Pursuer Assignment and Control Strategies in Multi-Agent Pursuit-Evasion Under Uncertainties.

Leiming Zhang,Subhrajit Bhattacharya,Amanda Prorok

doi:10.3389/frobt.2021.691637

Leiming Zhang, Subhrajit Bhattacharya + Show 1 more

Open Access

https://doi.org/10.3389/frobt.2021.691637

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Abstract

We consider a pursuit-evasion problem with a heterogeneous team of multiple pursuers and multiple evaders. Although both the pursuers and the evaders are aware of each others’ control and assignment strategies, they do not have exact information about the other type of agents’ location or action. Using only noisy on-board sensors the pursuers (or evaders) make probabilistic estimation of positions of the evaders (or pursuers). Each type of agent use Markov localization to update the probability distribution of the other type. A search-based control strategy is developed for the pursuers that intrinsically takes the probability distribution of the evaders into account. Pursuers are assigned using an assignment algorithm that takes redundancy (i.e., an excess in the number of pursuers than the number of evaders) into account, such that the total or maximum estimated time to capture the evaders is minimized. In this respect we assume the pursuers to have clear advantage over the evaders. However, the objective of this work is to use assignment strategies that minimize the capture time. This assignment strategy is based on a modified Hungarian algorithm as well as a novel algorithm for determining assignment of redundant pursuers. The evaders, in order to effectively avoid the pursuers, predict the assignment based on their probabilistic knowledge of the pursuers and use a control strategy to actively move away from those pursues. Our experimental evaluation shows that the redundant assignment algorithm performs better than an alternative nearest-neighbor based assignment algorithm1.

Highlights

1.1 MotivationPursuit-evasion is an important problem in robotics with a wide range of applications including environmental monitoring and surveillance
Assuming a known pursuer-to-evader assignment, we describe the control strategies used by the evaders to avoid being captured and the control strategy used by the pursuers to capture the evaders
We considered a pursuit-evasion problem with multiple pursuers, and multiple evaders under uncertainties

Summary

Introduction

1.1 MotivationPursuit-evasion is an important problem in robotics with a wide range of applications including environmental monitoring and surveillance. Very often evaders are adversarial agents whose exact locations or actions are not known and can at best be modeled stochastically. Even when the pursuers are more capable and more numerous than the evaders, capture time may be highly unpredictable in such probabilistic settings. This paper address the problem of assignment of pursuers to evaders and control of pursuers under such stochastic settings in order to minimize the expected time to capture. We consider a multi-agent pursuit-evasion problem where, in a known environment, we have several surveillance robots (the pursuers) for monitoring a workspace for potential intruders (the evaders). We assume that the signals emitted by each evader are distinct and is different from any type of signal that the pursuers might be emitting. Each pursuer emits a distinct weak and noisy signal that the evaders can detect to localize the pursuers. The environment (obstacle map) is assumed to be known to either type of agents

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