Publications

SELECTED PUBLICATIONS

Conferences, and Technical Reports (Preprints):

  • “Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles; Yuezhan Tao, Eran Iceland, Beiming Li, Elchanan Zwecher, Uri Heinemann, Avraham Cohen, Amir Avni, Oren Gal, Ariel Barel, Vijay Kumar arXiv:2309.06986 [cs.RO]  (accepted to ICRA-2024)
  • Multi-Agent Distributed and Decentralized Geometric Task Allocation”; Michael Amir, Yigal Koifman, Yakov Bloch, Ariel Barel, Alfred M. Bruckstein arXiv:2210.05552 [cs.MA]
  • “Integrating Deep Reinforcement and Supervised Learning to Expedite Indoor Mapping”; Elchanan Zwecher, Eran Iceland, Sean R. Levy, Shmuel Y. Hayoun, Oren Gal, Ariel Barel arXiv:2109.08490 [cs.LG]
  • “Deep-Learning-Aided Path Planning and Map Construction for Expediting Indoor Mapping”; Elchanan Zwecher, Eran Iceland, Shmuel Y. Hayoun, Ahavatya Revivo, Sean R. Levy, Ariel Barel (pending publication, 2020) arXiv:2011.02043 [cs.LG]
  • “COME TOGETHER: Multi-Agent Geometric Consensus (Gathering, Rendezvous, Clustering, Aggregation)”; Ariel Barel, Rotem Manor, Alfred M. Bruckstein (Tech report, Technion CIS, 2016) arXiv:1902.01455 [cs.MA]
  • “Probabilistic Gathering of Agents with Simple Sensors”; Ariel Barel, Rotem Manor, Alfred M. Bruckstein (Poster Presentation – Conference on Collective Behavior, SMR 3201, Trieste 2018) arXiv:1902.00294 [cs.MA]
  • “Local Interactions for Cohesive Flexible Swarms”; Rotem Manor, Ariel Barel, Alfred M. Bruckstein (IRC 2020 XIV. Conference, Tokyo 2019) arXiv:1903.09259 [cs.MA]

Journals, Conferences, and Proceedings:

  • “Reinforcement Learning Based Decentralized Weapon-Target Assignment and Guidance”; Merkulov, Gleb, Eran Iceland, Shay Michaeli, Yosef Riechkind, Oren Gal, Ariel Barel, and Tal Shima. In AIAA SCITECH 2024 Forum, p. 0125. 2024. https://arc.aiaa.org/doi/abs/10.2514/6.2024-0125
  • “Multi-Agent Distributed and Decentralized Geometric Task Allocation; Michael Amir, Yigal Koifman, Yakov Bloch, Ariel Barel, Alfred M. Bruckstein, 2023 62nd IEEE Conference on Decision and Control (CDC), Singapore, Singapore, 2023, pp. 8355-8362, doi: 10.1109/CDC49753.2023.10383740.
  • “Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force”; Sahar, Y., Wagner, M., Barel, A., & Shoval, S. (2023). Paper presented at the 23rd National Industrial Engineering & Management Conference IE&M 2023, Ariel.
  • “Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip Force”; Yotam Sahar, Michael Wagner, Ariel Barel, and Shraga Shoval (2022, November). In Sensors – Multidisciplinary Digital Publishing Institute (MDPI). https://www.mdpi.com/1424-8220/22/21/8368
  • “Integrating Deep Reinforcement and Supervised Learning to Expedite Indoor Mapping”; Zwecher, E., Iceland, E., Levy, S. R., Hayoun, S. Y., Gal, O., & Barel, A. In 2022 International Conference on Robotics and Automation (ICRA), Philadelphia, 2022 (pp. 10542-10548). IEEE. https://ieeexplore.ieee.org/abstract/document/9811861
  • “Probabilistic Gathering of Agents with Simple Sensors”; Ariel Barel, Thomas Dagès, Rotem Manor, Alfred M. Bruckstein, SIAM Journal on Applied Mathematics, 2021, 81.2: 620-640. https://doi.org/10.1137/20M133333X
  • “On Steering Swarms”; Ariel Barel, Rotem Manor, Alfred M. Bruckstein. Swarm Intelligence ANTS, Rome 2018. Lecture Notes in Computer Science, vol 11172. Springer, Cham https://doi.org/10.1007/978-3-030-00533-7_35

Theses