Optimal Autonomous Pursuit of an Intruder on a Grid Aided by Local Node and Edge Sensors
Abstract
Timely detection of intruders ensures the safety and security of high valued assets within a protected area. This problem takes on particular significance across international borders and becomes challenging when the terrain is porous, rugged and treacherous in nature. Keeping an effective vigil against intruders on large tracts of land is a tedious task; currently, it is primarily performed by security personnel with automatic detection systems in passive supporting roles. This paper discusses an alternate autonomous approach by utilizing one or more Unmanned Vehicles (UVs), aided by smart sensors on the ground, to detect and localize an intruder. To facilitate autonomous UV operations, the region is equipped with Unattended Ground Sensors (UGSs) and laser fencing. Together, these sensors provide time-stamped location information (node and edge detection) of the intruder to a UV. For security reasons, we assume that the sensors are not networked (a central node can be disabled bringing the whole system down) and so, the UVs must visit the vicinity of the sensors to gather the information therein. This makes the problem challenging in that pursuit must be done with local and likely delayed information. We discretize time and space by considering a 2D grid for the area and unit speed for the UV, i.e. it takes one time unit to travel from one node to an adjacent node. The intruder is slower and takes two time steps to complete the same move. We compute the min–max optimal, i.e. minimum number of steps to capture the intruder under worst-case intruder actions, for different number of rows and columns in the grid and for both one and two pursuers.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 10, 2021
- Source ID
- 10.1142/s2301385022500054
Entities
People
- David W. Casbeer
- Krishnamoorthy Kalyanam
- Sufal Chandra Swar
- Suresh Manickam
- Swaroop Darbha
Organizations
- Aeronautical Development Establishment
- Air Force Research Laboratory
- Ames Research Center
- Texas A&M University