1,721,362 research outputs found
Sketch maps dataset
No full textA dataset of 25 sketch-maps obtained from an [interface](aass.oru.se/Research/mro/smokebot/sketchmap-web/) in a web browser. The sketch correspond to the ground truth of KTH dataset for SLAM.
Each sketch is associated with two possible ground truth segmentatino given by two independent users.
If you use this dataset please cite this paper:
@Article{robotics8020043,
AUTHOR = {Mielle, Malcolm and Magnusson, Martin and Lilienthal, Achim J.},
TITLE = {URSIM: Unique Regions for Sketch Map Interpretation and Matching},
JOURNAL = {Robotics},
VOLUME = {8},
YEAR = {2019},
NUMBER = {2},
ARTICLE-NUMBER = {43},
URL = {https://www.mdpi.com/2218-6581/8/2/43},
ISSN = {2218-6581},
ABSTRACT = {We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human–robot interactions. While sketch maps are not metrically accurate and many details, which are deemed unnecessary, are omitted, they represent the topology of the environment well and are typically accurate at key locations. Thus, for sketch map interpretation and matching, one cannot only rely on metric information. Our matching method first finds the most distinguishable, or unique, regions of two maps. The topology of the maps, the positions of the unique regions, and the size of all regions are used to build region descriptors. Finally, a sequential graph matching algorithm uses the region descriptors to find correspondences between regions of the sketch and metric maps. Our method obtained higher accuracy than both a state-of-the-art matching method for inaccurate map matching, and our previous work on the subject. The state of the art was unable to match sketch maps while our method performed only 10% worse than a human expert.},
DOI = {10.3390/robotics8020043}
The Next Step in Robot Commissioning : Autonomous Picking and Palletizing
Get PDFSo far, autonomous order picking (commissioning) systems have not been able to meet the stringent demands regarding speed, safety, and accuracy of real-world warehouse automation, resulting in reliance on human workers. In this letter, we target the next step in autonomous robot commissioning: automatizing the currently manual order picking procedure. To this end, we investigate the use case of autonomous picking and palletizing with a dedicated research platform and discuss lessons learned during testing in simplified warehouse settings. The main theoretical contribution is a novel grasp representation scheme which allows for redundancy in the gripper pose placement. This redundancy is exploited by a local, prioritized kinematic controller which generates reactive manipulator motions on-the-fly. We validated our grasping approach by means of a large set of experiments, which yielded an average grasp acquisition time of 23.5 s at a success rate of 94.7%. Our system is able to autonomously carry out simple order picking tasks in a humansafe manner, and as such serves as an initial step toward future commercial-scale in-house logistics automation solutions
Exploration and localization of a gas source with MOX gas sensors on a mobile robot-A Gaussian regression bout amplitude approach
No full textMobile robot olfaction systems combine gas sensors with mobility provided by robots. They relief humans of dull, dirty and dangerous tasks in applications such as search & rescue or environmental monitoring. We address gas source localization and especially the problem of minimizing exploration time of the robot, which is a key issue due to energy constraints. We propose an active search approach for robots equipped with MOX gas sensors and an anemometer, given an occupancy map. Events of rapid change in the MOX sensor signal ('bouts') are used to estimate the distance to a gas source. The wind direction guides a Gaussian regression, which interpolates distance estimates. The contributions of this paper are two-fold. First, we extend previous work on gas source distance estimation with MOX sensors and propose a modification to cope better with turbulent conditions. Second, we introduce a novel active search gas source localization algorithm and validate it in a real-world environment
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Superpixels and their Application for Visual Place Recognition in Changing Environments
Get PDFSuperpixels are the results of an image oversegmentation. They are an established intermediate level image representation and used for various applications including object detection, 3d reconstruction and semantic segmentation. While there are various approaches to create such segmentations, there is a lack of knowledge about their properties. In particular, there are contradicting results published in the literature. This thesis identifies segmentation quality, stability, compactness and runtime to be important properties of superpixel segmentation algorithms. While for some of these properties there are established evaluation methodologies available, this is not the case for segmentation stability and compactness. Therefore, this thesis presents two novel metrics for their evaluation based on ground truth optical flow. These two metrics are used together with other novel and existing measures to create a standardized benchmark for superpixel algorithms. This benchmark is used for extensive comparison of available algorithms. The evaluation results motivate two novel segmentation algorithms that better balance trade-offs of existing algorithms: The proposed Preemptive SLIC algorithm incorporates a local preemption criterion in the established SLIC algorithm and saves about 80 % of the runtime. The proposed Compact Watershed algorithm combines Seeded Watershed segmentation with compactness constraints to create regularly shaped, compact superpixels at the even higher speed of the plain watershed transformation.
Operating autonomous systems over the course of days, weeks or months, based on visual navigation, requires repeated recognition of places despite severe appearance changes as they are for example induced by illumination changes, day-night cycles, changing weather or seasons - a severe problem for existing methods. Therefore, the second part of this thesis presents two novel approaches that incorporate superpixel segmentations in place recognition in changing environments. The first novel approach is the learning of systematic appearance changes. Instead of matching images between, for example, summer and winter directly, an additional prediction step is proposed. Based on superpixel vocabularies, a predicted image is generated that shows, how the summer scene could look like in winter or vice versa. The presented results show that, if certain assumptions on the appearance changes and the available training data are met, existing holistic place recognition approaches can benefit from this additional prediction step. Holistic approaches to place recognition are known to fail in presence of viewpoint changes. Therefore, this thesis presents a new place recognition system based on local landmarks and Star-Hough. Star-Hough is a novel approach to incorporate the spatial arrangement of local image features in the computation of image similarities. It is based on star graph models and Hough voting and particularly suited for local features with low spatial precision and high outlier rates as they are expected in the presence of appearance changes. The novel landmarks are a combination of local region detectors and descriptors based on convolutional neural networks. This thesis presents and evaluates several new approaches to incorporate superpixel segmentations in local region detection. While the proposed system can be used with different types of local regions, in particular the combination with regions obtained from the novel multiscale superpixel grid shows to perform superior to the state of the art methods - a promising basis for practical applications
- …
