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Ivan Petrović

Bio: Ivan Petrović is an academic researcher from University of Zagreb. The author has contributed to research in topics: Mobile robot & Motion planning. The author has an hindex of 28, co-authored 248 publications receiving 3002 citations. Previous affiliations of Ivan Petrović include Czech Technical University in Prague & University of Toronto.


Papers
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Proceedings ArticleDOI
01 Aug 2021
TL;DR: In this article, a stereo visual odometry method for event cameras based on feature detection and matching with careful feature management is proposed, while pose estimation is done by feature reprojection error minimization.
Abstract: Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than standard cameras in environments of challenging illumination and in high-speed scenarios, thus developing odometry algorithms based solely on event cameras offers exciting new possibilities for autonomous systems and robots. In this paper, we propose a novel stereo visual odometry method for event cameras based on feature detection and matching with careful feature management, while pose estimation is done by feature reprojection error minimization. We evaluate the performance of the proposed method on two publicly available datasets: MVSEC sequences captured by an indoor flying drone and DSEC outdoor driving sequences. MVSEC offers accurate ground truth from motion capture, while for DSEC, which does not offer ground truth, in order to obtain a reference trajectory on the standard camera frames we used our SOFT visual odometry, one of the highest ranking algorithms on the KITTI scoreboards. We compared our method to the ESVO method, which is the first and still the only stereo event odometry method, showing on par performance on both MVSEC and DSEC sequences. Furthermore, two important advantages of our method over ESVO are that it adapts tracking frequency to the asynchronous event rate and does not require initialization.

1 citations

Journal Article
TL;DR: In this paper, a laboratory model for experimental investigations of the rubber-asphalt sliding pair has been designed to better understand the dynamic behavior of the friction force in the contact patch between the car tire and the road.
Abstract: A laboratory model for experimental investigations of the rubber-asphalt sliding pair has been designed to better understand the dynamic behavior of the friction force in the contact patch between the car tire and the road. Its design is described and some experimental results are given. These results confirm that in order to describe friction force in contact between the car tire and the road it is essential to use a dynamic friction model . Moreover, they indicate that the existing dynamic friction models might be physically incorrect in regards to the change of friction coefficient for an asperity bristle passing through the contact surface.

1 citations

Book ChapterDOI
22 Nov 2017-Robot
TL;DR: A Cooperative Cloud SLAM on Matrix Lie Groups is presented, which enables efficient and accurate execution of simultaneous localization and environment mapping, while relying on integration of data from multiple agents.
Abstract: In this paper we present a Cooperative Cloud SLAM on Matrix Lie Groups (\(\text {C}^2\text {LEARS}\)), which enables efficient and accurate execution of simultaneous localization and environment mapping, while relying on integration of data from multiple agents. Such fused information is then used to increase mapping accuracy of every agent itself. In particular, the agents perform only computationally simpler tasks including local map building and single trajectory optimization. At the same time, the efficient execution is ensured by performing complex tasks of global map building and multiple trajectory optimization on a standalone cloud server. The front-end part of \(\text {C}^2\text {LEARS}\) is based on a planar SLAM solution, while the back-end is implemented using the exactly sparse delayed state filter on matrix Lie groups (LG-ESDSF). The main advantages of the front-end employing planar surfaces to represent the environment are significantly lower memory requirements and possibility of the efficient map exchange between agents. The back-end relying on the LG-ESDSF allows for efficient trajectory optimization utilizing sparsity of the information form and exploiting higher accuracy supported by representing the state on Lie groups. We demonstrate \(\text {C}^2\text {LEARS}\) on a real-world experiment recorded on the ground floor of our faculty building.

1 citations

Journal ArticleDOI
24 Dec 2022-St open
TL;DR: In this article , the influence of spoken language and sports an-nouncer talk (SAT) on the register of the English language using examples from the coverage of UEFA Euro 2020 was explored.
Abstract: Aim: To present and analyze features of live text commen-tary (LTC) as a recent register of the English language using examples from the coverage of UEFA Euro 2020. The paper explores the influence of spoken language and sports an-nouncer talk (SAT) on the register. It focuses on the differ-ences and similarities between LTC and SAT and presents an overview of features unique to LTC.Methods: LTC was examined as a text variety following Chovanec’s (2018) analysis and using the register perspec-tive proposed by Biber and Conrad (2009). Examples from fourteen LTCs reporting on the UEFA Euro 2020 competition held in June/July 2021 were analyzed, including their typ-ical situational and linguistic characteristics and some of their functions.Results: LTC is a hybrid register that exemplifies today’s convergence of different media. LTCs take the context of production from live blogs, while their language is main-ly reminiscent of SAT, including tense usage and adoption of certain forms. Spoken language, in general, is also an in-fluence, especially on the syntactic and grammatical levels. Distinct LTC features include the internal structure, icons, and interactiveness of the text. The analyzed commentaries feature clearly outlined sections (e.g., opening and closing posts) that serve specific discursive purposes. Icons have a particular function in LTC; their meaning is well-estab-lished, and they sometimes function as utterances. Another remarkable characteristic is the intertextuality derived from text contributions provided by various spectators of the sports event, including fans. This interaction is, at times, simulated. Conclusion: The paper confirmed LTC as a hybrid format with avenues for further hybridization. In LTC, we see an intertwining of different elements, which, taken together, produce a new whole in a process typical of the conver-gence seen in the media today. The most innovative aspects of LTC, the intertextuality, interactiveness, and co-produc-tion of a text, are limited.

1 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Posted Content
TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

2,198 citations

Journal Article
TL;DR: In this paper, two major figures in adaptive control provide a wealth of material for researchers, practitioners, and students to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs.
Abstract: This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

1,814 citations

Journal ArticleDOI
TL;DR: A review of motion planning techniques implemented in the intelligent vehicles literature, with a description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is presented.
Abstract: Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

1,162 citations

Journal Article
TL;DR: A new approach to visual navigation under changing conditions dubbed SeqSLAM, which removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images.
Abstract: Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

686 citations