Abstract
The problem is a two-dimensional area-restricted search for a target using a coordinated team of autonomous mobile sensing platforms (agents). Sensing is characterised by a range-dependent probability of detection, with a non-zero probability of false alarms. The context is underwater surveillance using a swarm of amphibious drones equipped with active sonars. The paper develops an intermittent information-driven search strategy, which alternates between two phases: the fast and non-receptive displacement phase (called the ballistic phase) with a slow displacement and sensing phase (called the diffusive phase). The proposed multi-agent search strategy is carried out in a decentralised manner, which means that all computations (estimation and motion control) are done locally. Coordination of agents is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology.
Highlights
Searching strategies for finding targets using appropriate sensing modalities are of great importance in many aspects of life, from national security [1,2], rescue and recovery missions [3,4], to biological applications [5,6,7]
By studying the GPS data of albatrosses, it was discovered that search patterns of these birds consist of the segments whose lengths are random draws from the Pareto–Lévy distribution [6]
We propose a fully decentralised intermittent information-driven search by a coordinated team of autonomous agents
Summary
Searching strategies for finding targets using appropriate sensing modalities are of great importance in many aspects of life, from national security [1,2], rescue and recovery missions [3,4], to biological applications [5,6,7]. By studying the GPS data of albatrosses, it was discovered that search patterns of these birds consist of the segments whose lengths are random draws from the Pareto–Lévy distribution [6] This discovery led to several papers demonstrating that the so-called Lévy walks/flight are the optimal search strategy for foraging animals (deer, bees, etc), resulting in fractal geometries of search paths. Bénichou et al studied intermittent search without taking into account the information gathered by sensing during the search, so the searcher could revisit a same location multiple times; this leads to apparent redundancy in the search process. To overcome this shortcoming, Vergassola et al [16]. The only requirement for avoiding the break-up of the multi-agent formation is that the graph of its communication network, during the search, is connected at all times
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