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Real-time cellular-level imaging and medical treatment with a swarm of wireless multifunctional robots

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Abstract

This is a short communication where we present a theoretical model of a swarm of wireless robots that can be used for cellular-level diagnosis and treatment of a variety of life threatening diseases such as cancer. Based on this model, we illustrate a distributed position and orientation tracking algorithm that constructs digitized images from a set of pixels transmitted by the robots of the swarm model that are in motion. Simulation results are also presented.

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Acknowledgements

The authors would like to thank their colleagues Divya Sai Chadalavada (currently at Intel), Parth Joshi (currently at Qualcomm), Ooha Parvathareddy (previously at USC), Ujwala Parvathareddy (previously at USC), and Alekhya Sai (previously at Intel) for their valuable suggestions and contributions in editing this paper.

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Authors and Affiliations

  1. Boston Consulting Group GAMMA, Los Angeles, USA

    Nikita Ahuja

  2. Amazon, Seattle, USA

    Harsha Bikkavilli

  3. Johns Hopkins University, Baltimore, USA

    Zhaoqi Chen

  4. Santa Monica College, Santa Monica, USA

    Mary Mehrnoosh Eshaghian-Wilner

  5. AMD, San Diego, USA

    Abhishek Mittal

  6. University of Southern California, Los Angeles, USA

    Kodiak Ravicz

  7. NVIDIA, Santa Clara, USA

    Bhimsen Sangal

  8. Xilinx, San Jose, USA

    Sagarneel Sarma

  9. Electrosonic, Los Angeles, USA

    Mike Schlesinger

  10. University of California, Los Angeles, USA

    Ariana Wilner

Authors
  1. Nikita Ahuja
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  2. Harsha Bikkavilli
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  3. Zhaoqi Chen
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  4. Mary Mehrnoosh Eshaghian-Wilner
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  5. Abhishek Mittal
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  10. Ariana Wilner
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Correspondence to Mary Mehrnoosh Eshaghian-Wilner.

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Ahuja, N., Bikkavilli, H., Chen, Z. et al. Real-time cellular-level imaging and medical treatment with a swarm of wireless multifunctional robots. J Supercomput 78, 1923–1943 (2022). https://doi.org/10.1007/s11227-021-03924-z

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  • DOI: https://doi.org/10.1007/s11227-021-03924-z

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