Robotics for Environmental Monitoring [From the Guest Editors]

R obotic systems are increasingly being utilized as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. In the past, their use in environmental sciences has been relatively subtle and not highly publicized, but recent disruptive events (such as the 2010 eruption of Eyjafjallaj€okull in Iceland, the massive oil spill in the Gulf of Mexico from the Deepwater Horizon platform, and the tragic 2011 earthquake and tsunami in Japan) have reinforced and highlighted the importance and ability of robotic systems to efficiently and precisely measure and potentially reduce environmental events at scales that were never thought to be possible before. With ever-increasing public awareness of robots being able to collect scientifically relevant information and interact with the environment, new opportunities are arising for largescale environmental monitoring that are expected to push the frontiers of robotic and natural sciences. One obvious advantage of utilizing robotics in environmental sciences is that they allow the monitoring and sampling of events that are too dangerous, or impossible, for humans to undertake. Having the ability to measure these previously unmeasurable events poses the question of determining what exactly we are trying to measure and how can this be achieved given operating and environmental constraints. Then, with this ability to collect scientifically relevant measurements at unprecedented spatial and temporal scales, how do we efficiently process potentially enormous volumes of data and turn it into useful information. Following the announcement of this special issue on robotics for environmental monitoring, we attracted a large number of impressive submissions from institutions around the world. These articles considered robotic systems and sciences applied to a diverse range of environmental monitoring applications within the marine, terrestrial, and aerial domains. Unfortunately, space limitations prohibit the presentation of all the articles in this issue. However, some will appear in the subsequent regular issues of the magazine as they are substantive pieces of work and illustrate unique applications and advances in robotics in this area. This special issue contains a collection of six articles that illustrate the breadth of research activities, applications, and challenges within the environmental robotics research landscape and offers an interesting resonance with those opportunities and the above-mentioned problems. The first article by Dunbabin and Marques, “Robotics for Environmental Monitoring,” collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring over the past two decades. It also discusses the emerging research trends for achieving large-scale environmental monitoring such as cooperative robotic teams, robot and sensor network interaction, adaptive sampling, and model-aided path planning. The obvious benefit of field robotic systems is to remove scientists from immediate danger. Muscato et al., in their article “Volcanic Environments,” discuss their long history of experiences in the development and application of terrestrial robotic systems for monitoring active volcanoes. They highlight the system requirements and challenges for collecting scientifically relevant information in these hostile environments. With this capability of measuring volcanic processes in situ, volcanologists are now empowered to better understand and investigate the precursors to volcanic eruptions, which will allow for a more precise prediction of the activity. The next article, “Autonomous Gas-Sensitive Microdrone” by Neumann et al. provides an interesting example of new techniques for sampling environmental processes. It investigates the combination of navigation and chemical sensors to estimate environmental parameters such as wind speed and direction. It then examines different sampling approaches to