| 1. |
- Molina, Sergi, et al.
(författare)
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The ILIAD Safety Stack : Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots
- 2023
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Ingår i: IEEE robotics & automation magazine. - : IEEE. - 1070-9932 .- 1558-223X.
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Tidskriftsartikel (refereegranskat)abstract
- Current intralogistics services require keeping up with e-commerce demands, reducing delivery times and waste, and increasing overall flexibility. As a consequence, the use of automated guided vehicles (AGVs) and, more recently, autonomous mobile robots (AMRs) for logistics operations is steadily increasing.
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| 2. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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A Submap per Perspective : Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality
- 2019
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Ingår i: 2019 European Conference on Mobile Robots (ECMR). - : IEEE. - 9781728136059
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Konferensbidrag (refereegranskat)abstract
- This paper targets high-precision robot localization. We address a general problem for voxel-based map representations that the expressiveness of the map is fundamentally limited by the resolution since integration of measurements taken from different perspectives introduces imprecisions, and thus reduces localization accuracy.We propose SuPer maps that contain one Submap per Perspective representing a particular view of the environment. For localization, a robot then selects the submap that best explains the environment from its perspective. We propose SuPer mapping as an offline refinement step between initial SLAM and deploying autonomous robots for navigation. We evaluate the proposed method on simulated and real-world data that represent an important use case of an industrial scenario with high accuracy requirements in an repetitive environment. Our results demonstrate a significantly improved localization accuracy, up to 46% better compared to localization in global maps, and up to 25% better compared to alternative submapping approaches.
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| 3. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry
- 2021
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Ingår i: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021). - : IEEE. - 9781665417143 - 9781665417150 ; , s. 5462-5469
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Konferensbidrag (refereegranskat)abstract
- This paper presents the accurate, highly efficient, and learning-free method CFEAR Radarodometry for large-scale radar odometry estimation. By using a filtering technique that keeps the k strongest returns per azimuth and by additionally filtering the radar data in Cartesian space, we are able to compute a sparse set of oriented surface points for efficient and accurate scan matching. Registration is carried out by minimizing a point-to-line metric and robustness to outliers is achieved using a Huber loss. We were able to additionally reduce drift by jointly registering the latest scan to a history of keyframes and found that our odometry method generalizes to different sensor models and datasets without changing a single parameter. We evaluate our method in three widely different environments and demonstrate an improvement over spatially cross-validated state-of-the-art with an overall translation error of 1.76% in a public urban radar odometry benchmark, running at 55Hz merely on a single laptop CPU thread.
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| 4. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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CorAl : Introspection for robust radar and lidar perception in diverse environments using differential entropy
- 2022
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Ingår i: Robotics and Autonomous Systems. - : Elsevier. - 0921-8890 .- 1872-793X. ; 155
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Tidskriftsartikel (refereegranskat)abstract
- Robust perception is an essential component to enable long-term operation of mobile robots. It depends on failure resilience through reliable sensor data and pre-processing, as well as failure awareness through introspection, for example the ability to self-assess localization performance. This paper presents CorAl: a principled, intuitive, and generalizable method to measure the quality of alignment between pairs of point clouds, which learns to detect alignment errors in a self-supervised manner. CorAl compares the differential entropy in the point clouds separately with the entropy in their union to account for entropy inherent to the scene. By making use of dual entropy measurements, we obtain a quality metric that is highly sensitive to small alignment errors and still generalizes well to unseen environments. In this work, we extend our previous work on lidar-only CorAl to radar data by proposing a two-step filtering technique that produces high-quality point clouds from noisy radar scans. Thus, we target robust perception in two ways: by introducing a method that introspectively assesses alignment quality, and by applying it to an inherently robust sensor modality. We show that our filtering technique combined with CorAl can be applied to the problem of alignment classification, and that it detects small alignment errors in urban settings with up to 98% accuracy, and with up to 96% if trained only in a different environment. Our lidar and radar experiments demonstrate that CorAl outperforms previous methods both on the ETH lidar benchmark, which includes several indoor and outdoor environments, and the large-scale Oxford and MulRan radar data sets for urban traffic scenarios. The results also demonstrate that CorAl generalizes very well across substantially different environments without the need of retraining.
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| 5. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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CorAl – Are the point clouds Correctly Aligned?
- 2021
-
Ingår i: 10th European Conference on Mobile Robots (ECMR 2021). - : IEEE.
-
Konferensbidrag (refereegranskat)abstract
- In robotics perception, numerous tasks rely on point cloud registration. However, currently there is no method that can automatically detect misaligned point clouds reliably and without environment-specific parameters. We propose "CorAl", an alignment quality measure and alignment classifier for point cloud pairs, which facilitates the ability to introspectively assess the performance of registration. CorAl compares the joint and the separate entropy of the two point clouds. The separate entropy provides a measure of the entropy that can be expected to be inherent to the environment. The joint entropy should therefore not be substantially higher if the point clouds are properly aligned. Computing the expected entropy makes the method sensitive also to small alignment errors, which are particularly hard to detect, and applicable in a range of different environments. We found that CorAl is able to detect small alignment errors in previously unseen environments with an accuracy of 95% and achieve a substantial improvement to previous methods.
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| 6. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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Lidar-Level Localization With Radar? The CFEAR Approach to Accurate, Fast, and Robust Large-Scale Radar Odometry in Diverse Environments
- 2023
-
Ingår i: IEEE Transactions on robotics. - : IEEE. - 1552-3098 .- 1941-0468. ; 39:2, s. 1476-1495
-
Tidskriftsartikel (refereegranskat)abstract
- This article presents an accurate, highly efficient, and learning-free method for large-scale odometry estimation using spinning radar, empirically found to generalize well across very diverse environments—outdoors, from urban to woodland, and indoors in warehouses and mines—without changing parameters. Our method integrates motion compensation within a sweep with one-to-many scan registration that minimizes distances between nearby oriented surface points and mitigates outliers with a robust loss function. Extending our previous approach conservative filtering for efficient and accurate radar odometry (CFEAR), we present an in-depth investigation on a wider range of datasets, quantifying the importance of filtering, resolution, registration cost and loss functions, keyframe history, and motion compensation. We present a new solving strategy and configuration that overcomes previous issues with sparsity and bias, and improves our state-of-the-art by 38%, thus, surprisingly, outperforming radar simultaneous localization and mapping (SLAM) and approaching lidar SLAM. The most accurate configuration achieves 1.09% error at 5 Hz on the Oxford benchmark, and the fastest achieves 1.79% error at 160 Hz.
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| 7. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
-
Oriented surface points for efficient and accurate radar odometry
- 2021
-
Konferensbidrag (refereegranskat)abstract
- This paper presents an efficient and accurate radar odometry pipeline for large-scale localization. We propose a radar filter that keeps only the strongest reflections per-azimuth that exceeds the expected noise level. The filtered radar data is used to incrementally estimate odometry by registering the current scan with a nearby keyframe. By modeling local surfaces, we were able to register scans by minimizing a point-to-line metric and accurately estimate odometry from sparse point sets, hence improving efficiency. Specifically, we found that a point-to-line metric yields significant improvements compared to a point-to-point metric when matching sparse sets of surface points. Preliminary results from an urban odometry benchmark show that our odometry pipeline is accurate and efficient compared to existing methods with an overall translation error of 2.05%, down from 2.78% from the previously best published method, running at 12.5ms per frame without need of environmental specific training.
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| 8. |
- Adolfsson, Daniel, 1992-
(författare)
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Robust large-scale mapping and localization : Combining robust sensing and introspection
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The presence of autonomous systems is rapidly increasing in society and industry. To achieve successful, efficient, and safe deployment of autonomous systems, they must be navigated by means of highly robust localization systems. Additionally, these systems need to localize accurately and efficiently in realtime under adverse environmental conditions, and within considerably diverse and new previously unseen environments.This thesis focuses on investigating methods to achieve robust large-scale localization and mapping, incorporating robustness at multiple stages. Specifically, the research explores methods with sensory robustness, utilizing radar, which exhibits tolerance to harsh weather, dust, and variations in lighting conditions. Furthermore, the thesis presents methods with algorithmic robustness, which prevent failures by incorporating introspective awareness of localization quality. This thesis aims to answer the following research questions:How can radar data be efficiently filtered and represented for robust radar odometry? How can accurate and robust odometry be achieved with radar? How can localization quality be assessed and leveraged for robust detection of localization failures? How can self-awareness of localization quality be utilized to enhance the robustness of a localization system?While addressing these research questions, this thesis makes the following contributions to large-scale localization and mapping: A method for robust and efficient radar processing and state-of-the-art odometry estimation, and a method for self-assessment of localization quality and failure detection in lidar and radar localization. Self-assessment of localization quality is integrated into robust systems for large-scale Simultaneous Localization And Mapping, and rapid global localization in prior maps. These systems leverage self-assessment of localization quality to improve performance and prevent failures in loop closure and global localization, and consequently achieve safe robot localization.The methods presented in this thesis were evaluated through comparative assessments of public benchmarks and real-world data collected from various industrial scenarios. These evaluations serve to validate the effectiveness and reliability of the proposed approaches. As a result, this research represents a significant advancement toward achieving highly robust localization capabilities with broad applicability.
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| 9. |
- Adolfsson, Daniel, 1992-, et al.
(författare)
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TBV Radar SLAM - Trust but Verify Loop Candidates
- 2023
-
Ingår i: IEEE Robotics and Automation Letters. - : IEEE. - 2377-3766. ; 8:6, s. 3613-3620
-
Tidskriftsartikel (refereegranskat)abstract
- Robust SLAM in large-scale environments requires fault resilience and awareness at multiple stages, from sensing and odometry estimation to loop closure. In this work, we present TBV (Trust But Verify) Radar SLAM, a method for radar SLAM that introspectively verifies loop closure candidates. TBV Radar SLAM achieves a high correct-loop-retrieval rate by combining multiple place-recognition techniques: tightly coupled place similarity and odometry uncertainty search, creating loop descriptors from origin-shifted scans, and delaying loop selection until after verification. Robustness to false constraints is achieved by carefully verifying and selecting the most likely ones from multiple loop constraints. Importantly, the verification and selection are carried out after registration when additional sources of loop evidence can easily be computed. We integrate our loop retrieval and verification method with a robust odometry pipeline within a pose graph framework. By evaluation on public benchmarks we found that TBV Radar SLAM achieves 65% lower error than the previous state of the art. We also show that it generalizes across environments without needing to change any parameters. We provide the open-source implementation at https://github.com/dan11003/tbv_slam_public
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| 10. |
- Alhashimi, Anas, 1978-, et al.
(författare)
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BFAR – Bounded False Alarm Rate detector for improved radar odometry estimation
- 2021
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Konferensbidrag (refereegranskat)abstract
- This paper presents a new detector for filtering noise from true detections in radar data, which improves the state of the art in radar odometry. Scanning Frequency-Modulated Continuous Wave (FMCW) radars can be useful for localisation and mapping in low visibility, but return a lot of noise compared to (more commonly used) lidar, which makes the detection task more challenging. Our Bounded False-Alarm Rate (BFAR) detector is different from the classical Constant False-Alarm Rate (CFAR) detector in that it applies an affine transformation on the estimated noise level after which the parameters that minimize the estimation error can be learned. BFAR is an optimized combination between CFAR and fixed-level thresholding. Only a single parameter needs to be learned from a training dataset. We apply BFAR tothe use case of radar odometry, and adapt a state-of-the-art odometry pipeline (CFEAR), replacing its original conservative filtering with BFAR. In this way we reduce the state-of-the-art translation/rotation odometry errors from 1.76%/0.5◦/100 m to 1.55%/0.46◦/100 m; an improvement of 12.5%.
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| 11. |
- Alvfors, Per, et al.
(författare)
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Research and development challenges for Swedish biofuel actors – three illustrative examples
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Currently biofuels have strong political support, both in the EU and Sweden. The EU has, for example, set a target for the use of renewable fuels in the transportation sector stating that all EU member states should use 10% renewable fuels for transport by 2020. Fulfilling this ambition will lead to an enormous market for biofuels during the coming decade. To avoid increasing production of biofuels based on agriculture crops that require considerable use of arable area, focus is now to move towards more advanced second generation (2G) biofuels that can be produced from biomass feedstocks associated with a more efficient land use.Climate benefits and greenhouse gas (GHG) balances are aspects often discussed in conjunction with sustainability and biofuels. The total GHG emissions associated with production and usage of biofuels depend on the entire fuel production chain, mainly the agriculture or forestry feedstock systems and the manufacturing process. To compare different biofuel production pathways it is essential to conduct an environmental assessment using the well-to-tank (WTT) analysis methodology. In Sweden the conditions for biomass production are favourable and we have promising second generation biofuels technologies that are currently in the demonstration phase. In this study we have chosen to focus on cellulose based ethanol, methane from gasification of solid wood as well as DME from gasification of black liquor, with the purpose of identifying research and development potentials that may result in improvements in the WTT emission values. The main objective of this study is thus to identify research and development challenges for Swedish biofuel actors based on literature studies as well as discussions with the the researchers themselves. We have also discussed improvement potentials for the agriculture and forestry part of the WTT chain. The aim of this study is to, in the context of WTT analyses, (i) increase knowledge about the complexity of biofuel production, (ii) identify and discuss improvement potentials, regarding energy efficiency and GHG emissions, for three biofuel production cases, as well as (iii) identify and discuss improvement potentials regarding biomass supply, including agriculture/forestry. The scope of the study is limited to discussing the technologies, system aspects and climate impacts associated with the production stage. Aspects such as the influence on biodiversity and other environmental and social parameters fall beyond the scope of this study. We find that improvement potentials for emissions reductions within the agriculture/forestry part of the WTT chain include changing the use of diesel to low-CO2-emitting fuels, changing to more fuel-efficient tractors, more efficient cultivation and manufacture of fertilizers (commercial nitrogen fertilizer can be produced in plants which have nitrous oxide gas cleaning) as well as improved fertilization strategies (more precise nitrogen application during the cropping season). Furthermore, the cultivation of annual feedstock crops could be avoided on land rich in carbon, such as peat soils and new agriculture systems could be introduced that lower the demand for ploughing and harrowing. Other options for improving the WTT emission values includes introducing new types of crops, such as wheat with higher content of starch or willow with a higher content of cellulose. From the case study on lignocellulosic ethanol we find that 2G ethanol, with co-production of biogas, electricity, heat and/or wood pellet, has a promising role to play in the development of sustainable biofuel production systems. Depending on available raw materials, heat sinks, demand for biogas as vehicle fuel and existing 1G ethanol plants suitable for integration, 2G ethanol production systems may be designed differently to optimize the economic conditions and maximize profitability. However, the complexity connected to the development of the most optimal production systems require improved knowledge and involvement of several actors from different competence areas, such as chemical and biochemical engineering, process design and integration and energy and environmental systems analysis, which may be a potential barrier. Three important results from the lignocellulosic ethanol study are: (i) the production systems could be far more complex and intelligently designed than previous studies show, (ii) the potential improvements consist of a large number of combinations of process integration options wich partly depends on specific local conditions, (iii) the environmental performance of individual systems may vary significantly due to systems design and local conditons.From the case study on gasification of solid biomass for the production of biomethane we find that one of the main advantages of this technology is its high efficiency in respect to converting biomass into fuels for transport. For future research we see a need for improvements within the gas up-grading section, including gas cleaning and gas conditioning, to obtain a more efficient process. A major challenge is to remove the tar before the methanation reaction. Three important results from the biomethane study are: (i) it is important not to crack the methane already produced in the syngas, which indicates a need for improved catalysts for selective tar cracking, (ii) there is a need for new gas separation techniques to facilitate the use of air oxidation agent instead of oxygen in the gasifier, and (iii) there is a need for testing the integrated process under realistic conditions, both at atmospheric and pressurized conditions. From the case study on black liquor gasification for the production of DME we find that the process has many advantages compared to other biofuel production options, such as the fact that black liquor is already partially processed and exists in a pumpable, liquid form, and that the process is pressurised and tightly integrated with the pulp mill, which enhances fuel production efficiency. However, to achieve commercial status, some challenges still remain, such as demonstrating that materials and plant equipment meet the high availability required when scaling up to industrial size in the pulp mill, and also proving that the plant can operate according to calculated heat and material balances. Three important results from the DME study are: (i) that modern chemical pulp mills, having a potential surplus of energy, could become important suppliers of renewable fuels for transport, (ii) there is a need to demonstrate that renewable DME/methanol will be proven to function in large scale, and (iii) there is still potential for technology improvements and enhanced energy integration. Although quantitative improvement potentials are given in the three biofuel production cases, it is not obvious how these potentials would affect WTT values, since the biofuel production processes are complex and changing one parameter impacts other parameters. The improvement potentials are therefore discussed qualitatively. From the entire study we have come to agree on the following common conclusions: (i) research and development in Sweden within the three studied 2G biofuel production technologies is extensive, (ii) in general, the processes, within the three cases, work well at pilot and demonstration scale and are now in a phase to be proven in large scale, (iii) there is still room for improvement although some processes have been known for decades, (iv) the biofuel production processes are complex and site specific and process improvements need to be seen and judged from a broad systems perspective (both within the production plant as well as in the entire well-to-tank perspective), and (v) the three studied biofuel production systems are complementary technologies. Futher, the process of conducting this study is worth mentioning as a result itself, i.e. that many different actors within the field have proven their ability and willingness to contribute to a common report, and that the cooperation climate was very positive and bodes well for possible future collaboration within the framework of the f3 center. Finally, judging from the political ambitions it is clear that the demand for renewable fuels will significantly increase during the coming decade. This will most likely result in opportunities for a range of biofuel options. The studied biofuel options all represent 2G biofuels and they can all be part of the solution to meet the increased renewable fuel demand.
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| 12. |
- Andreasson, Henrik, 1977-, et al.
(författare)
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Has something changed here? : Autonomous difference detection for security patrol robots
- 2007
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Ingår i: 2007 IEEE/RSJ international conference on intelligent robots and systems. - New York, NY, USA : IEEE. - 9781424409129 ; , s. 3429-3435
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Konferensbidrag (refereegranskat)abstract
- This paper presents a system for autonomous change detection with a security patrol robot. In an initial step a reference model of the environment is created and changes are then detected with respect to the reference model as differences in coloured 3D point clouds, which are obtained from a 3D laser range scanner and a CCD camera. The suggested approach introduces several novel aspects, including a registration method that utilizes local visual features to determine point correspondences (thus essentially working without an initial pose estimate) and the 3D-NDT representation with adaptive cell size to efficiently represent both the spatial and colour aspects of the reference model. Apart from a detailed description of the individual parts of the difference detection system, a qualitative experimental evaluation in an indoor lab environment is presented, which demonstrates that the suggested system is able register and detect changes in spatial 3D data and also to detect changes that occur in colour space and are not observable using range values only.
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| 13. |
- Andreasson, Henrik, 1977-, et al.
(författare)
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Incorporating Ego-motion Uncertainty Estimates in Range Data Registration
- 2017
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Ingår i: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538626825 - 9781538626832 ; , s. 1389-1395
-
Konferensbidrag (refereegranskat)abstract
- Local scan registration approaches commonlyonly utilize ego-motion estimates (e.g. odometry) as aninitial pose guess in an iterative alignment procedure. Thispaper describes a new method to incorporate ego-motionestimates, including uncertainty, into the objective function of aregistration algorithm. The proposed approach is particularlysuited for feature-poor and self-similar environments,which typically present challenges to current state of theart registration algorithms. Experimental evaluation showssignificant improvements in accuracy when using data acquiredby Automatic Guided Vehicles (AGVs) in industrial productionand warehouse environments.
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| 14. |
- Gupta, Himanshu, 1993-, et al.
(författare)
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Revisiting Distribution-Based Registration Methods
- 2023
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Ingår i: 2023 European Conference on Mobile Robots (ECMR). - : IEEE. - 9798350307047 - 9798350307054 ; , s. 43-48
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Konferensbidrag (refereegranskat)abstract
- Normal Distribution Transformation (NDT) registration is a fast, learning-free point cloud registration algorithm that works well in diverse environments. It uses the compact NDT representation to represent point clouds or maps as a spatial probability function that models the occupancy likelihood in an environment. However, because of the grid discretization in NDT maps, the global minima of the registration cost function do not always correlate to ground truth, particularly for rotational alignment. In this study, we examined the NDT registration cost function in-depth. We evaluated three modifications (Student-t likelihood function, inflated covariance/heavily broadened likelihood curve, and overlapping grid cells) that aim to reduce the negative impact of discretization in classical NDT registration. The first NDT modification improves likelihood estimates for matching the distributions of small population sizes; the second modification reduces discretization artifacts by broadening the likelihood tails through covariance inflation; and the third modification achieves continuity by creating the NDT representations with overlapping grid cells (without increasing the total number of cells). We used the Pomerleau Dataset evaluation protocol for our experiments and found significant improvements compared to the classic NDT D2D registration approach (27.7% success rate) using the registration cost functions "heavily broadened likelihood NDT" (HBL-NDT) (34.7% success rate) and "overlapping grid cells NDT" (OGC-NDT) (33.5% success rate). However, we could not observe a consistent improvement using the Student-t likelihood-based registration cost function (22.2% success rate) over the NDT P2D registration cost function (23.7% success rate). A comparative analysis with other state-of-art registration algorithms is also presented in this work. We found that HBL-NDT worked best for easy initial pose difficulties scenarios making it suitable for consecutive point cloud registration in SLAM application.
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| 15. |
- Magnusson, Martin, 1977-, et al.
(författare)
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Semi-Supervised 3D Place Categorisation by Descriptor Clustering
- 2017
-
Ingår i: IROS Vancouver 2017. - Piscataway : Institute of Electrical and Electronics Engineers (IEEE). - 9781538626825 - 9781538626818 - 9781538626832 ; , s. 620-625
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Konferensbidrag (refereegranskat)abstract
- Place categorisation; i.e., learning to group perception data into categories based on appearance; typically uses supervised learning and either visual or 2D range data. This paper shows place categorisation from 3D data without any training phase. We show that, by leveraging the NDT histogram descriptor to compactly encode 3D point cloud appearance, in combination with standard clustering techniques, it is possible to classify public indoor data sets with accuracy comparable to, and sometimes better than, previous supervised training methods. We also demonstrate the effectiveness of this approach to outdoor data, with an added benefit of being able to hierarchically categorise places into sub-categories based on a user-selected threshold. This technique relieves users of providing relevant training data, and only requires them to adjust the sensitivity to the number of place categories, and provide a semantic label to each category after the process is completed. © 2017 IEEE.
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| 16. |
- Mielle, Malcolm, 1991-, et al.
(författare)
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SLAM auto-complete : completing a robot map using an emergency map
- 2017
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Ingår i: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR). - : IEEE conference proceedings. - 9781538639238 - 9781538639245 ; , s. 35-40
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Konferensbidrag (refereegranskat)abstract
- In search and rescue missions, time is an important factor; fast navigation and quickly acquiring situation awareness might be matters of life and death. Hence, the use of robots in such scenarios has been restricted by the time needed to explore and build a map. One way to speed up exploration and mapping is to reason about unknown parts of the environment using prior information. While previous research on using external priors for robot mapping mainly focused on accurate maps or aerial images, such data are not always possible to get, especially indoor. We focus on emergency maps as priors for robot mapping since they are easy to get and already extensively used by firemen in rescue missions. However, those maps can be outdated, information might be missing, and the scales of rooms are typically not consistent.We have developed a formulation of graph-based SLAM that incorporates information from an emergency map. The graph-SLAM is optimized using a combination of robust kernels, fusing the emergency map and the robot map into one map, even when faced with scale inaccuracies and inexact start poses.We typically have more than 50% of wrong correspondences in the settings studied in this paper, and the method we propose correctly handles them. Experiments in an office environment show that we can handle up to 70% of wrong correspondences and still get the expected result. The robot can navigate and explore while taking into account places it has not yet seen. We demonstrate this in a test scenario and also show that the emergency map is enhanced by adding information not represented such as closed doors or new walls.
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| 17. |
- Mielle, Malcolm, 1991-, et al.
(författare)
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Using emergency maps to add not yet explored places into SLAM
- 2017
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- While using robots in search and rescue missions would help ensure the safety of first responders, a key issue is the time needed by the robot to operate. Even though SLAM is faster and faster, it might still be too slow to enable the use of robots in critical situations. One way to speed up operation time is to use prior information.We aim at integrating emergency-maps into SLAM to complete the SLAM map with information about not yet explored part of the environment. By integrating prior information, we can speed up exploration time or provide valuable prior information for navigation, for example, in case of sensor blackout/failure. However, while extensively used by firemen in their operations, emergency maps are not easy to integrate in SLAM since they are often not up to date or with non consistent scales.The main challenge we are tackling is in dealing with the imperfect scale of the rough emergency maps and integrate it with the online SLAM map in addition to challenges due to incorrect matches between these two types of map. We developed a formulation of graph-based SLAM incorporating information from an emergency map into SLAM, and propose a novel optimization process adapted to this formulation.We extract corners from the emergency map and the SLAM map, in between which we find correspondences using a distance measure. We then build a graph representation associating information from the emergency map and the SLAM map. Corners in the emergency map, corners in the robot map, and robot poses are added as nodes in the graph, while odometry, corner observations, walls in the emergency map, and corner associations are added as edges. To conserve the topology of the emergency map, but correct its possible errors in scale, edges representing the emergency map's walls are given a covariance so that they are easy to extend or shrink but hard to rotate. Correspondences between corners represent a zero transformation for the optimization to match them as close as possible. The graph optimization is done by using a combination robust kernels. We first use the Huber kernel, to converge toward a good solution, followed by Dynamic Covariance Scaling, to handle the remaining errors.We demonstrate our system in an office environment. We run the SLAM online during the exploration. Using the map enhanced by information from the emergency map, the robot was able to plan the shortest path toward a place it has not yet explored. This capability can be a real asset in complex buildings where exploration can take up a long time. It can also reduce exploration time by avoiding exploration of dead-ends, or search of specific places since the robot knows where it is in the emergency map.
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| 18. |
- Stoyanov, Todor, 1984-, et al.
(författare)
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Fast and accurate scan registration through minimization of the distance between compact 3D NDT Representations
- 2012
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Ingår i: The international journal of robotics research. - : Sage Publications. - 0278-3649 .- 1741-3176. ; 31:12, s. 1377-1393
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Tidskriftsartikel (refereegranskat)abstract
- Registration of range sensor measurements is an important task in mobile robotics and has received a lot of attention. Several iterative optimization schemes have been proposed in order to align three-dimensional (3D) point scans. With the more widespread use of high-frame-rate 3D sensors and increasingly more challenging application scenarios for mobile robots, there is a need for fast and accurate registration methods that current state-of-the-art algorithms cannot always meet. This work proposes a novel algorithm that achieves accurate point cloud registration an order of a magnitude faster than the current state of the art. The speedup is achieved through the use of a compact spatial representation: the Three-Dimensional Normal Distributions Transform (3D-NDT). In addition, a fast, global-descriptor based on the 3D-NDT is defined and used to achieve reliable initial poses for the iterative algorithm. Finally, a closed-form expression for the covariance of the proposed method is also derived. The proposed algorithms are evaluated on two standard point cloud data sets, resulting in stable performance on a par with or better than the state of the art. The implementation is available as an open-source package for the Robot Operating system (ROS).
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| 19. |
- Sun, L., et al.
(författare)
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Localising Faster : Efficient and precise lidar-based robot localisation in large-scale environments
- 2020
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Ingår i: 2020 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE. - 9781728173962 - 9781728173955 ; , s. 4386-4392
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a novel approach for global localisation of mobile robots in large-scale environments. Our method leverages learning-based localisation and filtering-based localisation, to localise the robot efficiently and precisely through seeding Monte Carlo Localisation (MCL) with a deeplearned distribution. In particular, a fast localisation system rapidly estimates the 6-DOF pose through a deep-probabilistic model (Gaussian Process Regression with a deep kernel), then a precise recursive estimator refines the estimated robot pose according to the geometric alignment. More importantly, the Gaussian method (i.e. deep probabilistic localisation) and nonGaussian method (i.e. MCL) can be integrated naturally via importance sampling. Consequently, the two systems can be integrated seamlessly and mutually benefit from each other. To verify the proposed framework, we provide a case study in large-scale localisation with a 3D lidar sensor. Our experiments on the Michigan NCLT long-term dataset show that the proposed method is able to localise the robot in 1.94 s on average (median of 0.8 s) with precision 0.75 m in a largescale environment of approximately 0.5 km 2.
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| 20. |
- Björkman, Henrik, 1977-
(författare)
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Alternative Methods for Assessment of Split Renal Function
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Living kidney donation is a clinical situation with unique features in the sense that healthy individuals voluntarily expose themselves to certain risks and inconveniences. Therefore, eliminating as much of the associated discomfort as possible is crucial. The primary aim of this study was to evaluate whether it is possible to use the examination with computed tomography (CT), which is essential to the investigation, also for determining the ratio of the two kidneys’ function – the split renal function. If possible, an examination with gamma camera renography could be excluded from the work-up. To investigate this possibility, 27 subjects who had underwent CT and renography as part of kidney donor investigation were studied retrospectively. The quantity of contrast material in each kidney was considered proportional to that kidney’s function, and measurement was made in each of the two available contrast phases. The results were compared to the results from renography. A similar analysis was conducted in 38 patients investigated for suspected renal artery stenosis with CT and renography, including a study of an automatized method for the acquisition of data from CT. For further scrutiny, a respiratory triggered dynamic contrast-enhanced magnetic resonance imaging (MRI) examination was investigated in 26 individuals. Results of split renal function were compared with renography and with CT in a subgroup. To study the possibility of facilitating the data analysis with CT, a formula for approximation of the contrast attenuation was studied in 64 subjects. An analysis of the significance of choice of contrast phase was also conducted in 43 subjects. Unsatisfactory agreement with renography resulted from the CT analysis of previous donors, partly due to technical shortcomings. However, the technique was recognized to have a potential value. In the subsequent material, the settings were improved, with beneficial effects on the agreement. Respiratory-triggered MRI generated high quality examinations of renal uptake and excretion, with results harmonizing well with renography and CT. The approximation formula applied to CT resulted in higher accuracy for renal volume assessment than with the automatic method, and an acceptable agreement of the split renal function estimate. From the presented results, a revision of the current donor investigation protocol is suggested. CT gives sufficient information to exclude renography as a routine examination. In cases of uncertainty, renography is recommended for secondary evaluation.
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| 21. |
- Gauffin, Håkan, et al.
(författare)
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Knee Arthroscopic Surgery in Middle-Aged Patients With Meniscal Symptoms A 3-Year Follow-up of a Prospective, Randomized Study
- 2017
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Ingår i: American Journal of Sports Medicine. - : SAGE PUBLICATIONS INC. - 0363-5465 .- 1552-3365. ; 45:9, s. 2077-2084
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Tidskriftsartikel (refereegranskat)abstract
- Background: The optimal treatment for middle-aged patients with knee pain and meniscal lesions has been extensively debated. Most previous studies have revealed only short-term beneficial results of knee arthroscopic surgery. The authors have previously shown a positive benefit of knee arthroscopic surgery and an exercise program after 1 year when compared with an exercise program alone. Purpose: To evaluate if knee arthroscopic surgery combined with an exercise program provided an additional long-term benefit after 3 years compared with an exercise program alone in middle-aged patients with meniscal symptoms. Study Design: Randomized controlled trial; Level of evidence, 1. Methods: Of 179 eligible patients, aged 45 to 64 years, 150 were randomized to (1) a 3-month exercise program (nonsurgery group) or (2) the same as group 1 plus knee arthroscopic surgery within 4 weeks (surgery group). The primary outcome was the change in the Knee Injury and Osteoarthritis Outcome Score (KOOS) subscore of pain between baseline and the 3-year follow-up. Results from the 1-year follow-up have been published previously. Results: Both treatment groups improved significantly in the KOOS pain subscore at 3 years follow-up in the intention-to-treat and as-treated analyses (P amp;lt; .001). The between-group difference for the change in the KOOS pain subscore between baseline and the 3-year follow-up was no longer statistically significant, neither in the intention-to-treat analysis (7.6 points; 95% CI, -0.6 to 15.9; P = .068) nor in the as-treated analysis (5.3 points; 95% CI, -3.1 to 13.8; P = .216). The factorial analysis of the effect of the intervention and age, onset of pain, and mechanical symptoms indicated that older patients improved more, regardless of treatment, and surgery may be more beneficial for patients without mechanical symptoms (as-treated analysis). The effect of the predictive factors on the KOOS pain subscore was uncertain because of the small sample size in the subgroup analyses. Conclusion: The benefit of knee arthroscopic surgery, seen at 1 year in middle-aged patients with meniscal symptoms, was diminished at 3 years and was no longer statistically significant.
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| 22. |
- Magnusson, Henrik, 1977-, et al.
(författare)
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Sustainable effect of individualised sun protection advice on sun protection behaviour : a 10-year follow-up of a randomised controlled study in primary care.
- 2019
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Ingår i: BJGP open. - London, United Kingdom : Royal College of General Practitioners. - 2398-3795. ; 3:3
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: In the light of increasing skin cancer incidences worldwide, preventive measures to promote sun protection in individuals with risky sun habits have continued relevance and importance.AIM: To report the long-term effect of individualised sun protection advice given in primary health care (PHC), on sun habits and sun protection behaviour.DESIGN & SETTING: In 2005, 309 PHC patients were enrolled in a randomised controlled study performed in a Swedish PHC setting.METHOD: At baseline, the study participants completed a Likert scale-based questionnaire, mapping sun habits, propensity to increase sun protection, and attitudes towards sun exposure, followed by randomisation into three intervention groups, all receiving individualised sun protection advice: in Group 1 (n = 116) by means of a letter, and in Group 2 (n = 97) and 3 (n = 96) communicated personally by a GP. In Group 3, participants also underwent a skin ultraviolet-sensitivity phototest, with adjusted sun protection advice based on the result. A repeated questionnaire was administered after 3 and 10 years.RESULTS: Statistically significant declines were observed in all groups for sun exposure mean scores over time. When using a cumulative score, according to the Sun Exposure and Protection Index (SEPI), significantly greater decrease in SEPI mean score was observed in Groups 2 and 3 (GP), compared to Group 1 (letter); P<0.01. The addition of a phototest did not enhance the effect of the intervention.CONCLUSION: Individualised sun protection advice mediated verbally by the GP can lead to sustained improvement of sun protective behaviour.
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| 23. |
- Magnusson, Martin, 1977-, et al.
(författare)
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Appearance-based loop detection from 3D laser data using the normal distributions transform
- 2009
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Ingår i: IEEE International Conference on Robotics and Automation 2009 (ICRA '09). - : IEEE conference proceedings. - 9781424427888 - 9781424427895 ; , s. 23-28
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We propose a new approach to appearance based loop detection from metric 3D maps, exploiting the NDT surface representation. Locations are described with feature histograms based on surface orientation and smoothness, and loop closure can be detected by matching feature histograms. We also present a quantitative performance evaluation using two realworld data sets, showing that the proposed method works well in different environments.© 2009 IEEE.
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| 24. |
- Magnusson, Martin, et al.
(författare)
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Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transform
- 2009
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Ingår i: Journal of Field Robotics. - : Wiley-Blackwell. - 1556-4959 .- 1556-4967. ; 26:11-12, s. 892-914
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Tidskriftsartikel (refereegranskat)abstract
- We propose a new approach to appearance-based loop detection for mobile robots, usingthree-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneouslocalization and mapping (SLAM) domain, and, because it can be seen as theproblem of recognizing previously visited places, it is an example of the data associationproblem. Without a flat-floor assumption, two-dimensional laser-based approaches arebound to fail in many cases. Two of the problems with 3D approaches that we address inthis paper are how to handle the greatly increased amount of data and how to efficientlyobtain invariance to 3D rotations.We present a compact representation of 3D point cloudsthat is still discriminative enough to detect loop closures without false positives (i.e.,detecting loop closure where there is none). A low false-positive rate is very important becausewrong data association could have disastrous consequences in a SLAM algorithm.Our approach uses only the appearance of 3D point clouds to detect loops and requires nopose information. We exploit the normal distributions transform surface representationto create feature histograms based on surface orientation and smoothness. The surfaceshape histograms compress the input data by two to three orders of magnitude. Becauseof the high compression rate, the histograms can be matched efficiently to compare theappearance of two scans. Rotation invariance is achieved by aligning scans with respectto dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determinethe threshold that separates scans at loop closures from nonoverlapping ones.Wediscuss the problem of determining ground truth in the context of loop detection and thedifficulties in comparing the results of the few available methods based on range information.Furthermore, we present quantitative performance evaluations using three realworlddata sets, one of which is highly self-similar, showing that the proposed methodachieves high recall rates (percentage of correctly identified loop closures) at low falsepositiverates in environments with different characteristics.
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| 25. |
- Moraes Holst, Luiza, et al.
(författare)
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Downregulated Mucosal Autophagy, Alpha Kinase-1 and IL-17 Signaling Pathways in Active and Quiescent Ulcerative Colitis
- 2022
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Ingår i: Clinical and Experimental Gastroenterology. - : DOVE MEDICAL PRESS LTD. - 1178-7023. ; 15, s. 129-144
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Tidskriftsartikel (refereegranskat)abstract
- Background: Improved mucosal immune profiling in active and quiescent colonic inflammatory bowel disease (IBD) is needed to develop therapeutic options for treating and preventing flares. This study therefore aimed to provide a comprehensive mucosal characterization with emphasis on immunological host response of patients with active ulcerative colitis (UC active), UC during remission (UC remission) and active colonic Crohn's disease (CD active).Methods: Colonic biopsies from 47 study subjects were collected for gene expression and pathway analyses using the NanoString host-response panel, including 776 genes and 56 immune-related pathways.Results: The majority of mucosal gene expression and signaling pathway scores were increased in active IBD (n=27) compared to healthy subjects (n=10). However, both active IBD and UC remission (n=10) demonstrated decreased gene expression and signaling pathway scores related to autophagy, alpha kinase-1 and IL-17 signaling pathways compared to healthy subjects. Further, UC remission was characterized by decreased scores of several signaling pathways linked to homeostasis along with increased mononuclear cell migration pathway score as compared to healthy subjects. No major differences in the colonic mucosal gene expression between CD active (n=7) and UC (n=20) active were observed.Conclusion: This study indicates that autophagy, alpha kinase-1 and IL-17 signaling pathways are persistently downregulated in UC irrespective of disease activity. Further, UC patients in remission present a unique mucosal environment, potentially preventing patients from reaching and sustaining true homeostasis. These findings may enable better comprehension of the remitting and relapsing pattern of colonic IBD and guide future treatment and prevention of flares.
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| 26. |
- Prentice, H. A., et al.
(författare)
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Patient demographic and surgical characteristics in anterior cruciate ligament reconstruction: a description of registries from six countries
- 2018
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Ingår i: British Journal of Sports Medicine. - : BMJ. - 0306-3674 .- 1473-0480. ; 52:11
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Tidskriftsartikel (refereegranskat)abstract
- Objective Findings from individual anterior cruciate ligament reconstruction (ACLR) registry studies are impactful, but how various registries from different countries compare with different patient populations and surgical techniques has not been described. We sought to describe six ACLR registry cohorts to understand variation across countries. Methods Five European registries and one US registry participated. For each registry, all primary ACLR registered between registry establishment through 31December 2014 were identified. Descriptive statistics included frequencies, proportions, medians and IQRs. Revision incidence rates following primary ACLR were computed. Results 101 125 ACLR were included: 21820 in Denmark, 300 in Luxembourg, 17556 in Norway, 30422 in Sweden, 2972 in the UK and 28055 in the US. In all six cohorts, males (range: 56.8%-72.4%) and soccer injuries (range: 14.1%-42.3%) were most common. European countries mostly used autografts (range: 93.7%-99.7%); allograft was most common in the US (39.9%). Interference screw was the most frequent femoral fixation in Luxembourg and the US (84.8% and 42.9%), and suspensory fixation was more frequent in the other countries (range: 43.9%-75.5%). Interference was the most frequent tibial fixation type in all six cohorts (range: 64.8%-98.2%). Three-year cumulative revision probabilities ranged from 2.8% to 3.7%. Conclusions Similarities in patient demographics and injury activity were observed between all cohorts of ACLR. However, graft and fixation choices differed. Revision rates were low. This work, including >100 000 ACLR, is the most comprehensive international description of contemporary practice to date.
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| 27. |
- Schröder, Karin, 1966-, et al.
(författare)
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Effectiveness and Quality of Implementing a Best Practice Model of Care for Low Back Pain (BetterBack) Compared with Routine Care in Physiotherapy : A Hybrid Type 2 Trial
- 2021
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Ingår i: Journal of Clinical Medicine. - : MDPI. - 2077-0383. ; 10:6, s. 1230-
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Tidskriftsartikel (refereegranskat)abstract
- Low back pain (LBP) occurs in all ages and first-line treatment by physiotherapists is common. The main aim of the current study was to evaluate the effectiveness of implementing a best practice model of care for LBP (intervention group—BetterBackJ MoC) compared to routine physiotherapy care (control group) regarding longitudinal patient reported outcomes. The BetterBackJ MoC contains clinical guideline recommendations and support tools to facilitate clinician adherence to guidelines. A secondary exploratory aim was to compare patient outcomes based on the fidelity of fulfilling a clinical practice quality index regarding physiotherapist care. A stepped cluster randomized design nested patients with LBP in the three clusters which were allocated to control (n = 203) or intervention (n = 264). Patient reported measures were collected at baseline, 3, 6 and 12 months and analyzed with mixed model regression. The primary outcome was between-group changes from baseline to 3 months for pain intensity and disability. Implementation of the BetterBackJ MoC did not show any between-group differences in the primary outcomes compared with routine care. However, the intervention group showed significantly higher satisfaction at 3 months and clinically meaningful greater improvement in LBP illness perception at 3 months and quality of life at 3 and 6 months but not in patient enablement and global impression of change compared with the control group. Physiotherapists’ care that adhered to all clinical practice quality indices resulted in an improvement of most patient reported outcomes with a clinically meaningful greater improved LBP illness perception at 3 month and quality of life at 3 and 6 months, significantly greater improvement in LBP illness perception, pain and satisfaction at 3 and 6 months and significantly better enablement at all time points as well as better global improvement outcomes at 3 months compared with non-adherent care. This highlights the importance of clinical guideline based primary care for improving patient reported LBP outcomes.
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