Article
An Information-Motivated Exploration Agent to Locate Stationary
Persons with Wireless Transmitters in Unknown Environments
Daniel Barry * , Andreas Willig and Graeme Woodward
Citation: Barry, D.; Willig, A.;
Woodward, G. An Information-
Motivated Exploration Agent to
Locate Stationary Persons with
Wireless Transmitters in Unknown
Environments. Sensors 2021, 21, 7695.
https://doi.org/10.3390/s21227695
Academic Editors: George
Nikolakopoulos, Pablo
Rodríguez-Gonzálvez and Diego
González-Aguilera
Received: 4 October 2021
Accepted: 15 November 2021
Published: 19 November 2021
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4.0/).
Computer Science and Software Engineering, University of Canterbury, Christchurch 8020, New Zealand;
andreas.willig@canterbury.ac.nz (A.W.); graeme.woodward@canterbury.ac.nz (G.W.)
* Correspondence: dan.barry@pg.canterbury.ac.nz; Tel.: +64-3-369-4999
Abstract:
Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently
were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider
the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown
environment, where the goal is to locate all transmitters in as short a time as possible. Existing
solutions in the UAV search space typically search for a single target, assume a simple environment,
assume target properties are known or have other unrealistic assumptions. We simulate large,
complex environments with limited a priori information about the environment and transmitter
properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that
maximizes predicted information gain at each search step, incorporating information from multiple
sensors whilst making minimal assumptions about the scenario. This search method is inspired
by the information theory concept of empowerment. Our algorithm shows significant speed-up
compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times
faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use
of received transmitter signals from unknown sources and incorporate both an exploration and
search strategy.
Keywords: search and rescue; wireless transmitters; UAV; drone
1. Introduction
In the last few years, unmanned Aerial Vehicles (UAVs) spurred substantial interest,
as they can improve the delivery of existing services or enable provision of new services
in a wide range of fields, including logistics [
1
], search and rescue (SAR) [
2
–
4
] public
safety communications [
5
,
6
], infrastructure monitoring [
7
], precision agriculture [
8
,
9
],
forestry [10,11], and telecommunications [12,13].
In this paper, we explore the use of UAVs in SAR scenarios in an unknown and pos-
sibly large terrain, with the intention of reducing time for locating victims. In particular,
we consider a case where an individual UAV has to search for an unknown number of
stationary persons in an outdoor area. We assume that the UAV is equipped with appropri-
ate sensors to detect persons, e.g., based on a downward-facing camera using visible light
or infrared. These sensors allow the UAV to decide the presence or absence of a person
only in a relatively small area determined by the visual angle of the camera and the flying
height of the UAV. With such a camera alone, to maximize the certainty that all persons will
be located, the UAV would have to pick a path that is “dense”, i.e., which guarantees that
each point is observed at least once through the camera
(e.g., a ’lawnmower’ path).
Such a
dense path may require substantial time to travel. A key assumption in our work is that
each person carries a wireless transmitter which emits signals frequently. The transmitter
could, for example, belong to a cellphone, it could be a WiFi transmitter or an emergency
beacon. We do not assume that the searching UAV has any a priori knowledge about the
specific wireless technologies that any person may be using or channel properties, we only
assume that the UAV is able to detect transmissions in a given frequency range, without
Sensors 2021, 21, 7695. https://doi.org/10.3390/s21227695 https://www.mdpi.com/journal/sensors
