A self deployed multi-channel wireless communications system for subterranean robots

A Self-Deployed Multi-Channel Wireless
Communications System for Subterranean Robots
Frank Mascarich
Autonomous Robots Lab
University of Nevada, Reno
fmascarich@nevada.unr.edu
Huan Nguyen
huann@nevada.unr.edu
Tung Dang
tung.dang@nevada.unr.edu
Shehryar Khattak
shehryar@nevada.unr.edu
Christos Papachristos
cpapachristos@unr.edu
Kostas Alexis
kalexis@unr.edu
Abstract—In this paper we present an experimental results-
driven system design to enable more robust and self-deployed
wireless communications for robotic systems autonomously op-
erating in underground environments such as mines, caves,
and tunnels. Subterranean environments pose severe chal-
lenges for wireless communications as wireless signal suffers
extra power loss due to tunnel’s curvatures; the existence of
corners, junctions and large obstacles inside the mines; the
changes in cross section of a passage and the tilt of sidewalls.
This is especially the case when high-bandwidth and low-power
wireless communications are considered as commonly found in
autonomous robots. In response to these challenges, we present
a multi-modal communication solution that a) relies on the
integration of both dual 5.8GHz WiFi radios (high bandwidth
channel), as well as 915MHz telemetry modules (low bandwidth
channel), while at the same time b) utilizes both high-gain
directional antennas outside of the underground environment
and communication “breadcrumbs” within the subterranean
setting. The communication breadcrumbs correspond to a
highly integrated, lightweight and self-contained solution of dual
radio WiFi and small patch 6dBi antennas, a 915MHz ultra
low-power module with a 3dBi wire antenna, alongside battery
for approximately 2 hours of operation. Finally, we present
an integrated robotic solution – the “Aerial Scouts”- that are
not only capable of autonomously exploring in the underground
domain but also ferrying and dropping the aforementioned
communication breadcrumbs on their own – thus autonomously
extending their network as they go. For evaluation purposes
we present experimental results from underground exploration
missions where we relate the location of the robot, the self-
deployed communications network and the measured received
signal strength indicator (RSSI) over several points of the 3D
reconstructed map of the environment.
TABLE OF CONTENTS
1. INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
2. RELATED WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
3. SYSTEM DESIGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
4. EXPERIMENTAL EVALUATION . . . . . . . . . . . . . . . . . . . . . .5
5. CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
BIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
1. INTRODUCTION
Underground environments such as mines, caves, and tun-
nels constitute valuable deployment domain for autonomous
978-1-7281-2734-7/20/$31.00 c

2020 IEEE
Figure 1. Instance of an subterranean aerial robotic
deployment utilizing the dual channel wireless
communication system.
robotic systems. These settings contain serious hazards to
human workers. The collapse of mines and tunnels, fires,
rock falls, the concentration of dangerous gasses, and flood-
ing all pose significant risk to human life. Autonomous robots
have previously been successfully deployed for many real-
world tasks, such as industrial inspection [1, 2], infrastructure
surveying [3, 4], exploration and mapping [5, 6], search and
rescue operations [7, 8] and disaster response [9–11], and
hence can be utilized to mitigate the risks in many common
underground tasks as well. However, subterranean envi-
ronments pose several significant challenges to autonomous
robotic operations [12]. Dark, muddy, dusty, and complex,
confined geometry create hazards to perception, mapping,
and autonomy. The ability to monitor and command these
systems is greatly hampered by the challenges of wireless
communication in such environments. The constrained, com-
plex geometry causes often unpredictable radio frequency
effects. Furthermore, the highly variable density and radio
frequency absorption properties of earthen materials also
causes hard to model radio frequency propagation in such
settings. These radio frequency effects greatly influence the
ability of robotic systems to communicate with each other and
with their human supervisors.
Many relevant applications preclude the use of any already-
installed communication infrastructure. For example, a mine
fire may destroy any such wireless communication network
used during normal mine operations. Additionally, deploy-
ments in tunnels and caves without any communication in-
1
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frastructure also represent valuable robotic scenarios. There-
fore, robotic systems engaged in these environments must
have the ability to deploy their own communication systems
during operation. In the case of aerial robots, burdened
by payload and endurance considerations, this implies the
development of lightweight independent modules capable of
being dropped from the aerial platform.
Motivated by these challenges, this paper presents a dual
channel communication system for robotic communication
providing a high-bandwidth but short range, 5.8GHz WiFi
mesh network for information-dense messages such as im-
ages and point clouds alongside a low-bandwidth, but long
range 915MHz mesh network for short messages such as
odometry, high-level autonomy commands from human oper-
ators, and the detection of objects of interest. The system con-
sists of two unique, deployable communication breadcrumbs,
each comprised of a radio module, battery and necessary
electronic components alongside a mechanical design allow-
ing the modules to be deployed from both aerial and ground
robots. Specifically, this paper details the system design of
the two communication breadcrumb modules as well as the
aerial robotic systems responsible for deploying the afore-
mentioned modules, called the ”Aerial Scouts”. Additionally,
this paper presents an experimental evaluation of the modules
in a deployment scenario within a mine.
The remainder of the paper is organized as follows: Section 2
overviews the related work. Section 3 details both the radio
communication modules and the aerial scouts, followed by an
experimental evaluation of the presented system by robotic
field deployments in an underground mine in Section 4.
Finally, conclusions are drawn in Section 5.
2. RELATED WORK
Wireless communication technologies has been deployed in
underground mines since before the early 2000’s for human-
human, human-machine and machine-machine communica-
tion [13]. Since then, researchers have thoroughly inves-
tigated characteristics of wireless communication in under-
ground settings. [14] shows that large scale fading, the
variation of received signal strength over large distance, in
underground environments follows Lognormal distribution,
however the path loss exponent is higher than within indoor
environments [15]. This can be explained by the fact that
multipath signals induced by irregular, rough walls con-
tribute negatively to the total signal power. Additionally,
UHF signals suffer extra power losses due to tunnel’s cur-
vatures [16], corners and junctions inside the mines [17],
changes in the cross-section of a passage [18], the tilt angle of
sidewall [19] and the existence of large vehicles or obstacles
in the mines [20].
Driven by the fact that high frequency signals can offer better
coverage in straight and line-of-sight (LOS) tunnel while
signals with lower frequencies may have better coverage
when there are obstacles, corners or junctions [13], as well
as the fact that lower frequencies propagate much farther
given equal output power, in this work, we develop a dual-
channel communication system: independent 5.8GHz Wifi
and 915MHz mesh networks. The choice of the 5.8GHz WiFi
band over the 2.4GHz band is driven not only by the fact that
it is capable of higher bandwidths but also because 5.8GHz
shows lower pathloss exponent compare to 2.4GHz in non
light-of-sight situations [21]. Also, as suggested in [17], both
channels use directional antennas at the ground station, as
depicted in Figure 2, aligning the antennae with the axis of the
tunnel to maximize the component of the transmitted power
along the tunnel axis. However, unlike [17], which uses 90-
degree reflectors to compensate for the drop in RSSI around
corners, the Aerial Scout platform described in Section 3,
drops breadcrumb repeaters which extend the range of their
respective networks.
3. SYSTEM DESIGN
Radio frequency communication in subterranean settings
must tackle several significant challenges. As described in
Section 2, complex, confined geometries cause erratic and un-
reliable reflections and interference across many frequencies.
Nonetheless, the requirements of many robotic deployment
scenarios in subterranean environments require periodic, if
not constant communication with other robots and potentially
their human operators.
The types of messages distributed amongst such robot-human
teams can be bifurcated into two categories: high-bandwidth
messages contain several megabytes of data per message, and
low-bandwidth messages contain several bytes to hundreds
of bytes of data in each message. High-bandwidth messages
include image and point cloud data for the purposes of map-
sharing, co-localization of robotic collaborators, and critical
supervision by human operators. Such messages may vary
their transmission rate at the cost of precision and complete-
ness.
Low-bandwidth messages include relatively short messages
such as odometry and pose information measuring in the
range of hundreds of bytes as well as even shorter messages
such as high-level autonomy commands from a human or
robotic supervisor which may be as short as a single byte or
less. These low-bandwidth communications also represent
emergency or other mission-critical messages which must be
transmitted to the robot quickly and with guaranteed delivery.
High-bandwidth messages, on the other hand, may be loss
tolerant. For example, images and map data transmitted back
to a human operator do not necessarily have to be delivered
at the full frame rate of the camera, sensor or algorithm.
Communication Architecture
Both the division of message size into high-bandwidth and
low-bandwidth and the relative reliability requirements of
the two message types lend to the design of a dual-channel
communication architecture. In this work, a high-bandwidth
5.8Ghz WiFi mesh network is deployed along side a low-
bandwidth 915MHz DigiMesh network. Mesh networks pro-
vide the delivery of packets of information across a dynamic
set of nodes. Nodes exchange messages and re-organize
the network using a wide variety of meshing algorithms,
whose operation is not the focus of this work. In this paper,
both networks are capable of dynamically reorganizing their
networks when new nodes are added or removed from the
network, or when nodes are moved within the network such
that the path over which messages must travel between two
clients changes. Figure 3 depicts the network architecture,
while Table 1 shows the employed division of messages
between the two communication channels.
High-Bandwidth Communication Module Design
The high-bandwidth communication module employs an
ACKSYS EmbedAir1000, which consists of an 89mm x
51mm x 28mm, 45 gram dual-radio module, small 3dBi patch
2

Table 1. Message Description
High-Bandwidth Messages
Message Type Description Size(Typ.) Rate
Images 640x480 Mono 1MB 5Hz
Object Detection Images 640x480 Color 3MB <1Hz
Maps Updates only 1MB 2Hz
Low-Bandwidth Messages
Message Type Description Size(Typ.) Rate
Pose Position & Orientation <200B 10Hz
Object Detections Object Type String & Position < 200B < 1Hz
High-Level Autonomy Commands
Take-Off - 1B <1Hz
Land - 1B <1Hz
Drop Payload Drops Comms Module 1B <1Hz
Start Exploration Starts Autonomy 1B <1Hz
Stop Exploration Stops Autonomy 1B <1Hz
Return to Home - 1B <1Hz
Go To Position Position & Orientation <100B <1Hz
Figure 2. Image depicting ground station antennae
configuration. The two square antennae on the left side of
the image are the 5.8Ghz antennae connected to the
ACKSYS EmbedAir1000 module. The upper antenna
carries the traffic of the mesh network radio, while the lower
antenna broadcasts an access point for Aerial Scouts to
connect to the ground station when in proximity. The other,
triangular shaped antenna is the low frequency antenna for
the low-bandwidth mesh network.
antennas and a 2000 mAh single cell battery. The first radio,
supporting IEEE 802.11AC, is used to form the mesh network
and connect to other high-bandwidth nodes within range. The
second radio, supporting IEEE 802.11n broadcasts a stan-
dard 5.8GHz WiFi access point, to which clients, including
human operators and the robots in the network, connect.
The utilization of dual radio modules greatly improves the
capacity of the network as the two radios can transmit or
receive simultaneously. In ideal laboratory conditions, the
mesh network was found to be capable of 164 Mbps across
two nodes, between two clients connected to each node’s
access point. Furthermore, the addition of more nodes to the
mesh network did not significantly effect the overall network
throughput. At the base station, to maximize the initial range
of the network, a high-gain, directional antenna is directed at
the entrance of the underground environment.
Figure 3. Network diagram depicting the dual channel
network architecture.
The utilization of standard WiFi access point provides many
benefits to the communication system. First, no additional
radio components are required to be carried on board the
robot, the Aerial Scout, which is detailed in subsection 3,
as well as the vast majority of modern robotic systems are
capable of communicating over standard WiFi networks.
Second, the utilization of standard WiFi networking allows
for the utilization of other standard networking protocols
and systems. In the presented field deployments, the Aerial
Scouts utilize the ROS framework [22] to send and receive
messages both internally, between various software systems
for command, perception, and control, as well as externally
with other Aerial Scouts and human operators. To simplify
the communication network across disparate systems, the
Nimbro Network package [23] was employed for explicit
control over the transmission of messages and their respective
bandwidth consumption. The Nimbro Network package also
allows multiple ROS masters to run independently, permitting
the operation of multiple robots with few minor modifications
to their respective network configurations.
Low-Bandwidth Communication Module Design
The low-bandwidth communication module employs a Digi
XBee-PRO 900HP 915MHz radio module which supports
the proprietary DigiMesh mesh networking topology. The
DigiMesh topology is a wireless mesh which features de-
centralized network organization, homogeneous node types,
dynamic routing, self-healing mesh properties, and message
re-transmission protocols. At the base-station, a high-gain,
directional antenna is utilized to maximize the initial range
3

Figure 4. Image depicting the high-bandwidth breadcrumb
module connected to a servo-less payload release
mechanism.
Figure 5. Images depicting the low-bandwidth mesh
breadcrumb. The image on the left shows the breadcrumb
module in its state while in flight, connected to the servo-less
payload release mechanism. The image on the right shows
the breadcrumb module in its released state, with its arms
deployed as a self-righting mechanism.
of the low-bandwidth network. On board each robot, a small
XBee-PRO module is mounted utilizing a short, 3dBi whip
antenna, and communicates over a USB-Serial interface with
the Aerial Scout’s high-level processor.
The low-bandwidth breadcrumb module utilizes the same
XBee-PRO module, and is mounted within a custom designed
mechanism depicted in Figure 5. The module is equipped
with spring-loaded arms to ensure the module lands right-
side-up. The arms are folded together, loading the springs
when the modules are mounted onto the Aerial Scout’s
deployment mechanism. When released during flight, the
spring mechanism opens, preventing the module from landing
upside-down. Both laboratory and field tests indicated that
the bandwidth and range performance of the module was
greatly affected by the final orientation of the radio’s antenna
with respect to the ground.
Figure 6. Diagram depicting the Aerial Scout’s sensing and
compute system.
The module weighs only 34 grams when utilizing a 1000mAh
battery permitting more than 2 hours of operation under
heavy communication load. The module is capable of uti-
lizing larger batteries, permitting longer operation at the cost
of additional payload. During laboratory testing, the low-
bandwidth communications network achieved bidirectional
throughput rates of 21 Kbps, with several hundred meters
between nodes. This throughput exceeded the requirements
of the low-bandwidth channel messages. In field testing,
including the experiment described in Section 4, the range of
the module was found to be greatly reduced in subterranean
environments, reaching a maximum of 212 meters, along
a nearly straight line-of-sight path. Similar to the high-
bandwidth network, the inclusion of additional nodes did not
affect total network throughput.
Aerial Scouts
Figure 6 depicts the Aerial Scout platform deployed during
the experiments. The Aerial platform is based on a DJI
Matrice M100 quadrotor. The robot utilizes a 64-beam
Ouster OS1 3D LiDAR capable of providing pointclouds at
10Hz upto 100m in range with-in a horizontal and vertical
field-of-view 360◦
and 33.2◦
,respectively for localization and
mapping purposes [24]. The odometry estimates is then fused
with inertial measurements from the autopilot of the robot to
provide higher pose update rate, which is utilized by a Model
Predictive Controller [25] to guide the robot along paths gen-
erated by the exploration planner. The localization system is
further enhanced with visual-thermal-inertial odometry [26–
28], using a loosely-coupled filtering approach [29] to im-
prove its robustness. For this purpose, a FLIR Tau 2 thermal
camera mounted on the robot provides thermal images of
640×512 resolution at 30Hz. A FLIR BlackFly visible light
camera, with shutter–synchronized LEDs, provided visual
images of 640 × 512 resolution at 20Hz and a VectorNav
VN–100 IMU provideed inertial measurements at an update
rate of 200Hz. All of the aforementioned components of lo-
calization, mapping, control, and path planning are executed
in real-time and on-board the robot using an Intel NUC-i7
(NUC7i7BNH) computer.
4

Figure 7. This figure depicts the results of the evaluation of the dual channel communications system at the Comstock Mine
in Virginia City, Nevada. In each of the maps, point clouds are colored by the RSSI value of the respective communications
channel where green indicates the greatest RSSI, and red indicates the weakest RSSI. The left-most map depicts the relative
RSSI of the WiFi channel through out the mine in the first flight which took place without any WiFi breadcrumbs placed
within the mine. It should be noted that the transition from green to red in the middle of the mine indicates where the WiFi
signal was lost. The second map from the left shows the RSSI value of the WiFi channel in the second flight after a WiFi
breadcrumb was placed at the position indicated by the label ’A’. It should be noted that the robot only lost communication
briefly within the drift adjacent to the placement of the WiFi breadcrumb. The third image from the left indicates the RSSI
value of the low-bandwidth communications network during the first flight, where the fourth image from the left depicts the
RSSI value of the low-bandwidth communications network in the second flight. It should be noted that in both flights, the
low-bandwidth communications network maintained a connection to the Aerial Scout throughout the mission other than a
brief period of less than four seconds withing the third drift. The fourth image from the left also depicts the location of the
low-bandwidth breadcrumb placed at the position indicated by the label ’B’.
4. EXPERIMENTAL EVALUATION
To evaluate the proposed communication network, the system
is evaluated in a field deployment at the Comstock Mine,
located in Virginia City, Nevada. This mine is an exploratory
portal mine consisting of a main drift extending roughly
165m from the portal and several short drifts extending off
the right side of the main drift, ranging in length from 12 to
47 meters. The experiment consists of two flights, the first of
which utilizes only radios at the ground station, and onboard
the robot, and the second of which includes both wireless
breadcrumbs deployed within the mine. Figure 7 depicts
colorized point clouds from the experiment in which points
are colored with respect to nearest measured RSSI value of
both the high-bandwidth and low-bandwidth communication
networks.
The first flight demonstrates that the maximum range of
the low-bandwidth communication channel greatly exceeds
that of the high-bandwidth communication channel, covering
nearly the entirety of the mine without any breadcrumb
modules. It should be noted that in this particular hard-
rock mine, the lower frequency of the low-bandwidth com-
munication channel is capable of reflecting around the turns
and corners of the mine much better than the high-frequency,
5

high-bandwidth communication network.
The second flight demonstrates the extension of the high-
bandwidth communication network when a breadcrumb mod-
ule is deployed. Due to the reduced performance of the
module when located on the ground, as opposed to in flight,
the module was deployed within the maximum range of the
base station’s high-bandwidth antenna. The short strip of red
immediately below the position of the deployed node shows
the transition period as the robot’s onboard WiFi connection
switched between the access point provided by the base
station and the access point of the breadcrumb module.
5. CONCLUSIONS
In this work a pair of self-deployable networking modules
was presented enabling robust and reliable communication
between autonomous robotic systems and human operators in
subterranean settings. A bifurcation of the relevant network
data was presented which encourages the deployment of a
dual channel system, one channel affording high-bandwidth
for information-dense messages, and another channel guar-
anteeing delivery of short, mission critical messages. The
work presented the overall communication architecture, the
mechanical and electrical design of the two breadcrumb
modules, as well as the Aerial Scout platform which en-
ables deployment of the breadcrumb modules at the edges
of the communication network. Finally, a field deployment
inside an underground mine was presented to demonstrate the
robustness and limitations of the described communications
system.
Further development of this work includes thorough evalua-
tion of the modules in a number of subterranean settings char-
acterized by unique geometries and material properties. Such
an evaluation should consider the various effects concrete,
hard and soft rock on various communication frequencies.
Further mechanical design improvements may reduce the
weight of the breadcrumb modules, enabling the Aerial Scout
platform to ferry additional modules, further extending its
range and capabilities.
ACKNOWLEDGMENTS
This material is based upon work supported by the Defense
Advanced Research Projects Agency (DARPA) under Agree-
ment No. HR00111820045. The presented content and ideas
are solely those of the authors.
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[27] S. Khattak, F. Mascarich, T. Dang, C. Papachristos,
and K. Alexis, “Robust thermal-inertial localization for
aerial robots: A case for direct methods,” in 2019 In-
ternational Conference on Unmanned Aircraft Systems
(ICUAS). IEEE, 2019, pp. 1061–1068.
[28] S. Khattak, C. Papachristos, and K. Alexis, “Visual-
thermal landmarks and inertial fusion for naviga-
tion in degraded visual environments,” in 2019 IEEE
Aerospace Conference. IEEE, 2019, pp. 1–9.
[29] S. Lynen, M. W. Achtelik, S. Weiss, M. Chli, and
R. Siegwart, “A robust and modular multi-sensor fusion
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BIOGRAPHY[
Frank Mascarich earned his B.S.
in Computer Science and Engineering
from the University of Nevada, Reno in
2016 with a focus in embedded systems,
and his Master’s in Computer Science
and Engineering from the University of
Nevada, Reno in 2018. Frank is cur-
rently an PhD student and Graduate Re-
search Assistant with the Autonomous
Robots Lab at the University of Nevada,
Reno. His research focuses on perception and navigation
in degraded visual environments and developing robots and
sensory systems for dirty, dull and dangerous applications.
Huan Nguyen received his B.S. and
M.S. degrees in Electrical Engineering
from Ho Chi Minh University of Tech-
nology in 2016 and 2018 respectively.
He is currently a PhD student in Au-
tonomous Robots Lab at the University
of Nevada, Reno. His research interests
are in the areas of control, motion plan-
ning and path planning for autonomous
mobile robots.
Tung Dang received his B.S. and M.S.
degrees in Electrical Engineering from
Ho Chi Minh City University of Tech-
nology in 2013 and 2015 respectively.
He is currently working towards his PhD
with Autonomous Robots Lab at the Uni-
versity of Nevada, Reno. His research
interests are in the areas of active per-
ception, path planning and control for
autonomous mobile robots.
Shehryar Khattak earned his B.S. in
Mechanical Engineering from Ghulam
Ishaq Khan Institute of Engineering Sci-
ences and Technology, Pakistan in 2009
and M.S. in Aerospace Engineering from
Korea Advanced Institute of Science and
Technology, Daejeon in 2012. From Au-
gust 2012 to December 2015, he worked
as a Research Engineer at Samsung
Electronics in Suwon, South Korea. Cur-
rently, Shehryar is pursuing his Ph.D. in Computer Science
and Engineering from the University of Nevada, Reno. His
current research is related to robot perception and path plan-
ning with focus on development of localization and mapping
algorithms exploiting multi-sensor information.
Christos Papachristos is an Assistant
Professor at the Computer Science En-
gineering Department of the University
of Nevada, Reno. Previously, he held the
position of Research Assistant Professor
at the University of Nevada, Reno in
affiliation with the Autonomous Robots
Lab, where he focused his robotics
research on enabling operational re-
silience and autonomous exploration,
consistent high-fidelity mapping, and characterization of
complex GPS-denied degraded visual environments including
7

underground mines and tunnels. Dr. Papachristos obtained
his Ph.D. in aerial robotics at the University of Patras in
Greece. He is the author of more than 50 publications,
and has acted as co-PI or Senior Personnel in multi-million
projects in the US and the EU.
Kostas Alexis obtained his Ph.D. in
the field of aerial robotics control and
collaboration from the University of Pa-
tras, Greece in 2011. His Ph.D. re-
search was supported by the Greek
National-European Commission Excel-
lence scholarship. Being awarded a
Swiss Government fellowship he moved
to ETH Zurich. From 2011 to June
2015 he held the position of Senior Re-
searcher at the Autonomous Systems Lab, ETH Zurich. Cur-
rently, Dr. Alexis is an Assistant Professor at the University
of Nevada, Reno and director of the Autonomous Robots
Lab. His research interests lie in the fields of robotics and
autonomy with a particular emphasis in the topics of control
and planning and extensive experience in aerial robotics
including the co-development of the AtlantikSolar UAV – a
solar powered small aerial robot that demonstrated 81.5h
of continuous flight. He is the author of more than 70
publications and has received multiple best paper awards.
8

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