Казанский (Приволжский) федеральный университет, КФУ
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PRIORITIZING TASKS WITHIN A ROBOTIC TRANSPORTATION SYSTEM FOR A SMART HOSPITAL ENVIRONMENT
Форма представленияСтатьи в зарубежных журналах и сборниках
Год публикации2021
Языканглийский
  • Лавренов Роман Олегович, автор
  • Магид Евгений Аркадьевич, автор
  • Цой Татьяна Григорьевна, автор
  • Библиографическое описание на языке оригинала Safin R, Lavrenov R, Tsoy T, Prioritizing Tasks Within a Robotic Transportation System for a Smart Hospital Environment//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2021. - Vol.12998 LNAI, Is.. - P.182-193.
    Аннотация This paper describes a design and an implementation of a small-scale robotic transportation system, which operates in a smart hospital environment. Within a proposed framework unmanned ground vehicles (UGV) perform transportation tasks between multiple stations that are located in different rooms. The UGVs navigate in the environment with moving objects in accordance with basic traffic rules, which consider priorities of particular tasks of each UGV. UGVs' behavior is defined by a state machine and transitions between these states, which allows to make the robots' behavior more predictable and controllable. Virtual experiments were carried out in a simulation of an entire floor of a small-size hospital building using the Gazebo simulator. The experiments confirmed that using various task priorities shorten a path length of robots with high priorities and thus reduce their task execution time.
    Ключевые слова Smart hospital, UGV, Robot navigation, Path planning, Task-based robotic system, Service robots, Leading edge healthcare
    Название журнала Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116450553&doi=10.1007%2f978-3-030-87725-5_16&partnerID=40&md5=fff142566f37f54a9d807ce2bda72f4b
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