Ústav inteligentních systémů

Browse

Recent Submissions

Now showing 1 - 5 of 9
  • Thumbnail Image
    Item
    Energy Efficiency of a Wheeled Bio-Inspired Hexapod Walking Robot in Sloping Terrain
    (MDPI, 2023-05-31) Žák, Marek; Rozman, Jaroslav; Zbořil, František
    Multi-legged robots, such as hexapods, have great potential to navigate challenging terrain. However, their design and control are usually much more complex and energy-demanding compared to wheeled robots. This paper presents a wheeled six-legged robot with five degrees of freedom, that is able to move on a flat surface using wheels and switch to gait in rugged terrain, which reduces energy consumption. The novel joint configuration mimics the structure of insect limbs and allows our robot to overcome difficult terrain. The wheels reduce energy consumption when moving on flat terrain and the trochanter joint reduces energy consumption when moving on slopes, extending the operating time and range of the robot. The results of experiments on sloping terrain are presented. It was confirmed that the use of the trochanter joint can lead to a reduction in energy consumption when moving in sloping terrain.
  • Thumbnail Image
    Item
    PredatorHP Revamped (Not Only) for Interval-Sized Memory Regions and Memory Reallocation (Competition Contribution)
    (Springer International Publishing, 2020-02-26) Šoková, Veronika; Peringer, Petr; Vojnar, Tomáš
    This paper concentrates on improvements of the PredatorHP shape analyzer in the past two years, including, e.g., improved handling of interval-sized memory regions or new support of memory reallocation. The paper characterizes PredatorHP's participation in SV-COMP 2020, pointing out its strengths and weakness and the way they were influenced by the latest changes in the tool.
  • Thumbnail Image
    Item
    Fast Matching of Regular Patterns with Synchronizing Counting
    (Springer Verlag, 2023-04-21) Holík, Lukáš; Síč, Juraj; Holíková, Lenka; Vojnar, Tomáš
    Fast matching of regular expressions with bounded repetition, aka counting, such as (){,}, i.e., matching linear in the length of the text and independent of the repetition bounds, has been an open problem for at least two decades. We show that, for a wide class of regular expressions with counting, which we call synchronizing, fast matching is possible. We empirically show that the class covers nearly all counting used in usual applications of regex matching. This complexity result is based on an improvement and analysis of a recent matching algorithm that compiles regexes to deterministic counting-set automata (automata with registers that hold sets of numbers).
  • Thumbnail Image
    Item
    Operational Semantic of an AgentSpeak(L) Interpreter using Late Bindings
    (SciTePress - Science and Technology Publications, 2023-02-01) Vídeňský, František; Zbořil, František; Kočí, Radek; Zbořil, František
    Although BDI systems have long been studied in the field of agent-based programming, there are still problems open for research. One problem is that some parts of systems are non-deterministic in the original specification. However, finding a suitable deterministic method can lead to improved rationality of an agent's behaviour. In our previous work, we introduced late binding into the interpretation of AgentSpeak(L) language. The main benefit of this approach is that the interpreter chooses substitutions only when needed, thus avoiding unnecessary and incorrect substitution selection. In this paper, we present a formal operational semantics for an interpreter using late binding variables. A well-specified operational semantics is necessary for the implementation of such an interpreter and its further development
  • Thumbnail Image
    Item
    Approximate Reduction of Finite Automata for High-Speed Network Intrusion Detection
    (Springer Verlag, 2018-02-23) Češka, Milan; Havlena, Vojtěch; Holík, Lukáš; Lengál, Ondřej; Vojnar, Tomáš
    We consider the problem of approximate reduction of non-deterministic automata that appear in hardware-accelerated network intrusion detection systems (NIDSes). We define an error distance of a reduced automaton from the original one as the probability of packets being incorrectly classified by the reduced automaton (wrt the probabilistic distribution of packets in the network traffic). We use this notion to design an approximate reduction procedure that achieves a great size reduction (much beyond the state-of-the-art language preserving techniques) with a controlled and small error. We have implemented our approach and evaluated it on use cases from Snort , a popular NIDS. Our results provide experimental evidence that the method can be highly efficient in practice, allowing NIDSes to follow the rapid growth in the speed of networks.