Towards probabilistic causal discovery, inference & explanations for autonomous drones in mine surveying tasks

Causal modelling offers great potential to provide autonomous agents the ability to understand the data-generation process that governs their interactions with the world. Such models capture formal knowledge as well as probabilistic representations of noise and uncertainty typically encountered by autonomous robots in real-world environments. Thus, causality can aid autonomous agents in making decisions and explaining outcomes, but deploying causality in such a manner introduces new challenges. Here we identify challenges relating to causality in the context of a drone system operating in a salt mine. Such environments are challenging for autonomous agents because of the presence of confounders, non-stationarity, and a difficulty in building complete causal models ahead of time. To address these issues, we propose a probabilistic causal framework consisting of: causally-informed POMDP planning, online SCM adaptation, and post-hoc counterfactual explanations. Further, we outline planned experimentation to evaluate the framework integrated with a drone system in simulated mine environments and on a real-world mine dataset

Towards Probabilistic Causal Discovery, Inference & Explanations for Autonomous Drones in Mine Surveying Tasks

Causal modelling offers great potential to provide autonomous agents the ability to understand the data-generation process that governs their interactions with the world. Such models capture formal knowledge as well as probabilistic representations of noise and uncertainty typically encountered by autonomous robots in real-world environments. Thus, causality can aid autonomous agents in making decisions and explaining outcomes, but deploying causality in such a manner introduces new challenges. Here we identify challenges relating to causality in the context of a drone system operating in a salt mine. Such environments are challenging for autonomous agents because of the presence of confounders, non-stationarity, and a difficulty in building complete causal models ahead of time. To address these issues, we propose a probabilistic causal framework consisting of: causally-informed POMDP planning, online SCM adaptation, and post-hoc counterfactual explanations. Further, we outline planned experimentation to evaluate the framework integrated with a drone system in simulated mine environments and on a real-world mine dataset.Comment: 3 Pages, 1 Figure, To be published in the Proceedings of the "Causality for Robotics: Answering the Question of Why" workshop at the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Adjusted initial submission versio

Remote sensing data applied to the reconstruction of volcanic activity in the Valley of the Volcanoes, Central Volcanic Zone, Peru

The Valley of the Volcanoes is a representative area of the extension of the Quaternary Andahua Group with which it overlaps. Some of its eruption centres have renewed activity after more than 500 ka. Recreating the history of the Valley of the Volcanoes activity required satellite data and remote sensing-based methods for visualizing the terrain surface. We used SRTM 30 m DEM, channels 4, 3, 2; Landsat 7, 8 and ASTER images. We verified and refined the obtained data during field works using Structure-from-Motion (SfM) to create of 3D models of selected geoforms. Satellite data allowed us to create: Red Relief Image Map, Topographic Position Index and Normalised Difference Vegetation Index (NDVI) maps. In the Valley of the Volcanoes, we analysed 12 lava fields with a total area of 326.3 km2 and a volume of approx. 20 km3. We determined the number of eruptions centres that yielded to 41 small lava domes and 23 scoria cones. This domes are classified as monogenetic volcanoes, however five of them can be considered polygenetic e.g. Puca Mauras. We used NDVI to develop chronology map of lavas. This allowed us to extract same-age eruption centres and associated volcanoes that represent the same eruptive time phase connected by fault lines: first generation (0.5–0.27 Ma) NW-SE and NE-SW, second (Pleistocene/Holocene) NNW-SSE and third (Holocene-Historical) again NW-SE and NE-SW. We carried out the reconstruction of the central part of the Valley of the Volcanoes because only there repeated phases of volcanic activity can be inferred with remote sensing and geological mapping. The results of this study led us to indicate that this area should be observed since it is very likely that future eruptions will occur

Unravelling the long-term, locally-heterogenous response of Greenland glaciers observed in archival photography

We present an approach for extracting quantifiable information from archival aerial photographs to extend the temporal record of change over a region of the central eastern Greenland Ice Sheet. The photographs we use were gathered in the 1930s as part of a surveying expedition, and so they were not acquired with photogrammetric analysis in mind. Nevertheless, we are able to make opportunistic use of this imagery, as well as additional, novel data-sets, to explore changes at ice margins well before the advent of conventional satellite technology. The insights that a longer record of ice margin change bring is crucial for improving our understanding of how glaciers are responding to the changing climate. In addition, our work focuses on a series of relatively small and little studied outlet glaciers from the eastern margin of the Ice Sheet. We show that whilst air and sea surface temperatures are important controls on the rates at which these ice masses change, there is also significant heterogeneity in their responses, with non-climatic controls (such as the role of bathymetry in front of calving margins) being extremely important. In general, there is often a tendency to focus either on changes of the Greenland Ice Sheet as a whole, or on regional variations. Here, we suggest that even this approach masks important variability, and full understanding of the behaviour and response of the Ice Sheet requires us to consider changes that are taking place at the scale of individual glaciers

Structure-from-motion with varying principal point

We consider the problem of structure-from-motion (SfM) for images with fixed calibration but varying principal point. This scenario occurs for archival imagery taken using historic glass plate and film cameras without fiducial markers, when images have been inconsistently cropped or when image plates are broken into multiple fragments.We derive initialisation and pose estimation methods and regularisation penalties tuned specifically for this scenario leading to a complete archival imagery SfM pipeline. This problem is of special importance if imiage data set is limited. We illustrate the performance of our methods on challenging real world examples from image archives. Specifically, we use archival images of the East coast of Greenland from the British Arctic Air Route Expedition (BAARE). This is of particular glaciological interest for measuring historic ice loss. We use a modern digital elevation model (ArcticDEM), masked to stable regions, as ground truth to evaluate our method

Izzivi pri določanju višin gorskih vrhov, kot so navedene v kartografskih virih

This study aimed to measure and validate altitudes from existing sources with direct GNSS measurements and airborne lidar data. For this purpose, 12 mountain peaks located in the south part of Polish territory were selected. Measurements were performed using a GNSS receiver using the Real-Time Kinematic (RTK) or static techniques enabling altitude measurements with accuracy of 10 cm. GNSS was treated as the primary data source, as the direct field measurements can determine the highest point on each peak. The obtained results were confronted with historical, internet sources, and official altitude data. Moreover, each altitude was determined using lidar data from an airborne lidar dataset of Poland from the ISOK program and provided by the national agency. Significant discrepancies in data were already detected during the analysis of internet materials and traditional maps, up to a few meters. The differences between measured and internet sources in altitude of mountain peak range from 27 cm to 504 cm. This study has shown the need to re-measure the altitudes of the mountain peaks and determine the highest point correctly

Aloft: Self-Adaptive Drone Controller Testbed

Aerial drones are increasingly being considered as a valuable tool for inspection in safety critical contexts. Nowhere is this more true than in mining operations which present a dynamic and dangerous environment for human operators. Drones can be deployed in a number of contexts including efficient surveying as well as search and rescue missions. Operating in these dynamic contexts is challenging however and requires the drones control software to detect and adapt to conditions at run-time. To help in the development of such systems we present Aloft, a simulation supported testbed for investigating self-adaptive controllers for drones in mines. Aloft, utilises the Robot Operating system (ROS) and a model environment using Gazebo to provide a physics-based testing. The simulation environment is constructed from a 3D point cloud collected in a physical mock-up of a mine and contains features expected to be found in real-world contexts. Aloft allows members of the research community to deploy their own self-adaptive controllers into the control loop of the drone to evaluate the effectiveness and robustness of controllers in a challenging environment. To demonstrate our system we provide a self-adaptive drone controller and operating scenario as an exemplar. The self-adaptive drone controller provided, utilises a two-layered architecture with a MAPE-K feedback loop. The scenario is an inspection task during which we inject a communications failure. The aim of the controller is to detect this loss of communication and autonomously perform a return home behaviour. Limited battery life presents a constraint on the mission, which therefore means that the drone should complete its mission as fast as possible. Humans, however, might also be present within the environment. This poses a safety risk and the drone must be able to avoid collisions during autonomous flight. In this paper we describe the controller framework and the simulation environment and provide information on how a user might construct and evaluate their own controllers in the presence of disruptions at run-time

Cumulative Protective Effect of Melatonin and Indole-3-Propionic Acid against KIO3—Induced Lipid Peroxidation in Porcine Thyroid

Iodine deficiency is the main environmental factor leading to thyroid cancer. At the same time iodine excess may also contribute to thyroid cancer. Potassium iodate (KIO3), which is broadly used in salt iodization program, may increase oxidative damage to membrane lipids (lipid peroxidation, LPO) under experimental conditions, with the strongest damaging effect at KIO3 concentration of ~10 mM (corresponding to physiological iodine concentration in the thyroid). Melatonin and indole-3-propionic acid (IPA) are effective antioxidative indoles, each of which protects against KIO3-induced LPO in the thyroid. The study aims to check if melatonin used together with IPA (in their highest achievable in vitro concentrations) reveals stronger protective effects against KIO3-induced LPO in porcine thyroid homogenates than each of these antioxidants used separately. Homogenates were incubated in the presence of KIO3 (200; 100; 50; 25; 20; 15; 10; 7.5; 5.0; 2.5; 1.25; 0.0 mM) without/with melatonin (5 mM) or without/with IPA (10 mM) or without/with melatonin + IPA, and then, to further clarify the narrow range of KIO3 concentrations, against which melatonin + IPA reveal cumulative protective effects, the following KIO3 concentrations were used: 20; 18.75; 17.5; 16.25; 15; 13.75; 12.5; 11.25; 10; 8.75; 7.5; 0.0 mM. Malondialdehyde + 4-hydroxyalkenals (MDA + 4-HDA) concentration (LPO index) was measured spectrophotometrically. Protective effects of melatonin + IPA were stronger than those revealed by each antioxidant used separately, but only when LPO was induced by KIO3 in concentrations from 18.75 mM to 8.75 mM, corresponding to physiological iodine concentration in the thyroid. In conclusion, melatonin and indole-3-propionic acid exert cumulative protective effects against oxidative damage caused by KIO3, when this prooxidant is used in concentrations close to physiological iodine concentrations in the thyroid. Therefore, the simultaneous administration of these two indoles should be considered to prevent more effectively oxidative damage (and thereby thyroid cancer formation) caused by iodine compounds applied in iodine prophylaxis

Correction: Iwan et al. Pro-Oxidative Effect of KIO3 and Protective Effect of Melatonin in the Thyroid—Comparison to Other Tissues. Life 2021, 11, 592

In the original article [...

Pro-Oxidative Effect of KIO3 and Protective Effect of Melatonin in the Thyroid—Comparison to Other Tissues

Not only iodine deficiency, but also its excess may contribute to thyroid cancer. Potassium iodate (KIO3), which is broadly used in the salt iodization program, can increase oxidative damage to membrane lipids (lipid peroxidation, LPO) under experimental conditions, with the strongest damaging effect at KIO3 concentration of ~10 mM (corresponding to physiological iodine concentration in the thyroid). Melatonin is an effective antioxidant, which protects against KIO3-induced LPO in the thyroid. This study aimed to compare the protective effects of melatonin, used in the highest achievable in vitro concentration, against KIO3-induced oxidative damage to membrane lipids in various porcine tissues (thyroid, ovary, liver, kidney, brain, spleen, and small intestine). Homogenates were incubated in the presence of KIO3 (20; 15; 10; 7.5; 5.0; 0.0 mM) without/with melatonin (5 mM). The malondialdehyde + 4-hydroxyalkenals (MDA + 4-HDA) concentration (LPO index) was measured spectrophotometrically. KIO3 increased the LPO in all examined tissues; in the thyroid, the damaging effect of KIO3 (10; and 7.5 mM) was lower than in other tissues and was not observed for the lowest concentration of 5 mM. Melatonin reduced LPO induced by KIO3 (10, 7.5, and 5 mM) in all tissues, and in the thyroid it was also protective against as high a concentration of KIO3 as 15 mM; the LPO level resulting from KIO3 + melatonin treatment was lower in the thyroid than in other tissues. In conclusion, the thyroid is less sensitive tothe pro-oxidative effects of KIO3 compared to other tissues. The strongest protective effect of melatonin was observed in the thyroid, but beneficial effects were significant also in other tissues. Melatonin should be considered to avoid the potential damaging effects of iodine compounds applied in iodine prophylaxis