increment_y += (float)increment_y;
dir_num_later = dir_num_x;
dir_num_x = bound_increment_x / dir[0];
dir_num_y = bound_increment_y / dir[1];
}
}
// Debug
// printf("height:%f,restrict_height:%f\n", obstacle_ele, obstacle_restrict_ele);
// d_map_clean[i] = obstacle_restrict_ele;
if(obstacle_ele - 3 * sqrt(map_variance[i])> obstacle_restrict_ele)
map_elevation[i] = -10;
}
//else
// d_map_clean[i] = 1;
}
}
bool getIndexShiftFromPositionShift(int *indexShift,
float *positionShift, float resolution)
{
for (int i = 0; i < 2; i++) {
indexShift[i] = static_cast<int>(positionShift[i] / resolution + 0.5 * (positionShift[i] > 0 ? 1 : -1));
}
// Debug
// std::cout << "indexShift1:" << indexShift[0]<< " indexShift2:" << indexShift[1]<< std::endl;
return true;
}
bool getPositionShiftFromIndexShift(float *positionShift,
int *indexShift, float resolution)
{
for(int i = 0; i < 2; i++)
{
positionShift[i] = (float)indexShift[i] * resolution;
}
// Debug
// std::cout << "positionShift1:" << positionShift[0]<<" positionShift2：" << positionShift[1]<< std::endl;
return true;
}
int IndexToRange(int index,int Length)
{
if (index < 0) index += ((-index / Length) + 1) * Length;
index = index % Length;
return index;
}
void Clear_regionrow(int Start_x, int Shift_x, int length)
{
int cell_num = Shift_x * length;
int threadsPerBlock = 256;
int blocksPerGrid =(cell_num + threadsPerBlock - 1) / threadsPerBlock;
G_Clear_map<<<blocksPerGrid, threadsPerBlock>>>(Start_x, Shift_x, true);
}
void Clear_regioncol(int Start_y, int Shift_y, int length)
{
int cell_num = Shift_y * length;
int threadsPerBlock = 256;
int blocksPerGrid =(cell_num + threadsPerBlock - 1) / threadsPerBlock;
G_Clear_map<<<blocksPerGrid, threadsPerBlock>>>(Start_y, Shift_y, false);
}
void Init_GPU_elevationmap(int length, float resolution, float h_mahalanobisDistanceThreshold_, float h_obstacle_threshold)
{
float init_centralcoordinate[2] = {0, 0};
int init_startindice[2] = {0, 0};
float *h_map_intensity;
float *h_map_elevation;
float *h_map_variance;
float *h_map_lowest;
float *h_map_traver;
int *h_map_colorR;
int *h_map_colorG;
int *h_map_colorB;
cudaMalloc((void**)&h_map_intensity, sizeof(float) * length * length);
cudaMalloc((void**)&h_map_elevation, sizeof(float) * length * length);
cudaMalloc((void**)&h_map_variance, sizeof(float) * length * length);
cudaMalloc((void**)&h_map_lowest, sizeof(float) * length * length);
cudaMalloc((void**)&h_map_traver, sizeof(float) * length * length);
cudaMalloc((void**)&h_map_colorR, sizeof(int) * length * length);
cudaMalloc((void**)&h_map_colorG, sizeof(int) * length * length);
cudaMalloc((void**)&h_map_colorB, sizeof(int) * length * length);
cudaMemcpyToSymbol(map_intensity, &h_map_intensity, sizeof(float *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_elevation, &h_map_elevation, sizeof(float *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_variance, &h_map_variance, sizeof(float *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_lowest, &h_map_lowest, sizeof(float *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_traver, &h_map_traver, sizeof(float *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_colorR, &h_map_colorR, sizeof(int *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_colorG, &h_map_colorG, sizeof(int *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(map_colorB, &h_map_colorB, sizeof(int *),size_t(0), cudaMemcpyHostToDevice);
cudaMemcpyToSymbol(central_coordinate, &init_centralcoordinate, 2*sizeof(float));
cudaMemcpyToSymbol(start_indice, &init_startindice, 2*sizeof(int));
cudaMemcpyToSymbol(Length, &length, sizeof(int));
cudaMemcpyToSymbol(Resolution, &resolution, sizeof(float));
cudaMemcpyToSymbol(mahalanobisDistanceThreshold_, &h_mahalanobisDistanceThreshold_, sizeof(float));
cudaMemcpyToSymbol(obstacle_threshold, &h_obstacle_threshold, sizeof(float));
int threadsPerBlock = 256;
int blocksPerGrid =(length * length + threadsPerBlock - 1) / threadsPerBlock;
std::cout << "GPU Init mapping:"<< length * length <<std::endl;
G_Init_map<<<blocksPerGrid, threadsPerBlock>>>();
//G_Printf_map<<<1, 1>>>();
cudaError_t cudaStatus = cudaGetLastError();
if (cudaStatus != cudaSuccess)
{
fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
//goto Error;
}
//cudaDeviceSynchronize();
}
float PositionToRange(float p, float shift, float resolution)
{
int p_index = round(p /resolution);
int shift_index = round(shift /resolution);
int current_index = p_index + shift_index;
return (current_index * resolution);
}