IEEE Robotics & Automation Magazine - March 2012 - 26

Figure 1. Robovolc operating on Mt. Etna, Italy, Europe's largest active
volcano. (Photo courtesy of University of Catania.)

identifies sensor types and technologies commonly
employed to measure environmentally relevant variables
and integrated sensor network systems already proved in
the field. It also discusses the broad emerging research
trends for achieving large-scale environmental monitoring
as well as some outstanding challenges in making environmental robotics pervasive.

Figure 2. The Nereus hybrid ROV that has explored the world's
deepest oceans at 10,903 m [4]. [Photo courtesy of Advanced
Imaging and Visualization Laboratory, Woods Hole
Oceanographic Institution (WHOI).]

IEEE ROBOTICS & AUTOMATION MAGAZINE

MARCH 2012

Environmental Sensing
One of the key goals in environmental science and ecology
is to gain baselines, detect changes, and correlate these to
various driving factors. The issues in detecting the changes
in ecosystems are considered by Carpenter and Brock [7].
They show that increased variability should occur prior to
threshold transitions in many ecosystems. However, they
identify that the challenge of deriving the true variability of
ecosystems is the essential long-term, high-frequency
observations.
Furthermore, ecology is one of the most statistically orientated sciences, requiring elaborate experimental design
and sampling protocols. Gaines and Denny [8] evaluate
the issues associated with misrepresentation and use of statistics, highlighting the importance of not only data capture but also the sampling regime.
Traditionally, data were obtained manually, limiting
the spatial and temporal coverage of the study sites as well
as being dictated by weather and cost. Ballester€os-Gomez
et al. [9] provide an overview of the traditional methods of
environmental monitoring, including sensors, calibration,
and field applicability. They recognize that environmental
sensor networks (ESNs) (i.e., a wireless network of sensors
distributed throughout the environment) are revolutionizing the observation of various processes and identify the
importance of these networks and robotic systems in
obtaining high-fidelity time-series data. However, problems with interoperability, calibration, communication,
and longevity are limiting their uptake in ecosystem sciences. Solutions to these issues are also a key requirement to
realize pervasive environmental robots.
Sensors
A key attribute of environmental monitoring is the
measurement of relevant environmental variables, being
physical, chemical or biological. Most physical variables,
such as temperature, pressure, and light intensity, can be
easily measured with portable off-the-shelf sensors. On the
other hand, standard measurements of environmental
chemical variables are mostly performed using bulky and
heavy analytical instrumentation installed in fixed stations.
The development of inexpensive, low-power consumption and small sensing devices, based in reasonably stable
electrochemical cells, metal oxide gas sensors (MOX), or
chemiluminescent devices is seen as a major step to the
development of chemical sensing systems able to be integrated in robots for environmental monitoring. However,
a large set of contaminants of interest (e.g., metals, radioisotopes, and biological contaminants) are present in small
concentrations in natural environments that no sensor
with enough sensitivity, selectivity, and long-term stability
currently exist.
For a deeper treatment about environmental sensors,
we direct the reader toward a multitude of articles dealing
only with this subject. For example, overviews of sensors
and requirements for general environmental monitoring

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - March 2012