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1. The single robot line coverage problem: Theory, algorithms, and experiments

   https://doi.org/10.1002/net.22171  

   Agarwal, Saurav ; Akella, Srinivas ( July 2023 , Networks)

   Line coverage is the task of servicing a given set of one‐dimensional features in an environment. It is important for the inspection of linear infrastructure such as road networks, power lines, and oil and gas pipelines. This paper addresses the single robot line coverage problem for aerial and ground robots by modeling it as an optimization problem on a graph. The problem belongs to the broad class of arc routing problems and is closely related to the rural postman problem (RPP) on asymmetric graphs. The paper presents an integer linear programming formulation with proofs of correctness. Using the minimum cost flow problem, we develop approximation algorithms with guarantees on the solution quality. These guarantees also improve the existing results for the asymmetric RPP. The main algorithm partitions the problem into three cases based on the structure of therequired graph, that is, the graph induced by the features that require servicing. We evaluate our algorithms on road networks from the 50 most populous cities in the world, consisting of up to 730 road segments. The algorithms, augmented with improvement heuristics, run within 3 s and generate solutions that are within 10% of the optimum. We experimentally demonstrate our algorithms with commercial UAVs on the UNC Charlotte campus road network.

    

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2. Optimization and Representativeness of Atmospheric Chemical Sampling by Hovering Unmanned Aerial Vehicles Over Tropical Forests

   https://doi.org/10.1029/2020EA001335  

   Ma, Yongjing ; Ye, Jianhuai ; Ribeiro, Igor Oliveira ; Vilà‐Guerau de Arellano, Jordi ; Xin, Jinyuan ; Zhang, Wenyu ; Souza, Rodrigo Augusto Ferreira de ; Martin, Scot T. ( April 2021 , Earth and Space Science)

   Atmospheric chemical species play critical roles in ecosystem functioning and climate, but spatially resolving near‐surface concentrations has been challenging. In this regard, hovering unmanned aerial vehicles (UAVs) represent an emerging technology. The study herein provides guidance for optimized atmospheric sampling by hovering copter‐type UAVs. Large‐eddy simulations are conducted for species having chemical lifetimes ranging from reactive (i.e., 10²s) to long‐lived (i.e., 10⁸s). The case study of fair‐weather conditions over an equatorial tropical forest is used because of previous UAV deployments in this region. A framework is developed of influence length and horizontal shift of upwind surface emissions. The framework quantifies the length scale of the contribution of upwind forest emissions to species concentrations sampled by the downwind hovering UAV. Main findings include the following: (1) sampling within an altitude that is no more than 200 m above the canopy is recommended for both high‐ and intermediate‐reactivity species because of the strong decrease in species concentration even in a highly turbulent atmosphere; (2) sampling durations of at least 5 and 10 min are recommended for intermediate‐ and high‐reactivity species, respectively, because of the effects of atmospheric turbulence; and (3) in the case of heterogeneity of emissions across the underlying landscape, maximum recommended altitudes are presented for horizontal sampling strategies that can resolve the variability in the landscape emissions. The coupled effects of emission rate, wind speed, species lifetime, turbulence, and UAV sampling duration on influence length must all be considered for optimized and representative sampling over forests.

    

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3. Linking Subsurface to Surface Using Gas Emission and Melt Inclusion Data at Mount Cleveland Volcano, Alaska

   https://doi.org/10.1029/2019GC008882  

   Werner, C. ; Rasmussen, D. J. ; Plank, T. ; Kelly, P. J. ; Kern, C. ; Lopez, T. ; Gliss, J. ; Power, J. A. ; Roman, D. C. ; Izbekov, P. ; et al ( July 2020 , Geochemistry, Geophysics, Geosystems)

   Mount Cleveland is one of Alaska's most active volcanoes, yet little is known about the magmatic system driving persistent and dynamic volcanic activity. Volcanic gas and melt inclusion (MI) data from 2016 were combined to investigate shallow magmatic processes. SO₂emission rates were between 166 and 324 t/day and the H₂O/SO₂was 600 ± 53, whereas CO₂and H₂S were below detection. Olivine‐, clinopyroxene‐, and plagioclase‐hosted MIs have up to 3.8 wt.% H₂O, 514 ppm CO₂, and 2,320 ppm S. Equilibration depths, based on MI H₂O contents, suggest that a magmatic column extended from 0.5 to 3.0 km (~10–60 MPa). We used MI data to empirically model open‐system H‐C‐S degassing from 0 to 12 km and found that a column of magma between 0.5 and 3 km could produce the measured gas H₂O/SO₂ratio. However, additional magma deeper than 3 km is required to sustain emissions over periods greater than days to weeks, if the observed vent dimension is a valid proxy for the conduit. Assuming an initial S content of 2,320 ppm, the total magma supply needed to sustain the annual SO₂flux was 5 to 9.8 Mm³/yr, suggesting a maximum intrusive‐to‐extrusive ratio of 13:1. The model predicts degassing of <50 t/day CO₂for July 2016, which corresponds to a maximum predicted CO₂/SO₂of 0.2. Ultimately, frequent recharge from deeper, less degassed magma is required to drive the continuous activity observed over multiple years. During periods of recharge we would expect lower H₂O/SO₂and measurable volcanic CO₂.

    

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4. Efficient Concurrent Design of the Morphology of Unmanned Aerial Systems and their Collective-Search Behavior

   Zeng, Chen ; KrisshnaKumar, Prajit ; Witter, Jhoel ; Chowdhury, Souma ( October 2022 , 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

   The collective operation of robots, such as unmanned aerial vehicles (UAVs) operating as a team or swarm, is affected by their individual capabilities, which in turn is dependent on their physical design, aka morphology. However, with the exception of a few (albeit ad hoc) evolutionary robotics methods, there has been very little work on understanding the interplay of morphology and collective behavior. There is especially a lack of computational frameworks to concurrently search for the robot morphology and the hyper-parameters of their behavior model that jointly optimize the collective (team) performance. To address this gap, this paper proposes a new co-design framework. Here the exploding computational cost of an otherwise nested morphology/behavior co-design is effectively alleviated through the novel concept of “talent” metrics; while also allowing significantly better solutions compared to the typically sub-optimal sequential morphology → behavior design approach. This framework comprises four major steps: talent metrics selection, talent Pareto exploration (a multi-objective morphology optimization process), behavior optimization, and morphology finalization. This co-design concept is demonstrated by applying it to design UAVs that operate as a team to localize signal sources, e.g., in victim search and hazard localization. Here, the collective behavior is driven by a recently reported batch Bayesian search algorithm called Bayes-Swarm. Our case studies show that the outcome of co-design provides significantly higher success rates in signal source localization compared to a baseline design, across a variety of signal environments and teams with 6 to 15 UAVs. Moreover, this co-design process provides two orders of magnitude reduction in computing time compared to a projected nested design approach. 

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5. Floods increase carbon dioxide and methane fluxes in agricultural streams

   https://doi.org/10.1111/fwb.13614  

   Blackburn, Samuel R. ; Stanley, Emily H. ( September 2020 , Freshwater Biology)

   Changes in climate are causing floods to occur more often and more intensely in many parts of the world, including agricultural landscapes of southern Wisconsin (U.S.A.). How flooding and greater flood frequency affect stream carbon dioxide (CO₂) and methane (CH₄) fluxes and concentrations is not obvious. Thus, we asked how diffusive fluxes of CO₂and CH₄varied over time, particularly in response to floods, in agricultural streams, and what were likely causes for observed flood responses.

   We measured concentrations and diffusive fluxes of CO₂and CH₄at 10 stream sites in mixed agricultural and suburban catchments in southern Wisconsin (U.S.A.) during the growing season (March–November) in a year that experienced multiple floods. Habitat, hydrologic, and water chemistry attributes were also quantified to determine likely drivers of changes in gas concentrations and fluxes.

   Habitat and water chemistry, as well as CO₂and CH₄concentrations and fluxes were temporally erratic and lacked any seasonality. Carbon dioxide and CH₄concentrations and fluxes were higher during floods along with increased water velocity, turbidity, and dissolved organic carbon and decreases in dissolved oxygen, soft sediment depth, and macrophyte cover.

   Increased gas concentrations and fluxes were probably due to flushing of gases from soils, respiration of organic matter in the channel, and increased gas exchange velocities during floods.

   Flooding alleviated both supply and transfer limits on CO₂and CH₄emissions in these agricultural streams, and frequent and prolonged flooding during the growing season led to sustained high emissions from these streams. We hypothesise that such persistent increases in emissions during floods may be a common response to high precipitation periods for many agricultural streams.

    

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