Intercepting a Moving Target in
Under the guidance of
Prof. N. L. Sarda
Given a road
number of pursuers and one
evader, devise a strategy to coordinate all pursuers to
capture the evader.
Speed of pursuer and evader not bounded
Pursuer receiving regular updates about evader position
Pursuer knows the initial position of the
Devising the strategy:
Here the aim is to develop a strategy
for pursuers considering the constraints of a road network.
Presently a simple shortest path strategy is implemented.
Developing an intelligent strategy for evader can help check
the efficiency of the pursuer strategy.
Here the aim is to develop a web based
interface for simulation and analysis of the strategies.
The interface will allow the user to select the simulation
parameters like starting nodes for pursuer and evader,
no. of pursuers and no. of evaders, etc.
The work by Parsons and Motwani have focussed on the
visibility based pursuit
Some others have advocated the use of randomized solutions
as the probability of pursuer catching evader increases
Most of the works have focussed on polygonal environments
None of the work encountered have focussed on road
Randomized strategy as given in  using RRTs focusses on
polygonal regions but can be adapted for graphs as well
Limitations of earlier works
Road networks are very different from the robotic
Dynamic constraints on fuel, roads,traffic conditions, number
of vehicles available
Bounded and polygonal environment
No constraints on paths
No constraints on number of pursuers
Possible pursuer strategies:
Shortest path to evader at every update
Dividing the area into n parts for n pursuers
Heuristic based strategies: roadblocks, toll booths, etc.
Moving away from the initial point
Heuristic based strategies: crowded roads, narrow roads, hiding place, etc
Pursuer within some small distance of
evader (in case of line of sight)
event simulation has been implemented to test and
analyse the strategies.
problem is simulated with one pursuer and one evader with
Shortest path at every update
Random run and moving
far away from the
evader within some distance of pursuer
Pursuer needs random updates to follow evader
Total number of events in the simulation can not be more than 1000
Simulation is over if it one of the two conditions are satisfied:
Evader is caught
Total number of events become more than 1000
based visualization software is
developed to monitor and analyze the process
User can set the simulation parameters, can
select the initial nodes for pursuer and evader.
Developed using JSP, Servlets and OpenLayers
user selects the map
sets the no. of pursuers and
map id is passed to the
fetches the map data using the
prepares a mapInfo obj
stores the obj in the session
user selects the initial nodes
sets the simulation parameters
run the simulation
prepares a Simulate obj.
sets the simulation params
run the simulation
stores the simObj in the session
user monitors the simulation
user can control the process by
advancing the simulation
Nodes (joints in a MULTILINESTRING where LINESTRINGS meet), needs to be extracted using
some external software, e.g.:
or a specific program written for this
SHP to GML
Convert the map
Convert the map
Create a table map<id> with following columns:
road ids in the map
geometry column containing roads as MULTILINESTRING geometry
Create a table map<id>_nodes with following columns:
original road ids in ascending order
geometry column containing nodes as POINT geometry
the map network
nodes in the map
Results: capture time vs. number of
Map used: Hyderabad Road Network
Difficulty of taking into account all the factors
responsible in chase is avoided by measuring
the simulation time over 10 and 20 simulation
runs and averaging the results
Result: measured over 10 simulation
Results: measured over 20 simulation
Developing heuristic based strategies for both pursuer
Incorporating the road constraints
Automating all the tasks in required in the preprocessing
Use of Raster layers instead of vector layers for displaying
map will speed up the process
 Theory and Applications of Graphs, chapter Pursuit
evasion in a
graph. Springer Berlin / Heidelberg, 1978.
 A. AlDahak and A. Elnagar. A practical pursuit
Detection and tracking. In Robotics and Automation, 2007 IEEE
International Conference on, pages 343
348, April 2007.
 W. Herbert and F. Mili. Route guidance: State of the art vs. state of
the practice. In Intelligent Vehicles Symposium, 2008 IEEE, pages
11671174, June 2008.
 L. J. Guibas, J.
C. Latombe, S. M. LaValle, D. Lin, and R. Motwani.
evasion problem. In Intl. J. of
Computational Geometry Applications, volume 9, pages 471