Pursuit on a Graph Using Partial Information

TL;DR

This paper develops an optimal pursuit strategy on a road network with partial information from sensors, enabling a blind pursuer to guarantee capture of an evader under certain initial delays.

Contribution

It introduces an algorithm that computes the maximum initial delay for guaranteed capture and determines the optimal pursuit policy in a sensor-instrumented network.

Findings

Algorithm guarantees capture if initial delay is within computed bounds.

Optimal pursuit policy derived for sensor-equipped road networks.

Provides a method for planning pursuit with partial information.

Abstract

The optimal control of a "blind" pursuer searching for an evader moving on a road network and heading at a known speed toward a set of goal vertices is considered. To aid the "blind" pursuer, certain roads in the network have been instrumented with Unattended Ground Sensors (UGSs) that detect the evader's passage. When the pursuer arrives at an instrumented node, the UGS therein informs the pursuer if and when the evader visited the node. The pursuer's motion is not restricted to the road network. In addition, the pursuer can choose to wait/loiter for an arbitrary time at any UGS location/node. At time 0, the evader passes by an entry node on his way towards one of the exit nodes. The pursuer also arrives at this entry node after some delay and is thus informed about the presence of the intruder/evader in the network, whereupon the chase is on - the pursuer is tasked with capturing the evader. Because the pursuer is "blind", capture entails the pursuer and evader being collocated at an UGS location. If this happens, the UGS is triggered and this information is instantaneously relayed to the pursuer, thereby enabling capture. On the other hand, if the evader reaches one of the exit nodes without being captured, he is deemed to have escaped. We provide an algorithm that computes the maximum initial delay at the entry node for which capture is guaranteed. The algorithm also returns the corresponding optimal pursuit policy.