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A Quantum Planner for Robot Motion

Author

Listed:
  • Antonio Chella

    (Dipartimento di Ingegneria (DID), Università degli Studi di Palermo, 90128 Palermo, Italy
    Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR), Via Ugo La Malfa 153, 90146 Palermo, Italy)

  • Salvatore Gaglio

    (Dipartimento di Ingegneria (DID), Università degli Studi di Palermo, 90128 Palermo, Italy
    Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR), Via Ugo La Malfa 153, 90146 Palermo, Italy)

  • Giovanni Pilato

    (Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR), Via Ugo La Malfa 153, 90146 Palermo, Italy)

  • Filippo Vella

    (Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR), Via Ugo La Malfa 153, 90146 Palermo, Italy)

  • Salvatore Zammuto

    (Dipartimento di Ingegneria (DID), Università degli Studi di Palermo, 90128 Palermo, Italy)

Abstract

The possibility of integrating quantum computation in a traditional system appears to be a viable route to drastically improve the performance of systems endowed with artificial intelligence. An example of such processing consists of implementing a teleo-reactive system employing quantum computing. In this work, we considered the navigation of a robot in an environment where its decisions are drawn from a quantum algorithm. In particular, the behavior of a robot is formalized through a production system. It is used to describe the world, the actions it can perform, and the conditions of the robot’s behavior. According to the production rules, the planning of the robot activities is processed in a recognize–act cycle with a quantum rule processing algorithm. Such a system aims to achieve a significant computational speed-up.

Suggested Citation

  • Antonio Chella & Salvatore Gaglio & Giovanni Pilato & Filippo Vella & Salvatore Zammuto, 2022. "A Quantum Planner for Robot Motion," Mathematics, MDPI, vol. 10(14), pages 1-29, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2475-:d:864178
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    References listed on IDEAS

    as
    1. Federico Centrone & Niraj Kumar & Eleni Diamanti & Iordanis Kerenidis, 2021. "Experimental demonstration of quantum advantage for NP verification with limited information," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    2. Maria Mannone & Valeria Seidita & Antonio Chella, 2022. "Categories, Quantum Computing, and Swarm Robotics: A Case Study," Mathematics, MDPI, vol. 10(3), pages 1-11, January.
    Full references (including those not matched with items on IDEAS)

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