The VolCAN Project

Volcano CO2 Sampling by Drone

You can tell a lot from the composition of the gasses coming from active volcanoes about what is happening deep beneath. It is even possible to predict when an active volcano will erupt causing widespread damage,and determine their contribution to climate change, yet gathering this critical data can be extremely hazardous to volcanologists.

An interdisciplinary team from UNM Departments of Computer Science, Earth and Planetary Sciences and Electric and Computer Engineering received a 4-year research grant from NSF’s National Robotics Initiative to develop novel bio-inspired software and drones to measure and sample volcanic gases. The team began this collaboration back in 2017 and participated in an international field expedition to the remote and dangerous volcanoes of Papua New Guinea sponsored by the Deep Carbon Observatory in Spring of 2019. During this expedition UNM researchers Tobias Fischer, Scott Nowicki (E and PS), Matthew Fricke and undergraduate student Jaret Jones (CS) successfully sampled the plume of Tavurvur and Manam Volcanoes for Carbon-isotopes, which provided information on the ultimate sources of carbon dioxide in these volcanoes. The results are about to be published in the journal Science Advances.

Following the expedition, UNM computer scientist Melanie Moses led the team to a successful proposal for the National Robotics Initiative to program swarms of drones so they work together to map the gas concentrations around volcanoes and so discover the richest places to sample. Writing code to allow drones to autonomously and collaboratively survey volcano gasses will allow small local monitoring stations to keep an eye on volcanoes, rather than having to rely on teams of drone pilots. The computer science efforts are spearheaded by Profs. Melanie Moses, Matthew Fricke and Jarred Saia specialists in bio-inspired algorithms. Drone hardware developments are lead by Prof. Rafael Fierro from Electric and Computer Engineering. Field testing, sensor development and science application are lead by Prof. Tobias Fischer and Dr. Scott Nowicki from Earth and Planetary Sciences. The team also includes several undergraduate students, M.Sc. students and Ph.D. students who will work synergistically within the VolCAN project.

“Our ultimate goal is to develop and test drone-platforms that enable scientists to collect data from active volcanoes that improve our understanding of volcanic processes and use that knowledge to forecast eruptions and save lives” said Tobias Fischer.

Tavurvur and Manam

Papua New Guinea

A major eruption of Tavurvur in 1994 destroyed the nearby provincial capital of Rabaul. Most of the town still lies under metres of ash. Another eruption in 2013 forced local people to evacuate.

A team from the University of New Mexico joined an expedition to Tavurvur led by Emma Liu of the University of Cambridge and supported by the Deep Carbon Observatory to test whether robotic drones could be used to reduce the risks of gathering volcanic samples. The team flew drones at Tavurvur and Manam volcanoes in Papua New Guinea. These volcanoes lie on the Pacific ring of fire. Drones were employed to place sensors in the crater of Tavurvur and sample gasses from multiple towering plumes. During the expedition a 7.5 earthquake caused the team to evacuate their hotel in the middle of the night, underscoring the danger of working in geologic hotspots. So far during the expedition two drones have been lost to the volcano, but drones can be replaced.

New Mexico Supervolcano

Valles Caldera

Valles Caldera is a supervolcano in northern New Mexico. A series of eruption in the Jemez volcano fields over the course of half a million years formed a caldera 15 miles wide. The presence of hot springs and CO2 emmisions near the caldera at Soda Dam and Hummingbird camp indicte that Valles Caldera is still an active volcanic system. We are sampling C02 emissions with automated UAS flights to better understand this system.

VolCAN Expedition to Iceland

Krýsuvík Geothermal Area, Fagradalsfjall Volcano & Sólheimajökull Glacier(on top of the Katla Volcano)

In early-September, 2022, VolCAN team members John Ericksen, Tobias Fischer, Matthew Fricke, Carter Frost, Melanie Moses, Karissa Rosenberger, Samantha Wolf, Rafael Fierro & Scott Nowicki traveled to Iceland. On September 3 the team visited the Krýsuvík Geothermal Area. September 4 & 5 the team was at the Fagradalsfjall Volcano where we flew multiple missions. September 7 the team few missions from the South East river outlet from Katla as well as at the Sólheimajökull Glacier(on top of the Katla Volcano). September 8 the team hiked out of Emstrur-Botnar Hut, along Laugavegur near Þórsmörk on the West side of Katla and few multiple missions.

VolCAN Expedition to Iceland 2022

Krýsuvík Geothermal Area, Fagradalsfjall Volcano & Sólheimajökull Glacier(on top of the Katla Volcano)

In late-November, 2021, VolCAN team members Tobias Fischer, Scott Nowicki, Matthew Fricke, and John Ericksen collected gas samples from the CO2 plume of the erupting Cumbre Vieja volcano. Cumbre Vieja is located on La Palma Island in Spain’s Canary Islands. The eruption, which began in September and ended in late December, is the largest in Europe in 500 years.
Volcanic lava flows from Cumbre Vieja destroyed more than 1,000 homes and covered significant parts of the Western side of the island with ash. The continuous emission of ash from the volcano resulted in frequent closing of the airport and evaculatons of towns and villages near the volcano. High sulfur dioxide and aerosol concentrations in the air, made for hazardous conditions. Frequent earthquakes and unpredictable lava flows added made gas sampling challenging for volcanologists.

VolCAN Expedition to La Palma 2021

Tajogaite volcanic eruption

VolCAN Expedition to Iceland 2023

Litli-Hrútur eruption

Publications

Boundary Sketching with Asymptotically Optimal Distance and Rotation

Varsha Dani, Abir Islam, Jared Saia

We address the problem of designing a distributed algorithm for two robots that sketches the boundary of an unknown shape. Critically, we assume a certain amount of delay in how quickly our robots can react to external feedback...

MLA: Dani, Varsha and Islam, Abir and Saia, Jared. (2023). Boundary Sketching with Asymptotically Optimal Distance and Rotation. Structural Information and Communication Complexity. 978-3-031-32733-9 357--385.

Aerial Survey Robotics in Extreme Environments: Mapping Volcanic CO2 Emissions With Flocking UAVs

John Ericksen, Matthew G. Fricke, Scott Nowicki, Tobias P. Fischer, Julie C. Hayes, Karissa Rosenberger, Samantha R. Wolf, Rafael Fierro, and Melanie E. Moses

We present methods for autonomous collaborative surveying of volcanic CO2 emissions using aerial robots. CO2 is a useful predictor of volcanic eruptions and an influential greenhouse gas. However, current CO2 mapping methods are hazardous and inefficient, as a result, only a small fraction of CO2 emitting volcanoes have been surveyed. We develop algorithms and a platform to measure volcanic CO2 emissions...

MLA: Ericksen, John and Fricke, G. Matthew and Nowicki, Scott and Fischer, Tobias P. and Hayes, Julie C. and Rosenberger, Karissa and Wolf, Samantha R. and Fierro, Rafael and Moses, Melanie E.. (2022). Aerial Survey Robotics in Extreme Environments: Mapping Volcanic CO2 Emissions With Flocking UAVs. Frontiers in Control Engineering. 3 .

Drone CO2 Measurements During the Tajogaite Volcanic Eruption

John Ericksen, Tobias Fischer, Scott Nowicki, Nemesio Pérez, Pedro Hernandez, Eleazar Padrón, Melanie Moses, G. Matthew Fricke

We report in-plume CO2 concentrations and isotope ratios during an active eruption of the Tajogaite Volcano. CO2 measurements inform our understanding of volcanic contributions to the global climate carbon cycle, and the role of CO2 in eruptions...

Under review at Science Advances.

LOCUS: A multi-robot loss-tolerant algorithm for surveying volcanic plumes

John Ericksen, Abhinav Aggarwal, G. Matthew Fricke, Melanie E. Moses

Measurement of volcanic CO2 flux by a drone swarm poses special challenges. Drones must be able to follow gas concentration gradients while tolerating frequent drone loss. We present the LoCUS algorithm as a solution to this problem and prove its robustness. LoCUS relies on swarm coordination and self-healing to solve the task...

MLA: Ericksen, John and Aggarwal, Abhinav and Fricke, G. Matthew and Moses, Melanie E.. (2020). LoCUS: A Multi-Robot Loss-Tolerant Algorithm for Surveying Volcanic Plumes. 2020 Fourth IEEE International Conference on Robotic Computing (IRC). 113 to 120. Status = Added in NSF-PAR doi: https://doi.org/10.1109/IRC.2020.00025

Adaptive Control for Cooperative Aerial Transportation Using Catenary Robots

Cardona, Gustavo A. and D'Antonio, Diego S. and Fierro, Rafael and Saldana, David

We present a method for cooperative transportation using two catenary robots. Each catenary robot is composed of two quadrotors connected by a hanging cable. Unlike other methods in the literature for aerial transportation using cables, we do not assume that the cables are attached to the object. Instead, the quadrotors wrap cables around the object and pull...

MLA: Cardona, Gustavo A. and D'Antonio, Diego S. and Fierro, Rafael and Saldana, David. (2021). Adaptive Control for Cooperative Aerial Transportation Using Catenary Robots. IEEE 2021 Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO). 1 to 8. Status = Added in NSF-PAR doi: https://doi.org/10.1109/AIRPHARO52252.2021.95...

Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change

Nichol, J. Jake and Peterson, Matthew G. and Peterson, Kara J. and Fricke, G. Matthew and Moses, Melanie E.

We use machine learning techniques, including random forest regression and Gini importance, to show that the Energy Exascale Earth System Model (E3SM) relies too heavily on just one of the ten chosen climatological quantities to predict September sea ice averages. Furthermore, E3SM gives too much importance to six of those quantities when compared to observed data. Identifying the features that climate models incorrectly rely on should allow climatologists to improve prediction accuracy.

MLA: Nichol, J. Jake and Peterson, Matthew G. and Peterson, Kara J. and Fricke, G. Matthew and Moses, Melanie E.. (2021). Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change. Journal of Computational and Applied Mathematics. 395 (C) 113451. doi: https://doi.org/10.1016/j.cam.2021.113451

Aerial strategies advance volcanic gas measurements at inaccessible, strongly degassing volcanoes

E. J. Liu1, A. Aiuppa, A. Alan, et.al.

Volcanic emissions are a critical pathway in Earth’s carbon cycle. Here, we show that aerial measurements of volcanic gases using unoccupied aerial systems (UAS) transform our ability to measure and monitor plumes remotely and to constrain global volatile fluxes from volcanoes...

MLA: Liu, Emma J., et al. "Aerial strategies advance volcanic gas measurements at inaccessible, strongly degassing volcanoes." Science Advances 6.44 (2020): eabb9103.

Enabling human–infrastructure interfaces for inspection using augmented reality

Maharjan, D and Agüero, M and Mascarenas, D and Fierro, R and Moreu, F.

This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions)...

MLA: Maharjan, D and Agüero, M and Mascarenas, D and Fierro, R and Moreu, F. (2021). Enabling human–infrastructure interfaces for inspection using augmented reality. Structural Health Monitoring. 20 (4) 1980 to 1996. Status = Added in NSF-PAR doi: https://doi.org/10.1177/1475921720977017

Multi-Robot system for autonomous cooperative counter-UAS missions: Design, integration, and field testing

A. Barisic, M. Ball, N. Jackson, R. McCarthy, N. Naimi, L. Strassle, J. Becker, M. Brunner, J. Fricke, L. Markovic, I. Seslar, D. Novick, J. Salton, R. Siegwart, S. Bogdan, and R. Fierro

With the rapid development of technology and the proliferation of uncrewed aerial systems (UAS), there is an immediate need for security solutions. Toward this end, we propose the use of a multi-robot system for autonomous and cooperative counter-UAS missions. In this paper, we present the design of the hardware and software components of different complementary robotic platforms: a mobile uncrewed ground vehicle (UGV) equipped with a LiDAR sensor, an uncrewed aerial vehicle (UAV) with a gimbal-mounted stereo camera for air-to-air inspections, and a UAV with a capture mechanism equipped with radars and camera...

MLA: A. Barisic, M. Ball, N. Jackson, R. McCarthy, N. Naimi, L. Strassle, J. Becker, M. Brunner, J. Fricke, L. Markovic, I. Seslar, D. Novick, J. Salton, R. Siegwart, S. Bogdan, and R. Fierro, “Multi-Robot system for autonomous cooperative counter-UAS missions: Design, integration, and field testing,” IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Sevilla, Spain, Nov. 2022, pp. 203-210. Status = AWAITING_PUBLICATION.

Robust Linear-Velocity-Free Formation Tracking of Multiple Quadrotors with Unknown Disturbances

J. Lin, Y. Wang, Z. Miao, Q. Lin, G. Hu, and R. Fierro

This article addresses the problem of quadrotor formation control with inaccessible linear velocity and the unknown disturbances under directed interaction topologies. Considering the unknown disturbances act in both the translational and rotational motions of each underactuated quadrotor, a hierarchical distributed disturbance rejection controller is developed for the quadrotor formation...

MLA: J. Lin, Y. Wang, Z. Miao, Q. Lin, G. Hu, and R. Fierro, “Robust Linear-Velocity-Free Formation Tracking of Multiple Quadrotors with Unknown Disturbances,” IEEE Transactions on Control of Network Systems, pp. 1-12, January 2023. doi: 10.1109/TCNS.2023.3239560.

out in the community

Outreach

Albuquerque, New Mexico

Bandelier Elementary School

Matthew Fricke and Carter Frost visited Tiara Dominguez's 5th grade class at Bandelier Elementary School. We discussed the hurtles of observing volcanoes as well as forging strategies with the students. The students had the opportunity to operate the Swarmie Robots using only the onboard sensors and controllers to locate a resource, pick it up and deliver it to a collection zone.

Hardware and Software Platform

DragonFly Autonomous UAS