Optimal exploration path Code
Optimal exploration of grid environments for a realistic robot.
Brought to you by:
quattrinili
| File | Date | Author | Commit |
|---|---|---|---|
| incl | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
| src | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
| tools | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
| Doxyfile | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
| Makefile | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
| README | 2013-12-28 | quattrinili | [r3] Updated README file. |
| main.cpp | 2013-12-14 | quattrinili | [r1] Code for finding exploration path |
=============================================================================
C++ Exploration problem solver
Alberto Quattrini Li
Politecnico di Milano, Italy
21/12/2013
=============================================================================
STRUCTURE OF FOLDER
===================
-ROOT-+- : contains Doxyfile, README, Makefile (linux), and main.cpp
|
|-incl : headers of classes
|-src : sources of classes
'-tools: contains source code of another method
INSTRUCTIONS
============
To compile the program, just use the make tool.
Dependencies:
- OpenCV
- google-glog
- google-gflags
-Linux
1.Have installed g++ and make
2.take Makefile related to linux in the root
3.launch make
To change parameters to the problem you can use the parameters specified by
gflags
The format of the map should be a gray-scale image, where white (255) represents
free space, and gray (128) represents obstacles. In the output images, black (0)
represents unknown area.
DESCRIPTION
===========
The search class library provided is meant to be used for finding the best
path, assuming that we already know the map.
In this way, we can compare, given a map, how distant the result given by
online algorithms is from the optimal execution of the path.