6. 1. Path finding
• Building a graph
2. Path planning
• Where to go on the graph at any given moment
Patrol
7. 1. Find shortest route between points
2. Good for solving mazes
3. Field based heavily on Dijkstra's algorithm
Path finding
8. • Creating the graph
• Find observation points
• Create routes between observation points
• Take hazard forces into consideration
• Base on Real achievable types of data
My Contribution
11. 1. Part of the IDF ground forces weapons development department
2. Assists in evaluating
1. New weapons
2. New combat doctrines
3. Aided in human engineering for new systems
3. The lab can simulate a virtual battle space
4. It’s techniques are similar to the gaming industry
5. The lab is located outside “Tel Hashomer”
6. Come visit
Battle Lab
13. 1. I am in-charged of the CGF team
2. The team is responsible of all virtual autonomous entities
3. Virtual entities types are vehicles & humans
4. The battle space can be in open & urban areas
5. Combat can be close & far range
6. Entities use COTS product called B-Have for path finding
Computer Generated Forces
16. 1. An abstract data structure used in AI applications
2. Aids agents in path-finding through large spaces
Navigation Mesh
17. 1. Done offline, no dynamic path finding
2. No collision avoidance algorithms
3. A lot of needed starting materials
I. DTM
II. vector data
4. Large terrain
• there are many paths from one point to another
Project Highlights
18. 1. Responsible for intel gathering by using visual means
1. Satellites
2. Unmanned aerial vehicle
3. Ground Sensors
2. The map unit is responsible for data distribution
3. Route planning is based on the maps received from them
9900 division
19. • The collection, analysis, evaluation, and interpretation of geographic
information on the natural and man-made features of the terrain, to
predict the effect of terrain on military operations
3DTerrain Analysis
21. 1. Also known as
1. digital Terrain model (DTM)
2. digital surface model (DSM)
2. A 3D representation of a terrain's surface
3. Represented as
1. A raster (a grid of squares)
2. A vector-based triangular irregular network (TIN).
4. Produced by types of radar
Digital elevation model (DEM)
TIN
23. 1. Applies different color symbols to represent elevation or depth zones
HypsometricTinting
24. 1. Contour lines connect points of equal elevation
2. They are very intuitive for humans
Contour Lines
25. 1. Setting a hypothetical light source
2. Calculating the illumination values for each cell
3. It can greatly enhance the visualization of a surface for analysis
Hill shade
26. 1. Identifies the cells in an input raster that can be seen
2. It is useful for finding the visibility
3. For instance, finding a well-exposed places for communication towers
Viewshed
27. • Slope measures the rate of change of elevation at a surface location
Slope
28. 1. A coordinate-based data model
2. Represents geographic features as points, lines, and polygons
Vector Data
29. 1. Create a cost distance layer
I. Data analysis
II. Reclassification
III. Accumulate
IV. Distance cost + Direction
2. Find path
Path Finding withTerrain Analysis
30. • Make all data sets simpler and in the same range
Reclassification
31. • Sum data sets with weights
Accumulated Cost layer
35. Input
1. Terrain data
I. Elevation map (DTM)
II. Vector data
1) Roads
2) Rivers
3) Houses
4) Forests
5) Fields
6) Walls
7) Man made obstacles
8) Soil types
2. Vehicle configuration
The Project
36. Output
1. Observation points
• An array of geographical points ( x,y,z)
2. A graph of Routes between observation points
• For each route:
I. An array of geographical points
II. The cost of each route
The Project
37. • How to find observation points
• Find points that are higher than all there surrounding points
Finding Peaks
38. 1. For each observation point
1. Create a cost layer
2. Find paths to all other observation points
2. Dissolve graph
Creating Graph
40. • Full Graph
• Some routes are similar to other routes
Example
A
E
G
F
C
D
B
41. • Removing all unnecessary routes
Graph Dissolving
A
E
G
F
C
D
B
42. 1. Threat types
I. Short range AT units
II. Improvised explosive device
2. Patrol routes are known to enemy
• No point in hiding !!!!
3. Avoid Areas with high probability of ambush
• Unseen areas from most angles
I. Forests
II. Ravines
Path planning inThreatened Area
43. • Data resolution isn’t that high
• Cant analysis small cracks in the mountain
• Prefer high ground terrain
• Stay away from forests
• Select routes that are watched by our observers
Path planning inThreatened Area
44. • Is the path from A to B going to be the path from B to A
• Are threats based on direction ?
• Should the cost be different ?
• How to decide the weights for each type of layer ?
• Is shorter path preferred than safer ?
• Is a steep short path preferred that a long moderate path ?
• Should the weights be set according to vehicle fuel consumption ?
• How should routes be dissolved ?
Things to think about
45. 1. For real world path finding- use terrain analysis
2. Battle lab also works in this field and can assist others
3. Problem with data not being precise enough
4. For creating a real word graph
I. Create data set layers from DEM & vector data
II. Find peaks
III. Reclassify & accumulate data into a cost layer
IV. Create a cost distance layer for each point
V. Create paths/routes from point to al other points
VI. Merging all routes and dissolve similar routes
5. Prefer high ground routes that are watched
6. Problem in deciding weights and costs
Summary
