Abstract

We study the problem of synthesizing a controller for a robot with a surveillance objective, that is, the robot is required to maintain knowledge of the location of a moving, possibly adversarial target. We formulate this problem as a one-sided partial-information game in which the winning condition for the agent is specified as a temporal logic formula. The specification formalizes the surveillance requirement given by the user, including additional non-surveillance tasks. In order to synthesize a surveillance strategy that meets the specification, we transform the partial-information game into a perfect-information one, using abstraction to mitigate the exponential blow-up typically incurred by such transformations. This enables the use of off-the-shelf tools for reactive synthesis. We use counterexample-guided refinement to automatically achieve abstraction precision that is sufficient to synthesize a surveillance strategy. We evaluate the proposed method on two case-studies, demonstrating its applicability to large state-spaces and diverse requirements.

Highlights

  • Performing surveillance, that is, tracking the location of a target, has many applications

  • Our contributions are as follows: (1) We propose a formalization of surveillance objectives as temporal logic specifications, and frame surveillance strategy synthesis as a reactive synthesis problem in a partialinformation two player game

  • We study surveillance objectives expressed by formulas of linear temporal logic (LTL) over surveillance predicates

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Summary

INTRODUCTION

Performing surveillance, that is, tracking the location of a target, has many applications. We introduce an abstract belief set construction, which underapproximates the information-tracking abilities of the agent (or, alternatively, overapproximates its belief, i.e., the set of positions it knows the target could be in) We leverage this construction by reasoning over the agent’s belief in the target location, and this allows us to specify surveillance objectives in LTL over these belief states. While closely related to the surveillance problem we consider, pursuit-evasion games with partial information [3], [13], [14] formulate the problem as eventual detection, and do not consider combinations with other mission specifications Other work, such as [15] and [16], incorporates map building during pursuit in an unknown environment, but again solely for target detection.

Surveillance Game Structures
Belief-Set Game Structures
Temporal Surveillance Objectives
Incorporating Task Specifications
Surveillance Synthesis Problem
BELIEF SET ABSTRACTION
ABSTRACTION PRECISION
Counterexamples for Safety Surveillance Properties
Counterexamples for Liveness Surveillance Properties
Counterexample-Guided Refinement
EXPERIMENTAL EVALUATION
Discussion
CONCLUSIONS
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