Robots for Environmental Monitoring: Significant Advancements and Applications

Robotic 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. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

[1]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[2]  Karl D. von Ellenrieder,et al.  Unmanned autonomous sailing: Current status and future role in sustained ocean observations , 2009 .

[3]  A. T. Almeida,et al.  Environmental monitoring with mobile robots , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  T. Schmugge,et al.  Research Article: Using Unmanned Aerial Vehicles for Rangelands: Current Applications and Future Potentials , 2006 .

[5]  Derek A. Paley,et al.  UAV coordination on convex curves in wind: An environmental sampling application , 2009, 2009 European Control Conference (ECC).

[6]  D. Caron,et al.  Design and Development of a Wireless Robotic Networked Aquatic Microbial Observing System , 2007 .

[7]  Giovanni Muscato,et al.  An Overview of the “Volcan Project”: An UAS for Exploration of Volcanic Environments , 2009, J. Intell. Robotic Syst..

[8]  Han-Lim Choi,et al.  Coordinated Targeting of Mobile Sensor Networks for Ensemble Forecast Improvement , 2011, IEEE Sensors Journal.

[9]  Roland Siegwart,et al.  Flying solo and solar to Mars , 2006, IEEE Robotics & Automation Magazine.

[10]  Peter Arzberger,et al.  New Eyes on the World: Advanced Sensors for Ecology , 2009 .

[11]  Kirk Martinez,et al.  Environmental Sensor Networks: A revolution in the earth system science? , 2006 .

[12]  David G. Schmale,et al.  Coordinated aerobiological sampling of a plant pathogen in the lower atmosphere using two autonomous unmanned aerial vehicles , 2010, J. Field Robotics.

[13]  Scot E. Smith,et al.  Small Unmanned Aircraft Systems for Low-Altitude Aerial Surveys , 2010 .

[14]  R. Eustice,et al.  Large area 3D reconstructions from underwater surveys , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[15]  Alistair Reid,et al.  1-Point RANSAC for extended Kalman filtering: Application to real-time structure from motion and visual odometry , 2010 .

[16]  N. Sobol,et al.  Preliminary results , 2020, Asymptotic Analysis of Random Walks: Light-Tailed Distributions.

[17]  Rustam Stolkin,et al.  Optimal AUV path planning for extended missions in complex, fast-flowing estuarine environments , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[18]  Stefan B. Williams,et al.  Autonomous underwater vehicle–assisted surveying of drowned reefs on the shelf edge of the Great Barrier Reef, Australia , 2010, J. Field Robotics.

[19]  C. Guestrin,et al.  Near-optimal sensor placements: maximizing information while minimizing communication cost , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[20]  Peter I. Corke,et al.  Data muling over underwater wireless sensor networks using an autonomous underwater vehicle , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[21]  John Gould,et al.  Argo profiling floats bring new era of in situ ocean observations , 2004 .

[22]  Pierre T. Kabamba,et al.  Solar-Powered Aircraft: Energy-Optimal Path Planning and Perpetual Endurance , 2009 .

[23]  Gaurav S. Sukhatme,et al.  USC CINAPS Builds bridges : observing and monitoring the southern california bight , 2010 .

[24]  Gaurav S. Sukhatme,et al.  Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions , 2010, OCEANS'10 IEEE SYDNEY.

[25]  Peter Wadhams,et al.  A new view of the underside of Arctic sea ice , 2006 .

[26]  Yangquan Chen,et al.  AggieAir — a low-cost autonomous multispectral remote sensing platform: New developments and applications , 2009, IEEE International Geoscience and Remote Sensing Symposium.

[27]  Peter I. Corke,et al.  Environmental Wireless Sensor Networks , 2010, Proceedings of the IEEE.

[28]  S. Carpenter,et al.  Rising variance: a leading indicator of ecological transition. , 2006, Ecology letters.

[29]  Holger Klinck,et al.  AAS Endurance: An autonomous acoustic sailboat formarine mammal research , 2009 .

[30]  TsengYu-Chee,et al.  The coverage problem in a wireless sensor network , 2005 .

[31]  D. Yoerger,et al.  Thickness of a submarine lava flow determined from near‐bottom magnetic field mapping by autonomous underwater vehicle , 1998 .

[32]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[33]  P. Lin,et al.  The Eyewall-Penetration Reconnaissance Observation of Typhoon Longwang (2005) with Unmanned Aerial Vehicle, Aerosonde , 2008 .

[34]  Arko Lucieer,et al.  Using an Unmanned Aerial Vehicle (UAV) for ultra-high resolution mapping of Antarctic moss beds , 2010 .

[35]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Gaurav S. Sukhatme,et al.  Autonomous Underwater Vehicle trajectory design coupled with predictive ocean models: A case study , 2010, 2010 IEEE International Conference on Robotics and Automation.

[37]  Aníbal Ollero,et al.  Multiple eyes in the skies: architecture and perception issues in the COMETS unmanned air vehicles project , 2005, IEEE Robotics & Automation Magazine.

[38]  William Whittaker,et al.  The Atacama Desert Trek: outcomes , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[39]  Mustafa Yücel,et al.  Marine chemical technology and sensors for marine waters: potentials and limits. , 2009, Annual review of marine science.

[40]  Marcel Babin,et al.  Real-time coastal observing systems for marine ecosystem dynamics and harmful algal blooms: Theory, instrumentation and modelling , 2008 .

[41]  Pratap Tokekar,et al.  A Robotic Sensor Network for monitoring carp in Minnesota lakes , 2010, 2010 IEEE International Conference on Robotics and Automation.

[42]  Matthew Dunbabin,et al.  Go with the flow : optimal AUV path planning in coastal environments , 2009, ICRA 2009.

[43]  Gaurav S. Sukhatme,et al.  Field-tests of a redundantly actuated cable-driven robot for environmental sampling applications , 2009, 2009 IEEE International Conference on Automation Science and Engineering.

[44]  Louis L. Whitcomb,et al.  Underwater robotics: out of the research laboratory and into the field , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[45]  D. C. Webb,et al.  SLOCUM: an underwater glider propelled by environmental energy , 2001 .

[46]  David M. Fratantoni,et al.  Multi-AUV Control and Adaptive Sampling in Monterey Bay , 2006, IEEE Journal of Oceanic Engineering.

[47]  Naomi Ehrich Leonard,et al.  Cooperative Control for Ocean Sampling: The Glider Coordinated Control System , 2008, IEEE Transactions on Control Systems Technology.

[48]  David S. Wettergreen,et al.  Intelligent Maps for Autonomous Kilometer-Scale Science Survey , 2008 .

[49]  Stefan B. Williams,et al.  AUV Benthic Habitat Mapping in South Eastern Tasmania , 2009, FSR.

[50]  Naomi Ehrich Leonard,et al.  Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay , 2010, J. Field Robotics.

[51]  Oliver Zielinski,et al.  Detecting marine hazardous substances and organisms: sensors for pollutants, toxins, and pathogens , 2009 .

[52]  Aníbal Ollero,et al.  Data Retrieving From Heterogeneous Wireless Sensor Network Nodes Using UAVs , 2010, J. Intell. Robotic Syst..

[53]  Yu-Chee Tseng,et al.  The Coverage Problem in a Wireless Sensor Network , 2003, WSNA '03.

[54]  B. Fulkerson,et al.  Soil Sensor Technology: Life within a Pixel , 2007 .

[55]  Fabio Tozeto Ramos,et al.  Airborne vision‐based mapping and classification of large farmland environments , 2010, J. Field Robotics.

[56]  P. Stevenson,et al.  Towards environmental monitoring with the Autosub autonomous underwater vehicle , 1998, Proceedings of 1998 International Symposium on Underwater Technology.

[57]  Volkan Isler,et al.  Robotic data mules for collecting data over sparse sensor fields , 2011, J. Field Robotics.

[58]  D. Baldocchi,et al.  CO2 fluxes over plant canopies and solar radiation: a review , 1995 .

[59]  Salah Sukkarieh,et al.  A Rotary-wing Unmanned Air Vehicle for Aquatic Weed Surveillance and Management , 2010, J. Intell. Robotic Syst..

[60]  David Wettergreen,et al.  Dante II: Technical Description, Results, and Lessons Learned , 1999, Int. J. Robotics Res..

[61]  T. Harmon,et al.  Environmental sensor networks in ecological research. , 2009, The New phytologist.

[62]  Gaurav S. Sukhatme,et al.  Adaptive sampling for environmental robotics , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[63]  Gwyn Griffiths Glider and autonomous vehicle observing systems , 2008 .

[64]  Jay A. Farrell,et al.  Moth-inspired chemical plume tracing on an autonomous underwater vehicle , 2006, IEEE Transactions on Robotics.

[65]  Geoffrey A. Hollinger,et al.  Autonomous data collection from underwater sensor networks using acoustic communication , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[66]  Clifford K. Ho,et al.  Overview of Sensors and Needs for Environmental Monitoring , 2005, Sensors (Basel, Switzerland).

[67]  Wen Hu,et al.  Experiments in Integrating Autonomous Uninhabited Aerial Vehicles(UAVs) and Wireless Sensor Networks , 2008, ICRA 2008.

[68]  Gaurav S. Sukhatme,et al.  Adaptive Sampling for Estimating a Scalar Field using a Robotic Boat and a Sensor Network , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[69]  S. Nebiker,et al.  A Light-weight Multispectral Sensor for Micro UAV - Opportunities for Very High Resolution Airborne Remote Sensing , 2008 .

[70]  Pratap Tokekar,et al.  Active target localization for bearing based robotic telemetry , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[71]  Stefan B. Williams,et al.  Repeated AUV surveying of urchin barrens in North Eastern Tasmania , 2010, 2010 IEEE International Conference on Robotics and Automation.

[72]  G. J. Holland,et al.  The Aerosonde Robotic Aircraft: A New Paradigm for Environmental Observations , 2001 .

[73]  Gaurav S. Sukhatme,et al.  Adaptive sampling for environmental field estimation using robotic sensors , 2004, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[74]  Stefan B. Williams,et al.  Surveying noctural cuttlefish camouflage behaviour using an AUV , 2009, 2009 IEEE International Conference on Robotics and Automation.

[75]  Salah Sukkarieh,et al.  Autonomous airborne wildlife tracking using radio signal strength , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[76]  Nathan R. Evans,et al.  Optical delineation of benthic habitat using an autonomous underwater vehicle , 2007, J. Field Robotics.

[77]  Michael T. Wolf,et al.  Probabilistic motion planning of balloons in strong, uncertain wind fields , 2010, 2010 IEEE International Conference on Robotics and Automation.

[78]  Mark W. Denny,et al.  The largest, smallest, highest, lowest, longest, and shortest: extremes in ecology , 1993 .

[79]  Graham Brooker,et al.  Feasibility of UAV Based Optical Tracker for Tracking Australian Plague Locust , 2009 .

[80]  Brian M. Sadler,et al.  Fundamentals of energy-constrained sensor network systems , 2005, IEEE Aerospace and Electronic Systems Magazine.

[81]  M. Purcell,et al.  REMUS: a small, low cost AUV; system description, field trials and performance results , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[82]  Dana R. Yoerger,et al.  Navigation and control of the Nereus hybrid underwater vehicle for global ocean science to 10,903 m depth: Preliminary results , 2010, 2010 IEEE International Conference on Robotics and Automation.

[83]  Paolo Dario,et al.  The DustBot System: Using Mobile Robots to Monitor Pollution in Pedestrian Area , 2010 .

[84]  Sonia Martínez,et al.  Monitoring Environmental Boundaries With a Robotic Sensor Network , 2006, IEEE Transactions on Control Systems Technology.

[85]  Waylon Brunette,et al.  Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks , 2003, Ad Hoc Networks.

[86]  Lino Marques,et al.  Particle swarm-based olfactory guided search , 2006, Auton. Robots.

[87]  Peter I. Corke,et al.  Data collection, storage, and retrieval with an underwater sensor network , 2005, SenSys '05.

[88]  Matthew David Dunbabin,et al.  Experimental evaluation of an Autonomous Surface Vehicle for water quality and greenhouse gas emission monitoring , 2010, 2010 IEEE International Conference on Robotics and Automation.

[89]  Stefan B. Williams,et al.  An efficient approach to bathymetric SLAM , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[90]  Aníbal Ollero,et al.  A cooperative perception system for multiple UAVs: Application to automatic detection of forest fires , 2006, J. Field Robotics.

[91]  Junku Yuh,et al.  Design and Control of Autonomous Underwater Robots: A Survey , 2000, Auton. Robots.

[92]  Ralf D. Prien,et al.  The future of chemical in situ sensors , 2007 .

[93]  A. Ballesteros-Gómez,et al.  Recent advances in environmental analysis. , 2011, Analytical chemistry.

[94]  Tad McGeer,et al.  Autonomous aerosondes for economical atmospheric soundings anywhere on the globe , 1992 .

[95]  Peter Corke,et al.  A framework for marine sensor network & autonomous vehicle interaction , 2010, OCEANS'10 IEEE SYDNEY.

[96]  Patrick F Rynne,et al.  Development and Preliminary Experimental Validation of a Wind- and Solar-Powered Autonomous Surface Vehicle , 2010, IEEE Journal of Oceanic Engineering.

[97]  Arthur C. Sanderson,et al.  Multiscale adaptive sampling in environmental robotics , 2010, 2010 IEEE Conference on Multisensor Fusion and Integration.

[98]  Richard Han,et al.  Perspectives on next‐generation technology for environmental sensor networks , 2010 .

[99]  Josué Jr. Guimarães Ramos,et al.  A semi-autonomous robotic airship for environmental monitoring missions , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[100]  Naomi Ehrich Leonard,et al.  Coordination of an underwater glider fleet for adaptive sampling , 2005 .

[101]  Dana R. Yoerger,et al.  Autonomous Search for Hydrothermal Vent Fields with Occupancy Grid Maps , 2008 .

[102]  Neeraj Suri,et al.  ASample: Adaptive Spatial Sampling in Wireless Sensor Networks , 2010, 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing.

[103]  Mohd Rizal Arshad,et al.  Recent advancement in sensor technology for underwater applications , 2009 .

[104]  Dana R. Yoerger,et al.  Fine-Scale Three-Dimensional Mapping of a Deep-Sea Hydrothermal Vent Site Using the Jason ROV System , 2000, Int. J. Robotics Res..

[105]  Frederick Armstrong,et al.  Antarctic Krill Under Sea Ice: Elevated Abundance in a Narrow Band Just South of Ice Edge , 2002, Science.

[106]  Scott Willcox,et al.  The Wave Glider: A persistent platform for ocean science , 2010, OCEANS'10 IEEE SYDNEY.

[107]  Peter A Lieberzeit,et al.  Sensor technology and its application in environmental analysis , 2006, Analytical and bioanalytical chemistry.

[108]  Paul C. Hewett,et al.  From z > 5 quasars to d < 100 pc M-dwarfs. , 1996 .

[109]  James Udy,et al.  Quantification of ebullitive and diffusive methane release to atmosphere from a water storage , 2011 .

[110]  Sonia Martinez,et al.  Deployment algorithms for a power‐constrained mobile sensor network , 2010 .

[111]  Gaurav S. Sukhatme,et al.  USC CINAPS Builds Bridges , 2010, IEEE Robotics & Automation Magazine.

[112]  H. Singh,et al.  Integrating in-situ chemical sampling with AUV control systems , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[113]  D.J. Stilwell,et al.  A comparison of two approaches for adaptive sampling of environmental processes using autonomous underwater vehicles , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[114]  Andreas Terzis,et al.  Using mobile robots to harvest data from sensor fields , 2009, IEEE Wireless Communications.

[115]  Lino Marques,et al.  Olfaction-based mobile robot navigation , 2002 .