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While feature association to a global map has significant benefits, to keep the computations from growing exponentially, most lidar-based odometry and mapping methods opt to associate features with local maps at one voxel scale. Taking advantage of the fact that surfels (surface elements) at different voxel scales can be organized in a tree-like structure, we propose an octree-based global map of multi-scale surfels that can be updated incrementally. This alleviates the need for recalculating, for example, a k-d tree of the whole map repeatedly. The system can also take input from a single or a number of sensors, reinforcing the robustness in degenerate cases. We also propose a point-to-surfel (PTS) association scheme, continuous-time optimization on PTS and IMU preintegration factors, along with loop closure and bundle adjustment, making a complete framework for Lidar-Inertial continuous-time odometry and mapping. Experiments on public and in-house datasets demonstrate the advantages of our system compared to other state-of-the-art methods., QC 20230403

Autonomous mobile robots have in recent years started to enter households in the form of autonomous vacuum cleaners and lawn mowers. The applicability of more advanced and general purpose service robots is almost endless. That is, robots that can perform a variety of tasks, instead of being specialized for a single task. To this end, there are some fundamental challenges that need to be addressed. One of the key capabilities of an autonomous mobile robot is navigation. To achieve truly autonomous navigation, the robot has to be able to localize itself, plan, execute, and update a path that takes it to its desired location, and to generate a map on-the-fly of its environment if the environment is unknown or changing. This thesis focuses on the latter two of these challenges, planning and mapping. More specifically, we investigate in the scenario where the robot lacks any prior knowledge of the environment, referred to as autonomous exploration. One of the most important insights throughout the thesis is that these challenges should not be examined in isolation. As these are generally not the main tasks, a truly autonomous mobile robot shall perform; instead, they are necessities to fulfill higher-level tasks. Therefore, aspects such as flexibility and scalability should be regarded higher than simply accomplishing the task as efficiently or quickly as possible. Another insight, specifically regarding mapping, comes from surveying both consumers, the ones using the maps, and producers, the ones creating the maps. Ideally, a mapping framework should be optimized towards both, as it is pointless creating maps that cannot be used as well as assuming data can be extracted from a map in ways that are unfeasible. However, in existing works this is rare. A third insight, specifically regarding exploration, comes from breaking down typical assumptions and simplifications that are generally applied to make the problem tractable. We show that the problem is often formulated su, Autonoma mobila robotar har på senare år börjat komma in i hushållen i form av autonoma dammsugare och gräsklippare. Tillämpbarheten av mer avancerade och generella servicerobotar är nästan oändlig. Det vill säga robotar som kan utföra en mängd olika uppgifter, istället för att vara specialiserade för en enskild uppgift. För detta ändamål finns det några grundläggande utmaningar som måste lösas. En av nyckelfunktionerna hos en autonom mobil robot är navigering. För att uppnå verklig autonom navigering måste roboten kunna lokalisera sig själv, planera, utföra och uppdatera en plan som tar den till dess önskade plats, och generera en karta i farten över sin miljö om miljön är okänd, eller förändras. Denna avhandling fokuserar på de två senare av dessa utmaningar, planering och kartläggning. Närmare bestämt undersöker vi scenariot där roboten saknar förkunskaper om miljön, så kallad autonom utforskning. En av de viktigaste insikterna genom hela avhandlingen är att dessa utmaningar inte bör granskas isolerat. Eftersom dessa i allmänhet inte är huvuduppgifterna en verklig autonom mobil robot ska utföra; istället är de nödvändigheter för att utföra uppgifter på högre nivå. Därför bör aspekter som flexibilitet och skalbarhet ses som högre än att bara utföra uppgiften så effektivt eller snabbt som möjligt. En annan insikt, specifikt när det gäller kartläggning, kommer från kart-läggning av både konsumenter, de som använder kartorna, och producenter, de som skapar kartorna. Helst bör ett kartramverk optimeras för båda, eftersom det är meningslöst att skapa kartor som inte kan användas samt att anta att data kan extraheras från en karta på sätt som är omöjliga. I befintligt arbete är detta sällsynt. En tredje insikt, specifikt angående utforskning, kommer från att bryta ner typiska antaganden och förenklingar som generellt tillämpas för att göra problemet löst. Vi visar att problemet ofta formaliseras så att det leder till onödigt girigt beteende, där den förväntade informati, QC 20220224

We propose UFOExplorer, a fast and efficient exploration method that scales well with the environment size. An exploration paradigm driven by map updates is proposed to enable the robot to react quicker and to always move towards the optimal exploration goal. For each map update, a dense graph-based planning structure is updated and extended. The planning structure is then used to generate a path using a simple exploration heuristic, which guides the robot towards the closest exploration goal. The proposed method scales well with the environment size, as the planning cost is amortized when updating and extending the planning structure. The simple exploration heuristic performs on par with the most recent state-of-the-art methods in smaller environments and outperforms them in larger environments, both in terms of exploration speed and computational efficiency. The implementation of the method is made available for future research., QC 20220214

The task of exploration does not end when the robot has covered the entire environment. The world is dynamic and to model this property and to keep the map up to date the robot needs to re-explore. In this work, we present an approach to long-term exploration that builds on prior work on dynamic mapping, volumetric representations of space, and exploration planning. The main contribution of our work is a novel formulation of the information gain function that controls the exploration so that it trades off revisiting highly dynamic areas where changes are very likely with covering the rest of the environment to ensure both coverage and up-to-date estimates of the dynamics. We provide experimental validation of our approach in three different simulated environments., QC 20210818

In map-predictive exploration planning, the aim is to exploit a-priori map information to improve planning for exploration in otherwise unknown environments. The use of map predictions in exploration planning leads to exacerbated greediness, as map predictions allow the planner to defer exploring parts of the environment that have low value, e.g., unfinished corners. This behavior is undesirable, as it leaves holes in the explored space by design. To this end, we propose a scoring function based on inverse covisibility that rewards visiting these low-value parts, resulting in a more cohesive exploration process, and preventing excessive greediness in a map-predictive setting. We examine the behavior of a non-greedy map-predictive planner in a bare-bones simulator, and answer two principal questions: a) how far beyond explored space should a map predictor predict to aid exploration, i.e., is more better; and b) does shortest-path search as the basis for planning, a popular choice, cause greediness. Finally, we show that by thresholding covisibility, the user can trade-off greediness for improved early exploration performance., Part of proceedings: ISBN 978-166541213-1QC 20220602

Exposure to Per- and polyfluoroalkyl substances (PFAS) has been linked to multiple undesirable health outcomes across a full lifespan, both in animal models as well as in human epidemiological studies. Immunosuppressive effects of PFAS have been reported, including increased risk of infections and suppressed vaccination responses in early childhood, as well as association with immunotoxicity and diabetes. On a mechanistic level, PFAS exposure has been linked with metabolic disturbances, particularly in lipid metabolism, but the underlying mechanisms are poorly characterized. Herein we explore lipidomic signatures of prenatal and early-life exposure to perfluoroundecanoic acid (PFUnDA) in non-obese diabetic (NOD) mice; an experimental model of autoimmune diabetes. Female NOD mice were exposed to four levels of PFUnDA in drinking water at mating, during gestation and lactation, and during the first weeks of life of female offspring. At offspring age of 11-12 weeks, insulitis and immunological endpoints were assessed, and serum samples were collected for comprehensive lipidomic analyses. We investigated the associations between exposure, lipidomic profile, insulitis grade, number of macrophages and apoptotic, active-caspase-3-positive cells in pancreatic islets. Dose-dependent changes in lipidomic profiles in mice exposed to PFUnDA were observed, with most profound changes seen at the highest exposure levels. Overall, PFUnDA exposure caused downregulation of phospholipids and triacylglycerols containing polyunsaturated fatty acids. Our results show that PFUnDA exposure in NOD mice alters lipid metabolism and is associated with pancreatic insulitis grade. Moreover, the results are in line with those reported in human studies, thus suggesting NOD mice as a suitable model to study the impacts of environmental chemicals on T1D., Funding agency:Norwegian Institute of Public Health

The composition of human breast milk is highly variable inter- and intra-individually. Environmental factors are suspected to contribute to such compositional variation, however, their impact on breast milk composition is currently poorly understood. We sought to (1) define the impact of maternal exposure to per- and polyfluoroalkyl substances (PFAS) on lipid composition of human breast milk, and (2) to study the combined impact of maternal PFAS exposure and breast milk lipid composition on the growth of the infants.In a mother-infant study (n = 44) we measured the levels of PFAS and lipids in maternal serum and conducted lipidomics analysis of breast milk collect 2-4 days after the delivery and at 3 months of infant age, by using ultra high performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry. Gastrointestinal biomarkers fecal calprotectin and human beta defensin 2 were measured in the stool samples at the age of 3, 6, 9, and 12 months. Maternal diet was studied by a validated food frequency questionnaire. PFAS levels were inversely associated with total lipid levels in the breast milk collected after the delivery. In the high exposure group, the ratio of acylated saturated and polyunsaturated fatty acids in triacylglycerols was increased. Moreover, high exposure to PFAS associated with the altered phospholipid composition, which was indicative of unfavorable increase in the size of milk fat globules. These changes in the milk lipid composition were further associated with slower infant growth and with elevated intestinal inflammatory markers. Our data suggest that the maternal exposure to PFAS impacts the nutritional quality of the breast milk, which, in turn, may have detrimental impact on the health and growth of the children later in life., Funding agencies:United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) 1DP3DK094338-01 Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research 2012-17 250114Academy of Finland postdoctoral grant 323171Medical Research Fund, Tampere University HospitalMedical Research Fund, Helsinki University Hospital

Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study, Funding agencies:Spanish Government BFU2016-78951-R BFU2017-90578-REDT PID2020-116875RB-I00 MICINN RTI2018-095166-B-I00Comunidad de Madrid B2017/BMD-3684European Association for the Study of Diabetes (EASD)

In the last decade, increasing incidence of type 1 diabetes (T1D) stabilized in Finland, a phenomenon that coincides with tighter regulation of perfluoroalkyl substances (PFAS). Here, we quantified PFAS to examine their effects, during pregnancy, on lipid and immune-related markers of T1D risk in children. In a mother-infant cohort (264 dyads), high PFAS exposure during pregnancy associated with decreased cord serum phospholipids and progression to T1D-associated islet autoantibodies in the offspring. This PFAS-lipid association appears exacerbated by increased human leukocyte antigen-conferred risk of T1D in infants. Exposure to a single PFAS compound or a mixture of organic pollutants in non-obese diabetic mice resulted in a lipid profile characterized by a similar decrease in phospholipids, a marked increase of lithocholic acid, and accelerated insulitis. Our findings suggest that PFAS exposure during pregnancy contributes to risk and pathogenesis of T1D in offspring., Funding Agencies:United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK)1DP3DK094338-01Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research 250114Academy of Finland postdoctoral grant 323171Medical Research Funds, Tampere University Hospital Juvenile Diabetes Research Foundation 2-SRA-2016-341-S-B 2-SRA-2016-289-S-BMedical Research Funds, Helsinki University Hospital

Algorithms for autonomous robotic exploration usually focus on optimizing time and coverage, often in a greedy fashion. However, obstacle inflation is conservative and might limit mapping capabilities and even prevent the robot from moving through narrow, important places. This letter proposes a method to influence the manner the robot moves in the environment by taking into consideration a user-defined spatial preference formulated in a fragment of signal temporal logic (STL). We propose to guide the motion planning toward minimizing the violation of such preference through a cost function that integrates the quantitative semantics, i.e., robustness of STL. To demonstrate the effectiveness of the proposed approach, we integrate it into the autonomous exploration planner (AEP). Results from simulations and real-world experiments are presented, highlighting the benefits of our approach., QC 20190813

Exploration is an important aspect of robotics, whether it is for mapping, rescue missions, or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this letter, we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries., QC 20190404

This paper presents a collision avoidance method for tele-operated unmanned aerial vehicles (UAVs). The method is designed to assist the operator at all times, such that the operator can focus solely on the main objectives instead of avoiding obstacles. We restrict the altitude to be fixed in a three dimensional environment to simplify the control and operation of the UAV. The method contributes a number of desired properties not found in other collision avoidance systems for tele-operated UAVs. Our method i) can handle situations where there is no input from the user by actively stopping and proceeding to avoid obstacles, ii) allows the operator to slide between prioritizing staying away from objects and getting close to them in a safe way when so required, and iii) provides for intuitive control by not deviating too far from the control input of the operator. We demonstrate the effectiveness of the method in real world experiments with a physical hexacopter in different indoor scenarios. We also present simulation results where we compare controlling the UAV with and without our method activated., QC 20190319

For autonomous robots to have a deeper understanding of their environment, non-geometric, or semantic information, is required. However, there is currently a gap between the producers and consumers of dense semantic maps. Where producers are focused on reconstruction accuracy but not usability. We introduce an efficient semantic extension of the octree-based online 3D volumetric mapping framework UFOMap, for storing non-geometric information and to bridge this gap. By using a general semantic representation with a compact and dynamic data structure, our framework is capable of building large-scale semantic maps in real time. Benchmarks show that this semantic representation has more than an order of magnitude lower memory footprint than other approaches and up to three orders of magnitude faster queries of information. For example, UFOMap can construct truly large-scale volumetric semantic maps in real-time at high resolution. The framework is available as a standalone open source repository at https://github.com/UnknownFreeOccupied/ufomap and integrated with the Robot Operating System (ROS)., QC 20220228