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.

The Power of Bellicose Rhetoric

Abstract: The use of metaphors often characterizes contemporary public discourses on various issues. By the same token, metaphors have been used extensively in the discourse on the COVID-19 pandemic. This paper examines the WAR metaphor as a framing and rhetorical device with distinct persuasive potency within the Croatian sociocultural context. The analysis shows that militaristic metaphors were omnipresent in the Croatian public discourse at the beginning of the pandemic. Their dual role, explanatory and persuasive, was instrumental in convincing the public to understand the pandemic and accept the restrictive mandates put in place.

First record of fossil fish (Enchodontoidei, Actinopterygii) in the Struganik quarry in Western Serbia

Abstract: This paper presents the first Upper Cretaceous remains of fish in Serbia, discovered near the village of Struganik. This is also the first described find of Mesozoic fish in Serbia. A stone slab with visible contours of an almost complete fish, with a total body length of about 20 cm, was excavated from the Struganik quarry. Most bones are preserved as imprints. The number of vertebrae, the shape and position of the cranial bones, the type of teeth, and the position of the first dorsal fin all indicate that the studied specimen belongs to the genus Enchodus known from several Upper Cretaceous localities in the Tethys domain.

Praćenje mobilnih robota korištenjem računalnog vida

Abstract: In this paper a global vision scheme applied to a fast dynamic game robot soccer is presented. The process of robots positions and orientations estimation is divided into two steps. In the first step, the Bayer format image is acquired from camera, then the RGB image is interpolated and pixels are classified into a finite number of classes. At the same time, a segmentation algorithm is used to find corresponding regions belonging to one of the classes. In the second step, all the regions are examined. Selection of the ones that are parts of the observed object is made by means of simple logic procedures. A data filtering is used to improve identified noisy data. The novelty is focused on the optimization of the image acquisition algorithm as well as the processing time needed to finish the estimation of possible object positions.

Hesiod’s Religious Norms in Context: On Works & Days 724–760

Abstract: We analyze the section from Hesiod’s Works and Days (724–760) that equips the farmer with the expertise necessary to facilitate the household’s harmonious relationship with the gods. We propose that this section with its tabular ordinances represents the earliest collection of Greek religious norms, and we contextualize it both within the structure of the W&D and within the wider framework of Greek religion. The section is carefully developed and purposefully placed towards the end of the poem, with an eye to symmetry and rhythm: Hesiod distributes divinely sanctioned social norms alongside religious norms in three distinct sections of the poem, providing ever more specific cautionary advice in the form of ordinances and injunctions. The passage 724–760 is also artfully structured and divided into ἀπό and ἐπί sections. By drawing attention to overlaps of the Hesiodic material and later inscriptional ritual norms, we demonstrate that they share common linguistic and thematic features. We also demonstrate that well-informed readers such as Plato, Plutarch, and Proclus repeatedly interpreted Hesiod’s norms in the light of their own religious experience.

Localisation of Mobile Robots by Tracking Identical Colour Markers

Abstract: A reliable tracking algorithm of multiple mobile robots is addressed in this paper. A central vision system is used to find robots in the environment where robots are marked with identical colour patches mounted on each of them. To distinguish robots a robust tracking algorithm considering robot kinematics is implemented. However, mistakes such as swaps of robots identifications can happen and are unrecoverable, resulting in wrong control. Therefore swaps of robots identifications and initialisation problems are tackled using a supervision algorithm which is based on the correlation of command, and estimated robots velocities.

I and i

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 …

Coverage control for mobile sensing networks

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.

Adaptive Control

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.

A Review of Motion Planning Techniques for Automated Vehicles

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.

SeqSLAM : visual route-based navigation for sunny summer days and stormy winter nights

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%.