Výsledky vyhľadávania - "Sampling-based algorithms"

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  1. 1

    KDF: Kinodynamic Motion Planning via Geometric Sampling-Based Algorithms and Funnel Control Autor Verginis, Christos K., Dimarogonas, Dimos V., Kavraki, Lydia E.

    ISSN: 1552-3098, 1941-0468, 1941-0468
    Vydavateľské údaje: New York IEEE 01.04.2023
    Vydané v IEEE transactions on robotics (01.04.2023)
    “… The considered systems evolve subject to complex, nonlinear, and uncertain dynamics (also known as differential constraints…”
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    Journal Article
  2. 2

    A review of recent trend in motion planning of industrial robots Autor Tamizi, Mehran Ghafarian, Yaghoubi, Marjan, Najjaran, Homayoun

    ISSN: 2366-5971, 2366-598X
    Vydavateľské údaje: Singapore Springer Nature Singapore 01.06.2023
    “…Motion planning is an integral part of each robotic system. It is critical to develop an effective motion in order to achieve a successful performance. The…”
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    Journal Article
  3. 3

    KDF: Kinodynamic Motion Planning via Geometric Sampling-based Algorithms and Funnel Control Autor Verginis, Christos K, Dimarogonas, Dimos V, Kavraki, Lydia E

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 24.04.2021
    Vydané v arXiv.org (24.04.2021)
    “… The considered systems evolve subject to complex, nonlinear, and uncertain dynamics (aka differential constraints…”
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    Paper
  4. 4

    A martingale approach and time-consistent sampling-based algorithms for risk management in stochastic optimal control Autor Vu Anh Huynh, Kogan, Leonid, Frazzoli, Emilio

    ISBN: 9781479977468, 1479977462
    ISSN: 0191-2216
    Vydavateľské údaje: IEEE 01.12.2014
    “…In this paper, we consider a class of stochastic optimal control problems with risk constraints that are expressed as bounded probabilities of failure for…”
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    Konferenčný príspevok..
  5. 5

    A Martingale Approach and Time-Consistent Sampling-based Algorithms for Risk Management in Stochastic Optimal Control Autor Huynh, Vu Anh, Kogan, Leonid, Frazzoli, Emilio

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 08.07.2015
    Vydané v arXiv.org (08.07.2015)
    “…In this paper, we consider a class of stochastic optimal control problems with risk constraints that are expressed as bounded probabilities of failure for…”
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    Paper
  6. 6

    Incremental sampling-based algorithm for risk-aware planning under motion uncertainty Autor Wei Liu, Ang, Marcelo H.

    ISSN: 1050-4729
    Vydavateľské údaje: IEEE 01.05.2014
    “…This paper considers the problem of motion planning for linear systems subject to Gaussian motion noise and proposes a risk-aware planning algorithm: CC-RRT*-D…”
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    Konferenčný príspevok..
  7. 7

    Voronoi Boundary Visibility for Efficient Path Planning Autor Al-Dahhan, Mohammed Rabeea Hashim, Schmidt, Klaus Werner

    ISSN: 2169-3536, 2169-3536
    Vydavateľské údaje: Piscataway IEEE 2020
    Vydané v IEEE access (2020)
    “…The subject of this paper is the computation of paths for mobile robots that navigate from a start position to a goal position in environments with static obstacles…”
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    Journal Article
  8. 8

    Motion Primitive Path Planning for Parametrically Uncertain Systems via the Koopman Operator Autor Gutow, Geordan Mihalick

    ISBN: 9798263390471
    Vydavateľské údaje: ProQuest Dissertations & Theses 01.01.2022
    “…This work considers the application of motion primitives to path planning and obstacle avoidance problems in which the system is subject to significant parametric and/or initial condition uncertainty…”
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    Dissertation
  9. 9

    A visibility-based pursuit-evasion game between two nonholonomic robots in environments with obstacles Autor Lozano, Eliezer, Becerra, Israel, Ruiz, Ubaldo, Bravo, Luis, Murrieta-Cid, Rafael

    ISSN: 0929-5593, 1573-7527
    Vydavateľské údaje: New York Springer US 01.02.2022
    Vydané v Autonomous robots (01.02.2022)
    “… To determine the players’ motion policies and their trajectories–subject to differential constraints…”
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    Journal Article
  10. 10

    Semiparametric Bayesian Analysis of Survival Data Autor Sinha, Debajyoti, Dey, Dipak K.

    ISSN: 0162-1459, 1537-274X
    Vydavateľské údaje: Alexandria, VA Taylor & Francis Group 01.09.1997
    “… Careful applications of some recently popular computational tools, including sampling-based algorithms, are used to find posterior estimates of several quantities of interest even when dealing…”
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    Journal Article
  11. 11

    Planning and control of multi-robot-object systems under temporal logic tasks and uncertain dynamics Autor Verginis, Christos K., Kantaros, Yiannis, Dimarogonas, Dimos V.

    ISSN: 0921-8890, 1872-793X, 1872-793X
    Vydavateľské údaje: Elsevier B.V 01.04.2024
    Vydané v Robotics and autonomous systems (01.04.2024)
    “… The robots and objects evolve subject to uncertain dynamics in an obstacle-cluttered environment…”
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    Journal Article
  12. 12

    Distributed Motion Coordination for Multirobot Systems Under LTL Specifications Autor Yu, Pian, Dimarogonas, Dimos V.

    ISSN: 1552-3098, 1941-0468, 1941-0468
    Vydavateľské údaje: New York IEEE 01.04.2022
    Vydané v IEEE transactions on robotics (01.04.2022)
    “… Based on the realistic assumptions that each robot is subject to both state and input constraints and can have only local view and local information, a fully distributed multirobot motion…”
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    Journal Article
  13. 13

    Modelling recall-based competing risks data with k different models Autor Panwar, M. S., Yadav, C. P.

    ISSN: 0094-9655, 1563-5163
    Vydavateľské údaje: Abingdon Taylor & Francis 03.03.2024
    “…In competing risks model, subjects are exposed to failure due to more than one cause…”
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    Journal Article
  14. 14

    Models of Approximate Inference in Vision Autor Chattoraj, Ankani

    ISBN: 9798790654435
    Vydavateľské údaje: ProQuest Dissertations & Theses 01.01.2022
    “…To develop a complete understanding of visual perception, it is important to investigate the system at all three levels proposed by Marr: computational goal of…”
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    Dissertation
  15. 15

    Sampling-based Near Time-Optimal Trajectory Generation for Pneumatic Drives Autor Hoffmann, Kathrin, Baumgart, Michaela, Kanagalingam, Gajanan, Verl, Alexander, Sawodny, Oliver

    ISSN: 2161-8089
    Vydavateľské údaje: IEEE 17.08.2025
    “… There occur nonlinear state-dependent jerk constraints because the pressure dynamics are not negligibly fast, the air mass flow through the valves is subject to pressure-dependent constraints…”
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    Konferenčný príspevok..
  16. 16

    First Order Stochastic Optimization with Oblivious Noise Autor Diakonikolas, Ilias, Karmalkar, Sushrut, Park, Jongho, Tzamos, Christos

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 04.08.2024
    Vydané v arXiv.org (04.08.2024)
    “… In our setting, in addition to random observation noise, the stochastic gradient may be subject to independent oblivious noise, which may not have bounded moments and is not necessarily centered…”
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    Paper
  17. 17

    Stealthy Terrain-Aware Multi-Agent Active Search Autor Bakshi, Nikhil Angad, Schneider, Jeff

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 17.10.2023
    Vydané v arXiv.org (17.10.2023)
    “… We present the Stealthy Terrain-Aware Reconnaissance (STAR) algorithm, a multi-objective parallelized Thompson sampling-based algorithm that relies on a strong…”
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    Paper
  18. 18

    Planning and Control of Multi-Robot-Object Systems under Temporal Logic Tasks and Uncertain Dynamics Autor Verginis, Christos K, Kantaros, Yiannis, Dimarogonas, Dimos V

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 25.04.2022
    Vydané v arXiv.org (25.04.2022)
    “… The robots and objects evolve subject to uncertain dynamics in an obstacle-cluttered environment…”
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    Paper
  19. 19

    Distributed motion coordination for multi-robot systems under LTL specifications Autor Pian Yu, Dimarogonas, Dimos V

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 16.03.2021
    Vydané v arXiv.org (16.03.2021)
    “… Based on the realistic assumptions that each robot is subject to both state and input constraints and can have only local view and local information, a fully distributed multi-robot motion…”
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    Paper
  20. 20

    Stochastic Matching with Few Queries: \((1-\varepsilon)\) Approximation Autor Behnezhad, Soheil, Derakhshan, Mahsa, Hajiaghayi, MohammadTaghi

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 27.02.2020
    Vydané v arXiv.org (27.02.2020)
    “…\). The maximum degree of \(Q\) can depend on \(p\), but not on the size of \(G\). This problem has been subject to extensive studies over the years and the approximation…”
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    Paper