3dpcp/.svn/pristine/ab/abd41dce84d3a5c2f03fd95ad30c160b542192de.svn-base
2012-11-13 09:12:22 +01:00

1226 lines
42 KiB
Text
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

/*
* veloslam implementation
*
* Copyright (C) Andreas Nuechter, Li Wei, Li Ming
*
* Released under the GPL version 3.
*
*/
/**
* @file
* @brief Main programm for dynamic Velodyne SLAM
*
* @author Andreas Nuechter. Jacobs University Bremen, Germany
* @author Li Wei, Wuhan University, China
* @author Li Ming, Wuhan University, China
*/
#ifdef _MSC_VER
#ifdef OPENMP
#define _OPENMP
#endif
#endif
#ifdef _OPENMP
#include <omp.h>
#endif
#ifdef _MSC_VER
#include <windows.h>
#else
#include <dlfcn.h>
#endif
#include "slam6d/icp6Dapx.h"
#include "slam6d/icp6Dsvd.h"
#include "slam6d/icp6Dquat.h"
#include "slam6d/icp6Dortho.h"
#include "slam6d/icp6Dhelix.h"
#include "slam6d/icp6Ddual.h"
#include "slam6d/icp6Dlumeuler.h"
#include "slam6d/icp6Dlumquat.h"
#include "slam6d/icp6Dquatscale.h"
#include "slam6d/icp6D.h"
#ifdef WITH_CUDA
#include "slam6d/cuda/icp6Dcuda.h"
#endif
#include "slam6d/lum6Deuler.h"
#include "slam6d/lum6Dquat.h"
#include "slam6d/ghelix6DQ2.h"
#include "slam6d/elch6Deuler.h"
#include "slam6d/elch6Dquat.h"
#include "slam6d/elch6DunitQuat.h"
#include "slam6d/elch6Dslerp.h"
#include "slam6d/graphSlam6D.h"
#include "slam6d/gapx6D.h"
#include "slam6d/graph.h"
#include "slam6d/globals.icc"
#ifndef _MSC_VER
#include <getopt.h>
#else
#include "XGetopt.h"
#endif
#include <csignal>
#include "veloslam/veloscan.h"
#include "veloslam/debugview.h"
#include "veloslam/tracker.h"
#include "veloslam/trackermanager.h"
#include "veloslam/intersection_detection.h"
#ifdef _MSC_VER
#define strcasecmp _stricmp
#define strncasecmp _strnicmp
#else
#include <strings.h>
#endif
#ifdef WITH_METRICS
#include "slam6d/metrics.h"
#endif //WITH_METRICS
#include <GL/gl.h> /* OpenGL header file */
#include <GL/glu.h> /* OpenGL utilities header file */
#ifdef _MSC_VER
#include <GL/glut.h>
#else
#include <GL/freeglut.h>
#endif
#ifndef _MSC_VER
#include <time.h>
void Sleep(unsigned int mseconds)
{
clock_t goal = mseconds + clock();
while (goal > clock());
}
#endif
#define WANT_STREAM ///< define the WANT stream :)
#include <string>
using std::string;
#include <iostream>
using std::cout;
using std::cerr;
using std::endl;
#include <fstream>
using std::ifstream;
#include <boost/thread.hpp>
#include <boost/thread/mutex.hpp>
#include <boost/thread/condition.hpp>
using namespace boost;
extern boost::mutex keymutex;
extern boost::condition keycond;
extern void StartShow();
extern TrackerManager trackMgr;
extern int sliding_window_size;
extern int current_sliding_window_pos;
extern Trajectory VelodyneTrajectory;
extern VeloScan* g_pfirstScan;
extern bool g_pause;
extern float constant_static_or_moving;
extern bool DebugDrawFinished ;
extern bool ICPFinished;
extern bool save_animation;
extern int anim_frame_rate;
extern int scanCount;
// Handling Segmentation faults and CTRL-C
void sigSEGVhandler (int v)
{
static bool segfault = false;
if(!segfault) {
segfault = true;
cout << endl
<< "# **************************** #" << endl
<< " Segmentation fault or Ctrl-C" << endl
<< "# **************************** #" << endl
<< endl;
// save frames and close scans
for(ScanVector::iterator it = Scan::allScans.begin(); it != Scan::allScans.end(); ++it) {
(*it)->saveFrames();
}
cout << "Frames saved." << endl;
Scan::closeDirectory();
}
exit(-1);
}
/**
* Explains the usage of this program's command line parameters
*/
void usage(char* prog)
{
#ifndef _MSC_VER
const string bold("\033[1m");
const string normal("\033[m");
#else
const string bold("");
const string normal("");
#endif
cout << endl
<< bold << "USAGE " << normal << endl
<< " " << prog << " [options] directory" << endl << endl;
cout << bold << "OPTIONS" << normal << endl
<< bold << " -a" << normal << " NR, " << bold << "--algo=" << normal << "NR [default: 1]" << endl
<< " selects the minimizazion method for the ICP matching algorithm" << endl
<< " 1 = unit quaternion based method by Horn" << endl
<< " 2 = singular value decomposition by Arun et al. " << endl
<< " 3 = orthonormal matrices by Horn et al." << endl
<< " 4 = dual quaternion method by Walker et al." << endl
<< " 5 = helix approximation by Hofer & Potmann" << endl
<< " 6 = small angle approximation" << endl
<< " 7 = Lu & Milios style, i.e., uncertainty based, with Euler angles" << endl
<< " 8 = Lu & Milios style, i.e., uncertainty based, with Quaternion" << endl
<< " 9 = unit quaternion with scale method by Horn" << endl
<< endl
<< bold << " -A" << normal << " NR, " << bold << "--anim=" << normal << "NR [default: first and last frame only]" << endl
<< " if specified, use only every NR-th frame for animation" << endl
<< endl
<< bold << " -c" << normal << " NR, " << bold << "--cldist=" << normal << "NR [default: 500]" << endl
<< " specifies the maximal distance for closed loops" << endl
<< endl
<< bold << " -C" << normal << " NR, " << bold << "--clpairs=" << normal << "NR [default: 6]" << endl
<< " specifies the minimal number of points for an overlap. If not specified" << endl
<< " cldist is used instead" << endl
<< endl
<< bold << " --cache" << normal << endl
<< " turns on cached k-d tree search" << endl
<< endl
<< bold << " -d" << normal << " NR, " << bold << "--dist=" << normal << "NR [default: 25]" << endl
<< " sets the maximal point-to-point distance for matching with ICP to <NR> 'units'" << endl
<< " (unit of scan data, e.g. cm)" << endl
<< endl
<< bold << " -D" << normal << " NR, " << bold << "--distSLAM="
<< normal << "NR [default: same value as -d option]" << endl
<< " sets the maximal point-to-point distance for matching with SLAM to <NR> 'units'" << endl
<< " (unit of scan data, e.g. cm)" << endl
<< endl
<< bold << " --DlastSLAM" << normal << " NR [default not set]" << endl
<< " sets the maximal point-to-point distance for the final SLAM correction," << endl
<< " if final SLAM is not required don't set it." << endl
<< endl
<< bold << " -e" << normal << " NR, " << bold << "--end=" << normal << "NR" << endl
<< " end after scan NR" << endl
<< endl
<< bold << " --exportAllPoints" << normal << endl
<< " writes all registered reduced points to the file points.pts before" << endl
<< " slam6D terminated" << endl
<< endl
<< bold << " --epsICP=" << normal << "NR [default: 0.00001]" << endl
<< " stop ICP iteration if difference is smaller than NR" << endl
<< endl
<< bold << " --epsSLAM=" << normal << " NR [default: 0.5]" << endl
<< " stop SLAM iteration if average difference is smaller than NR" << endl
<< endl
<< bold << " -f" << normal << " F, " << bold << "--format=" << normal << "F" << endl
<< " using shared library F for input" << endl
<< " (chose F from {uos, uos_map, uos_rgb, uos_frames, uos_map_frames, old, rts, rts_map, ifp, riegl_txt, riegl_rgb, riegl_bin, zahn, ply, wrl, xyz, zuf, iais, front, x3d, rxp, ais })" << endl
<< endl
<< bold << " -G" << normal << " NR, " << bold << "--graphSlam6DAlgo=" << normal << "NR [default: 0]" << endl
<< " selects the minimizazion method for the SLAM matching algorithm" << endl
<< " 0 = no global relaxation technique" << endl
<< " 1 = Lu & Milios extension using euler angles due to Borrmann et al." << endl
<< " 2 = Lu & Milios extension using using unit quaternions" << endl
<< " 3 = HELIX approximation by Hofer and Pottmann" << endl
<< " 4 = small angle approximation" << endl
<< endl
<< bold << " -i" << normal << " NR, " << bold << "--iter=" << normal << "NR [default: 50]" << endl
<< " sets the maximal number of ICP iterations to <NR>" << endl
<< endl
<< bold << " -I" << normal << " NR, " << bold << "--iterSLAM=" << normal << "NR [default: 0]" << endl
<< " sets the maximal number of iterations for SLAM to <NR>" << endl
<< " (if not set, graphSLAM is not executed)" << endl
<< endl
<< bold << " -l" << normal << " NR, " << bold << "--loopsize=" << normal << "NR [default: 20]" << endl
<< " sets the size of a loop, i.e., a loop must exceed <NR> of scans" << endl
<< endl
<< bold << " -L" << normal << " NR, " << bold << "--loop6DAlgo=" << normal << "NR [default: 0]" << endl
<< " selects the method for closing the loop explicitly" << endl
<< " 0 = no loop closing technique" << endl
<< " 1 = euler angles" << endl
<< " 2 = quaternions " << endl
<< " 3 = unit quaternions" << endl
<< " 4 = SLERP (recommended)" << endl
<< endl
<< bold << " --metascan" << normal << endl
<< " Match current scan against a meta scan of all previous scans (default match against the last scan only)" << endl
<< endl
<< bold << " -m" << normal << " NR, " << bold << "--max=" << normal << "NR" << endl
<< " neglegt all data points with a distance larger than NR 'units'" << endl
<< endl
<< bold << " -M" << normal << " NR, " << bold << "--min=" << normal << "NR" << endl
<< " neglegt all data points with a distance smaller than NR 'units'" << endl
<< endl
<< bold << " -n" << normal << " FILE, " << bold << "--net=" << normal << "FILE" << endl
<< " specifies the file that includes the net structure for SLAM" << endl
<< endl
<< bold << " -O" << normal << "NR (optional), " << bold << "--octree=" << normal << "NR (optional)" << endl
<< " use randomized octree based point reduction (pts per voxel=<NR>)" << endl
<< " requires " << bold << "-r" << normal <<" or " << bold << "--reduce" << endl
<< endl
<< bold << " -p, --trustpose" << normal << endl
<< " Trust the pose file, do not extrapolate the last transformation." << endl
<< " (just for testing purposes, or gps input.)" << endl
<< endl
<< bold << " -q, --quiet" << normal << endl
<< " Quiet mode. Suppress (most) messages" << endl
<< endl
<< bold << " -Q, --veryquiet" << normal << endl
<< " Very quiet mode. Suppress all messages, except in case of error." << endl
<< endl
<< bold << " -S, --scanserver" << normal << endl
<< " Use the scanserver as an input method and handling of scan data" << endl
<< endl
<< bold << " -r" << normal << " NR, " << bold << "--reduce=" << normal << "NR" << endl
<< " turns on octree based point reduction (voxel size=<NR>)" << endl
<< endl
<< bold << " -R" << normal << " NR, " << bold << "--random=" << normal << "NR" << endl
<< " turns on randomized reduction, using about every <NR>-th point only" << endl
<< endl
<< bold << " -s" << normal << " NR, " << bold << "--start=" << normal << "NR" << endl
<< " start at scan NR (i.e., neglects the first NR scans)" << endl
<< " [ATTENTION: counting naturally starts with 0]" << endl
<< endl
<< bold << " -t" << normal << " NR, " << bold << "--nns_method=" << normal << "NR [default: 1]" << endl
<< " selects the Nearest Neighbor Search Algorithm" << endl
<< " 0 = simple k-d tree " << endl
<< " 1 = cached k-d tree " << endl
<< " 2 = ANNTree " << endl
<< " 3 = BOCTree " << endl
<< endl
<< bold << " -u" << normal <<", "<< bold<<"--cuda" << normal << endl
<< " this option activates icp running on GPU instead of CPU"<<endl
<< endl << endl;
cout << bold << "EXAMPLES " << normal << endl
<< " " << prog << " dat" << endl
<< " " << prog << " --max=500 -r 10.2 -i 20 dat" << endl
<< " " << prog << " -s 2 -e 10 dat" << endl << endl;
exit(1);
}
/**
* Make type, start and end a write once only class for parseFormatFile because
* we know the directory only after the type, start and end parameters may have
* been written already, so encapsulate this write once behaviour in this class.
*/
template<typename T>
class WriteOnce {
public:
WriteOnce(T& value) : value(value), written(false) {}
WriteOnce& operator=(const T& other) { if(!written) { value = other; written = true; } return *this; }
operator T() const { return value; }
private:
T& value;
bool written;
};
/**
* Parsing of a formats file in the scan directory for default type and scan
* index ranges without overwriting user set parameters. Does nothing if
* file doesn't exist.
*
* @param dir directory the scans and format file are contained in
* @param type which ScanIO to use for the scans in that directory
* @param start index for the first valid scan
* @param end index for the last valid scan
*/
void parseFormatFile(string& dir, WriteOnce<IOType>& type, WriteOnce<int>& start, WriteOnce<int>& end)
{
ifstream file((dir+"format").c_str());
if(!file.good()) return;
string line, key, value, format;
while(getline(file, line)) {
size_t pos = line.find('=');
key = trim(line.substr(0, pos - 0));
value = trim(line.substr(pos+1));
if(key == "format") {
try {
format = value;
type = formatname_to_io_type(format.c_str());
} catch (...) { // runtime_error
cerr << "Error while parsing format file: Format '" << format << "' unknown." << endl;
break;
}
} else if(key == "start") {
stringstream str(value.c_str());
int s;
str >> s;
start = s;
} else if(key == "end") {
stringstream str(value.c_str());
int e;
str >> e;
end = e;
} else {
cerr << "Error while parsing format file: Unknown key '" << key << "'" << endl;
break;
}
}
}
/** A function that parses the command-line arguments and sets the respective flags.
* @param argc the number of arguments
* @param argv the arguments
* @param dir the directory
* @param red using point reduction?
* @param rand use randomized point reduction?
* @param mdm maximal distance match
* @param mdml maximal distance match for SLAM
* @param mni maximal number of iterations
* @param start starting at scan number 'start'
* @param end stopping at scan number 'end'
* @param maxDist - maximal distance of points being loaded
* @param minDist - minimal distance of points being loaded
* @param quiet switches on/off the quiet mode
* @param veryQuiet switches on/off the 'very quiet' mode
* @param extrapolate_pose - i.e., extrapolating the odometry by the last transformation
* (vs. taking the pose file as <b>exact</b>)
* @param meta match against all scans (= meta scan), or against the last scan only???
* @param anim selects the rotation representation for the matching algorithm
* @param mni_lum sets the maximal number of iterations for SLAM
* @param net specifies the file that includes the net structure for SLAM
* @param cldist specifies the maximal distance for closed loops
* @param epsilonICP stop ICP iteration if difference is smaller than this value
* @param epsilonSLAM stop SLAM iteration if average difference is smaller than this value
* @param algo specfies the used algorithm for rotation computation
* @param lum6DAlgo specifies the used algorithm for global SLAM correction
* @param loopsize defines the minimal loop size
* @param tracking select sematic algorithm of none/classification/tracking on/off the point classification mode
* @return 0, if the parsing was successful. 1 otherwise
*/
int parseArgs(int argc, char **argv, string &dir, double &red, int &rand,
double &mdm, double &mdml, double &mdmll,
int &mni, int &start, int &end, int &maxDist, int &minDist, bool &quiet, bool &veryQuiet,
bool &extrapolate_pose, bool &meta, int &algo,int &tracking, int &loopSlam6DAlgo, int &lum6DAlgo, int &anim,
int &mni_lum, string &net, double &cldist, int &clpairs, int &loopsize,int &trackingAlgo,
double &epsilonICP, double &epsilonSLAM, int &nns_method, bool &exportPts, double &distLoop,
int &iterLoop, double &graphDist, int &octree, bool &cuda_enabled, IOType &type,
bool& scanserver)
{
int c;
// from unistd.h:
extern char *optarg;
extern int optind;
WriteOnce<IOType> w_type(type);
WriteOnce<int> w_start(start), w_end(end);
/* options descriptor */
// 0: no arguments, 1: required argument, 2: optional argument
static struct option longopts[] = {
{ "format", required_argument, 0, 'f' },
{ "algo", required_argument, 0, 'a' },
{ "tracking", required_argument, 0, 'b' },
{ "track_value", required_argument, 0, 'T' },
{ "nns_method", required_argument, 0, 't' },
{ "loop6DAlgo", required_argument, 0, 'L' },
{ "graphSlam6DAlgo", required_argument, 0, 'G' },
{ "net", required_argument, 0, 'n' },
{ "iter", required_argument, 0, 'i' },
{ "iterSLAM", required_argument, 0, 'I' },
{ "max", required_argument, 0, 'm' },
{ "loopsize", required_argument, 0, 'l' },
{ "cldist", required_argument, 0, 'c' },
{ "clpairs", required_argument, 0, 'C' },
{ "min", required_argument, 0, 'M' },
{ "dist", required_argument, 0, 'd' },
{ "distSLAM", required_argument, 0, 'D' },
{ "start", required_argument, 0, 's' },
{ "end", required_argument, 0, 'e' },
{ "reduce", required_argument, 0, 'r' },
{ "octree", optional_argument, 0, 'O' },
{ "random", required_argument, 0, 'R' },
{ "quiet", no_argument, 0, 'q' },
{ "veryquiet", no_argument, 0, 'Q' },
{ "trustpose", no_argument, 0, 'p' },
{ "anim", required_argument, 0, 'A' },
{ "metascan", no_argument, 0, '2' }, // use the long format only
{ "DlastSLAM", required_argument, 0, '4' }, // use the long format only
{ "epsICP", required_argument, 0, '5' }, // use the long format only
{ "epsSLAM", required_argument, 0, '6' }, // use the long format only
{ "exportAllPoints", no_argument, 0, '8' },
{ "distLoop", required_argument, 0, '9' }, // use the long format only
{ "iterLoop", required_argument, 0, '1' }, // use the long format only
{ "graphDist", required_argument, 0, '3' }, // use the long format only
{ "cuda", no_argument, 0, 'u' }, // cuda will be enabled
{ "trackingAlgo", required_argument, 0, 'y'},//tracking algorithm
{ "scanserver", no_argument, 0, 'S' },
{ 0, 0, 0, 0} // needed, cf. getopt.h
};
cout << endl;
while ((c = getopt_long(argc, argv, "T:O:v:f:A:G:L:a:b:t:r:R:d:D:i:l:I:c:C:n:S:s:e:m:M:y:u:q:Q:p", longopts, NULL)) != -1)
switch (c)
{
case 'a':
algo = atoi(optarg);
if ((algo < 0) || (algo > 9)) {
cerr << "Error: ICP Algorithm not available." << endl;
exit(1);
}
break;
case 'b':
tracking = atoi(optarg);
break;
case 'v':
save_animation = true;
anim_frame_rate = atoi(optarg);
break;
case 'T':
constant_static_or_moving = atof(optarg);
if ((constant_static_or_moving < 0) || (constant_static_or_moving > 300)) {
cerr << "Error: constant_static_or_moving not available." << endl;
exit(1);
}
break;
case 't':
nns_method = atoi(optarg);
if ((nns_method < 0) || (nns_method > 3)) {
cerr << "Error: NNS Method not available." << endl;
exit(1);
}
break;
case 'L':
loopSlam6DAlgo = atoi(optarg);
if (loopSlam6DAlgo < 0 || loopSlam6DAlgo > 6) {
cerr << "Error: global loop closing algorithm not available." << endl;
exit(1);
}
break;
case 'G':
lum6DAlgo = atoi(optarg);
if ((lum6DAlgo < 0) || (lum6DAlgo > 6)) {
cerr << "Error: global relaxation algorithm not available." << endl;
exit(1);
}
break;
case 'c':
cldist = atof(optarg);
break;
case 'C':
clpairs = atoi(optarg);
break;
case 'l':
loopsize = atoi(optarg);
break;
case 'r':
red = atof(optarg);
break;
case 'O':
if (optarg) {
octree = atoi(optarg);
} else {
octree = 1;
}
break;
case 'R':
rand = atoi(optarg);
break;
case 'd':
mdm = atof(optarg);
break;
case 'D':
mdml = atof(optarg);
break;
case 'i':
mni = atoi(optarg);
break;
case 'I':
mni_lum = atoi(optarg);
break;
case 'n':
net = optarg;
break;
case 's':
w_start = atoi(optarg);
if (w_start < 0) { cerr << "Error: Cannot start at a negative scan number.\n"; exit(1); }
break;
case 'e':
w_end = atoi(optarg);
if (w_end < 0) { cerr << "Error: Cannot end at a negative scan number.\n"; exit(1); }
if (w_end < w_start) { cerr << "Error: <end> cannot be smaller than <start>.\n"; exit(1); }
break;
case 'm':
maxDist = atoi(optarg);
break;
case 'M':
minDist = atoi(optarg);
break;
case 'q':
quiet = true;
break;
case 'Q':
quiet = veryQuiet = true;
break;
case 'p':
extrapolate_pose = false;
break;
case 'y':
trackingAlgo=atoi(optarg);//choose tracking algorithm
break;
case 'A':
anim = atoi(optarg);
break;
case '2': // = --metascan
meta = true;
break;
case '4': // = --DlastSLAM
mdmll = atof(optarg);
break;
case '5': // = --epsICP
epsilonICP = atof(optarg);
break;
case '6': // = --epsSLAM
epsilonSLAM = atof(optarg);
break;
case '8': // not used
exportPts = true;
break;
case '9': // = --distLoop
distLoop = atof(optarg);
break;
case '1': // = --iterLoop
iterLoop = atoi(optarg);
break;
case '3': // = --graphDist
graphDist = atof(optarg);
break;
case 'f':
try {
w_type = formatname_to_io_type(optarg);
} catch (...) { // runtime_error
cerr << "Format " << optarg << " unknown." << endl;
abort();
}
break;
case 'u':
cuda_enabled = true;
break;
case 'S':
scanserver = true; // maybe some errors.
break;
case '?':
usage(argv[0]);
return 1;
default:
abort ();
}
scanserver = true;
if (optind != argc-1)
{
cerr << "\n*** Directory missing ***" << endl;
usage(argv[0]);
}
dir = argv[optind];
#ifndef _MSC_VER
if (dir[dir.length()-1] != '/') dir = dir + "/";
#else
if (dir[dir.length()-1] != '\\') dir = dir + "\\";
#endif
parseFormatFile(dir, w_type, w_start, w_end);
return 0;
}
/**
* This function is does all the matching stuff
* it iterates over all scans using the algorithm objects to calculate new poses
* objects could be NULL if algorithm should not be used
*
* @param cldist maximal distance for closing loops
* @param loopsize minimal loop size
* @param allScans Contains all laser scans
* @param my_icp6D the ICP implementation
* @param meta_icp math ICP against a metascan
* @param nns_method Indicates the nearest neigbor search method to be used
* @param my_loopSlam6D used loopoptimizer
* @param my_graphSlam6D used global optimization
* @param nrIt The number of iterations the global SLAM-algorithm will run
* @param epsilonSLAM epsilon for global SLAM iteration
* @param mdml maximal distance match for global SLAM
* @param mdmll maximal distance match for global SLAM after all scans ar matched
*/
void matchGraph6Dautomatic(double cldist, int loopsize, vector <Scan *> allScans, icp6D *my_icp6D,
bool meta_icp, int nns_method, bool cuda_enabled,
loopSlam6D *my_loopSlam6D, graphSlam6D *my_graphSlam6D, int nrIt,
double epsilonSLAM, double mdml, double mdmll, double graphDist,
bool &eP, IOType type)
{
double cldist2 = sqr(cldist);
// list of scan for metascan
vector < Scan* > metas;
// graph for loop optimization
graph_t g;
int n = allScans.size();
int loop_detection = 0;
double dist, min_dist = -1;
int first = 0, last = 0;
for(int i = 1; i < n; i++) {
cout << i << "/" << n << endl;
add_edge(i-1, i, g);
if(eP) {
allScans[i]->mergeCoordinatesWithRoboterPosition(allScans[i-1]);
}
//Hack to get all icp transformations into the .frames Files
if(i == n-1 && my_icp6D != NULL && my_icp6D->get_anim() == -2) {
my_icp6D->set_anim(-1);
}
/*if(i == 85 || i == 321 || i == 533) {
my_icp6D->set_anim(1);
}*/
if(my_icp6D != NULL){
cout << "ICP" << endl;
// Matching strongly linked scans with ICPs
if(meta_icp)
{
// metas.push_back(allScans[i - 1]);
// MetaScan* meta_scan = new MetaScan(metas);
// my_icp6D->match(meta_scan, allScans[i]);
//delete meta_scan;
} else {
switch(type) {
case UOS_MAP:
case UOS_MAP_FRAMES:
my_icp6D->match(allScans[0], allScans[i]);
break;
case RTS_MAP:
//untested (and could not work)
//if(i < 220-22 && i > 250-22) match(allScans[0], CurrentScan);
my_icp6D->match(allScans[0], allScans[i]);
break;
default:
my_icp6D->match(allScans[i - 1], allScans[i]);
break;
}
}
} else {
double id[16];
M4identity(id);
allScans[i]->transform(id, Scan::ICP, 0);
}
/*if(i == 85 || i == 321 || i == 533) {
my_icp6D->set_anim(-2);
}*/
if(loop_detection == 1) {
loop_detection = 2;
}
for(int j = 0; j < i - loopsize; j++) {
dist = Dist2(allScans[j]->get_rPos(), allScans[i]->get_rPos());
if(dist < cldist2) {
loop_detection = 1;
if(min_dist < 0 || dist < min_dist) {
min_dist = dist;
first = j;
last = i;
}
}
}
if(loop_detection == 2) {
loop_detection = 0;
min_dist = -1;
if(my_loopSlam6D != NULL) {
cout << "Loop close: " << first << " " << last << endl;
my_loopSlam6D->close_loop(allScans, first, last, g);
add_edge(first, last, g);
}
if(my_graphSlam6D != NULL && mdml > 0) {
int j = 0;
double ret;
do {
// recalculate graph
Graph *gr = new Graph(i + 1, cldist2, loopsize);
cout << "Global: " << j << endl;
ret = my_graphSlam6D->doGraphSlam6D(*gr, allScans, 1);
delete gr;
j++;
} while (j < nrIt && ret > epsilonSLAM);
}
}
}
if(loop_detection == 1 && my_loopSlam6D != NULL) {
cout << "Loop close: " << first << " " << last << endl;
my_loopSlam6D->close_loop(allScans, first, last, g);
add_edge(first, last, g);
}
if(my_graphSlam6D != NULL && mdml > 0.0) {
int j = 0;
double ret;
do {
// recalculate graph
Graph *gr = new Graph(n, cldist2, loopsize);
cout << "Global: " << j << endl;
ret = my_graphSlam6D->doGraphSlam6D(*gr, allScans, 1);
delete gr;
j++;
} while (j < nrIt && ret > epsilonSLAM);
}
if(my_graphSlam6D != NULL && mdmll > 0.0) {
my_graphSlam6D->set_mdmll(mdmll);
int j = 0;
double ret;
do {
// recalculate graph
Graph *gr = new Graph(n, sqr(graphDist), loopsize);
cout << "Global: " << j << endl;
ret = my_graphSlam6D->doGraphSlam6D(*gr, allScans, 1);
delete gr;
j++;
} while (j < nrIt && ret > epsilonSLAM);
}
}
icp6Dminimizer * CreateICPalgo( int algo , bool quiet )
{
icp6Dminimizer *my_icp6Dminimizer = 0;
switch (algo) {
case 1 :
my_icp6Dminimizer = new icp6D_QUAT(quiet);
break;
case 2 :
my_icp6Dminimizer = new icp6D_SVD(quiet);
break;
case 3 :
my_icp6Dminimizer = new icp6D_ORTHO(quiet);
break;
case 4 :
my_icp6Dminimizer = new icp6D_DUAL(quiet);
break;
case 5 :
my_icp6Dminimizer = new icp6D_HELIX(quiet);
break;
case 6 :
my_icp6Dminimizer = new icp6D_APX(quiet);
break;
case 7 :
my_icp6Dminimizer = new icp6D_LUMEULER(quiet);
break;
case 8 :
my_icp6Dminimizer = new icp6D_LUMQUAT(quiet);
break;
case 9 :
my_icp6Dminimizer = new icp6D_QUAT_SCALE(quiet);
break;
}
return my_icp6Dminimizer;
}
int FinalSLAM( double &red, int &rand,
double &mdm, double &mdml, double &mdmll,
int &mni, int &start, int &end, int &maxDist, int &minDist, bool &quiet, bool &veryQuiet,
bool &eP, bool &meta, int &algo, int &loopSlam6DAlgo, int &lum6DAlgo, int &anim,
int &mni_lum, string &net, double &cldist, int &clpairs, int &loopsize,
double &epsilonICP, double &epsilonSLAM, int &nns_method, bool &exportPts, double &distLoop,
int &iterLoop, double &graphDist, int &octree, bool &cuda_enabled, IOType &type
)
{
icp6Dminimizer *my_icp6Dminimizer = 0;
my_icp6Dminimizer= CreateICPalgo( algo, quiet);
if (mni_lum == -1 && loopSlam6DAlgo == 0)
{
icp6D *my_icp = 0;
if (cuda_enabled) {
#ifdef WITH_CUDA
my_icp = new icp6Dcuda(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, cuda_enabled);
#else
cout << "slam6d was not compiled for excuting CUDA code" << endl;
#endif
} else {
my_icp = new icp6D(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, cuda_enabled);
}
if (my_icp) my_icp->doICP(Scan::allScans);
delete my_icp;
} else if (clpairs > -1) {
//!!!!!!!!!!!!!!!!!!!!!!!!
icp6D *my_icp = 0;
if (cuda_enabled) {
#ifdef WITH_CUDA
my_icp = new icp6Dcuda(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, cuda_enabled);
#else
cout << "slam6d was not compiled for excuting CUDA code" << endl;
#endif
} else {
my_icp = new icp6D(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, cuda_enabled);
}
my_icp->doICP(Scan::allScans);
graphSlam6D *my_graphSlam6D = new lum6DEuler(my_icp6Dminimizer, mdm, mdml, mni, quiet, meta,
rand, eP, anim, epsilonICP, nns_method, epsilonSLAM);
my_graphSlam6D->matchGraph6Dautomatic(Scan::allScans, mni_lum, clpairs, loopsize);
//!!!!!!!!!!!!!!!!!!!!!!!!
} else {
graphSlam6D *my_graphSlam6D = 0;
switch (lum6DAlgo) {
case 1 :
my_graphSlam6D = new lum6DEuler(my_icp6Dminimizer, mdm, mdml, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, epsilonSLAM);
break;
case 2 :
my_graphSlam6D = new lum6DQuat(my_icp6Dminimizer, mdm, mdml, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, epsilonSLAM);
break;
case 3 :
my_graphSlam6D = new ghelix6DQ2(my_icp6Dminimizer, mdm, mdml, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, epsilonSLAM);
break;
case 4 :
my_graphSlam6D = new gapx6D(my_icp6Dminimizer, mdm, mdml, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, epsilonSLAM);
break;
}
// Construct Network
if (net != "none") {
icp6D *my_icp = 0;
if (cuda_enabled) {
#ifdef WITH_CUDA
my_icp = new icp6Dcuda(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method);
#else
cout << "slam6d was not compiled for excuting CUDA code" << endl;
#endif
} else {
my_icp = new icp6D(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method);
}
my_icp->doICP(Scan::allScans);
Graph* structure;
structure = new Graph(net);
my_graphSlam6D->doGraphSlam6D(*structure, Scan::allScans, mni_lum);
if(mdmll > 0.0) {
my_graphSlam6D->set_mdmll(mdmll);
my_graphSlam6D->doGraphSlam6D(*structure, Scan::allScans, mni_lum);
}
} else {
icp6D *my_icp = 0;
if(algo > 0) {
if (cuda_enabled) {
#ifdef WITH_CUDA
my_icp = new icp6Dcuda(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method);
#else
cout << "slam6d was not compiled for excuting CUDA code" << endl;
#endif
} else {
my_icp = new icp6D(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method);
}
loopSlam6D *my_loopSlam6D = 0;
switch(loopSlam6DAlgo) {
case 1:
my_loopSlam6D = new elch6Deuler(veryQuiet, my_icp6Dminimizer, distLoop, iterLoop,
rand, eP, 10, epsilonICP, nns_method);
break;
case 2:
my_loopSlam6D = new elch6Dquat(veryQuiet, my_icp6Dminimizer, distLoop, iterLoop,
rand, eP, 10, epsilonICP, nns_method);
break;
case 3:
my_loopSlam6D = new elch6DunitQuat(veryQuiet, my_icp6Dminimizer, distLoop, iterLoop,
rand, eP, 10, epsilonICP, nns_method);
break;
case 4:
my_loopSlam6D = new elch6Dslerp(veryQuiet, my_icp6Dminimizer, distLoop, iterLoop,
rand, eP, 10, epsilonICP, nns_method);
break;
}
matchGraph6Dautomatic(cldist, loopsize, Scan::allScans, my_icp, meta,
nns_method, cuda_enabled, my_loopSlam6D, my_graphSlam6D,
mni_lum, epsilonSLAM, mdml, mdmll, graphDist, eP, type);
delete my_icp;
if(loopSlam6DAlgo > 0) {
delete my_loopSlam6D;
}
}
if(my_graphSlam6D > 0) {
delete my_graphSlam6D;
}
}
}
delete my_icp6Dminimizer;
return 0;
}
void MatchTwoScan(icp6D *my_icp, VeloScan* currentScan, int scanCount, bool eP )
{
Scan *PreviousScan = 0;
//////////////////////ICP//////////////////////
if (scanCount > 0)
{
PreviousScan = Scan::allScans[scanCount-1];
// extrapolate odometry // <20><>ǰһ֡<D2BB><D6A1><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ϊ<EFBFBD><CEAA>׼
if (eP)
currentScan->mergeCoordinatesWithRoboterPosition(PreviousScan);
my_icp->match(PreviousScan, currentScan);
}
}
/**
* Main program for 6D SLAM.
* Usage: bin/slam6D 'dir',
* with 'dir' the directory of a set of scans
* ...
*/
int main(int argc, char **argv)
{
#ifndef _MSC_VER
glutInit(&argc, argv);
#else
glutInit(&argc, argv);
#endif
signal (SIGSEGV, sigSEGVhandler);
signal (SIGINT, sigSEGVhandler);
cout << "slam6D - A highly efficient SLAM implementation based on scan matching" << endl
<< " with 6 degrees of freedom" << endl
<< "(c) Jacobs University Bremen gGmbH, Germany, since 2009" << endl
<< " University of Osnabrueck, Germany, 2006 - 2009" << endl << endl;
if (argc <= 1) {
usage(argv[0]);
}
// parsing the command line parameters
// init, default values if not specified
string dir;
double red = -1.0, mdmll = -1.0, mdml = 25.0, mdm = 25.0;
int rand = -1, mni = 50;
int start = 0, end = -1;
bool quiet = false;
bool veryQuiet = false;
int maxDist = -1;
int minDist = -1;
bool eP = true; // should we extrapolate the pose??
bool meta = false; // match against meta scan, or against LAST scan only?
int algo = 1;
int mni_lum = -1;
double cldist = 500;
int clpairs = -1;
int loopsize = 20;
string net = "none";
int anim = -1;
double epsilonICP = 0.00001;
double epsilonSLAM = 0.5;
int nns_method = simpleKD;
bool exportPts = false;
int loopSlam6DAlgo = 0;
int lum6DAlgo = 0;
int tracking = 1;
double distLoop = 700.0;
int iterLoop = 100;
double graphDist = cldist;
int octree = 0; // employ randomized octree reduction?
bool cuda_enabled = false;
IOType type = UOS;
int trackingAlgo=0;
bool scanserver = false;
parseArgs(argc, argv, dir, red, rand, mdm, mdml, mdmll, mni, start, end,
maxDist, minDist, quiet, veryQuiet, eP, meta, algo, tracking,
loopSlam6DAlgo, lum6DAlgo, anim,
mni_lum, net, cldist, clpairs, loopsize, trackingAlgo,epsilonICP, epsilonSLAM,
nns_method, exportPts, distLoop, iterLoop, graphDist, octree, cuda_enabled, type,
scanserver);
cout << "VeloSLAM will proceed with the following parameters:" << endl;
//@@@ to do :-)
icp6Dminimizer *my_icp6Dminimizer = 0;
my_icp6Dminimizer= CreateICPalgo( algo, quiet);
icp6D *my_icp = 0;
my_icp = new icp6D(my_icp6Dminimizer, mdm, mni, quiet, meta, rand, eP,
anim, epsilonICP, nns_method, cuda_enabled);
if (my_icp==0)
{
cerr<< "can not create ICP " << endl;
exit(0);
}
Scan::openDirectory(scanserver, dir, type, start, end);
if(VeloScan::allScans.size() == 0) {
cerr << "No scans found. Did you use the correct format?" << endl;
exit(-1);
}
double eu[6] = {0.0, 0.0, 0.0, 0.0, 0.0, 0.0};
vector <Point> ptss;
veryQuiet =true;
if(!veryQuiet)
StartShow();
ICPFinished =true;
//Main Loop for ICP with Moving Object Detection and Tracking
for(ScanVector::iterator it = Scan::allScans.begin();
it != Scan::allScans.end();
++it)
{
while(DebugDrawFinished ==false && !veryQuiet)
{
Sleep(1);
}
VeloScan* currentScan =(VeloScan* ) *it;
currentScan->setRangeFilter(maxDist, minDist);
currentScan->setReductionParameter(red, octree);
currentScan->setSearchTreeParameter(nns_method, cuda_enabled);
currentScan->isTrackerHandled=false;
currentScan->scanid = scanCount; ///
ICPFinished =false;
if(tracking ==1 )
{
currentScan->FindingAllofObject(maxDist, minDist);
currentScan->ClassifiAllofObject();
}
if(tracking ==2 )
{
int windowsize =3;
currentScan->FindingAllofObject(maxDist, minDist);
currentScan->TrackingAllofObject(trackingAlgo);
currentScan->ClassifibyTrackingAllObject(scanCount, windowsize);
// trackMgr.ListTrackers();
}
if( tracking ==0 || tracking ==1 ||tracking ==2 )
{
currentScan->ExchangePointCloud();
currentScan->calcReducedPoints_byClassifi(red, octree, PointType());
}
currentScan->createSearchTree();
#ifdef NO_SLIDING_WINDOW
MatchTwoScan(my_icp, currentScan, scanCount, eP);
#else
if(current_sliding_window_pos > sliding_window_size )
MatchTwoScan(my_icp, currentScan, sliding_window_size, eP);
else
MatchTwoScan(my_icp, currentScan, scanCount, eP);
#endif
// update the cluster position in trakers.
///////////////////////////////////////////////////////////////////
const double* p;
p = currentScan->get_rPos();
Point x(p[0], p[1], p[2]);
VelodyneTrajectory.path.push_back(x);
//////////////////////////////////////////
scanCount++;
current_sliding_window_pos++;
#ifdef NO_SLIDING_WINDOW
#else
if(current_sliding_window_pos > sliding_window_size )
{
vector <Scan*>::iterator Iter = Scan::allScans.begin();
VeloScan *deleteScan = (VeloScan*)(*Iter);
// cout << "delete scan " << deleteScan->scanid << endl;
delete deleteScan;
}
#endif
ICPFinished =true;
if(!veryQuiet)
{
glutPostRedisplay();
}
while(DebugDrawFinished ==false && !veryQuiet)
{
Sleep(1);
}
////////////////////////////////////////
}
// long starttime = GetCurrentTimeInMilliSec();
// //Finall graph Matching
// FinalSLAM( red, rand,
// mdm, mdml, mdmll,
// mni, start, end, maxDist, minDist, quiet, veryQuiet,
// eP, meta, algo, loopSlam6DAlgo, lum6DAlgo, anim,
// mni_lum, net, cldist, clpairs, loopsize,
// epsilonICP, epsilonSLAM, nns_method, exportPts, distLoop,
// iterLoop, graphDist, octree, cuda_enabled, type
//);
if (exportPts)
{
cout << "Export all 3D Points to file \"points.pts\"" << endl;
ofstream redptsout("points.pts");
for(unsigned int i = 0; i < Scan::allScans.size(); i++)
{
DataXYZ xyz_r(Scan::allScans[i]->get("xyz reduced"));
for(unsigned int i = 0; i < xyz_r.size(); ++i)
redptsout << xyz_r[i][0] << ' ' << xyz_r[i][1] << ' ' << xyz_r[i][2] << '\n';
redptsout << std::flush;
}
}
for(ScanVector::iterator it = Scan::allScans.begin(); it != Scan::allScans.end(); ++it)
{
Scan* scan = *it;
scan->saveFrames();
}
Scan::closeDirectory();
delete my_icp6Dminimizer;
delete my_icp;
cout << endl << endl;
cout << "Normal program end." << endl;
}