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KRRF: Kinodynamic Rapidly-exploring Random Forest algorithm for multi-goal motion planning

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00377429" target="_blank" >RIV/68407700:21230/24:00377429 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/LRA.2024.3478570" target="_blank" >https://doi.org/10.1109/LRA.2024.3478570</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/LRA.2024.3478570" target="_blank" >10.1109/LRA.2024.3478570</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    KRRF: Kinodynamic Rapidly-exploring Random Forest algorithm for multi-goal motion planning

  • Original language description

    The problem of kinodynamic multi-goal motion planning is to find a trajectory over multiple target locations with an apriori unknown sequence of visits. The objective is to minimize the cost of the trajectory planned in a cluttered environment for a robot with a kinodynamic motion model. This problem has yet to be efficiently solved as it combines two NP-hard problems, the Traveling Salesman Problem (TSP) and the kinodynamic motion planning problem. We propose a novel approximate method called Kinodynamic Rapidly-exploring Ran- dom Forest (KRRF) to find a collision-free multi-goal trajectory that satisfies the motion constraints of the robot. KRRF simul- taneously grows kinodynamic trees from all targets towards all other targets while using the other trees as a heuristic to boost the growth. Once the target-to-target trajectories are planned, their cost is used to solve the TSP to find the sequence of targets. The final multi-goal trajectory satisfying kinodynamic constraints is planned by guiding the RRT-based planner along the target-to- target trajectories in the TSP sequence. Compared with existing approaches, KRRF provides shorter target-to-target trajectories and final multi-goal trajectories with 1.1 - 2 times lower costs while being computationally faster in most test cases. The method will be published as an open-source library.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Robotics and Automation Letters

  • ISSN

    2377-3766

  • e-ISSN

    2377-3766

  • Volume of the periodical

    9

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    8

  • Pages from-to

    10724-10731

  • UT code for WoS article

    001466141700001

  • EID of the result in the Scopus database

    2-s2.0-85207037891