Technology & Management Review

Peer Reviewed Article

Vol. 6 (2021)

Neural Networks for Autonomous Drone Navigation in Urban Environments

Published
2021-02-15

Abstract

This paper investigates using neural networks to enable autonomous drone navigation in urban settings. The study's primary goals were to examine how neural networks might improve autonomous drone sensing, planning, and decision-making and to analyze new developments and potential future paths in this area. A thorough analysis of the body of research and secondary data sources—such as scholarly publications, conference proceedings, and internet databases—was conducted regarding methodology. The most important discoveries are the notable developments in object detection and scene understanding that neural networks permit in drone vision, as well as the adaptive planning and decision-making skills made possible by trajectory prediction models and reinforcement learning. Emerging technologies like multimodal sensor fusion and continuous learning are also highlighted in the paper, along with the policy implications for data privacy, accessibility, ethics, and safety. While highlighting the significance of addressing essential policy considerations for ethical and sustainable deployment, these findings highlight the transformative potential of neural networks for autonomous drone navigation in urban contexts.

References

  1. Addimulam, S., Mohammed, M. A., Karanam, R. K., Ying, D., Pydipalli, R., Patel, B., Shajahan, M. A., Dhameliya, N., & Natakam, V. M. (2020). Deep Learning-Enhanced Image Segmentation for Medical Diagnostics. Malaysian Journal of Medical and Biological Research, 7(2), 145-152. https://mjmbr.my/index.php/mjmbr/article/view/687
  2. Anumandla, S. K. R. (2018). AI-enabled Decision Support Systems and Reciprocal Symmetry: Empowering Managers for Better Business Outcomes. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 33-41. https://upright.pub/index.php/ijrstp/article/view/129
  3. Dhameliya, N., Mullangi, K., Shajahan, M. A., Sandu, A. K., & Khair, M. A. (2020). Blockchain-Integrated HR Analytics for Improved Employee Management. ABC Journal of Advanced Research, 9(2), 127-140. https://doi.org/10.18034/abcjar.v9i2.738
  4. Ghadiok, V., Goldin, J., Ren, W. (2012). On the Design and Development of Attitude Stabilization, Vision-based Navigation, and Aerial Gripping for a Low-cost Quadrotor. Autonomous Robots, 33(1-2), 41-68. https://doi.org/10.1007/s10514-012-9286-z
  5. Jia, Z., Balasuriya, A., Challa, S. (2008). Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches. Algorithms, 1(2), 153-182. https://doi.org/10.3390/a1020153
  6. Khair, M. A., Tejani, J. G., Sandu, A. K., & Shajahan, M. A. (2020). Trade Policies and Entrepreneurial Initiatives: A Nexus for India’s Global Market Integration. American Journal of Trade and Policy, 7(3), 107–114. https://doi.org/10.18034/ajtp.v7i3.706
  7. Koehler, S., Dhameliya, N., Patel, B., & Anumandla, S. K. R. (2018). AI-Enhanced Cryptocurrency Trading Algorithm for Optimal Investment Strategies. Asian Accounting and Auditing Advancement, 9(1), 101–114. https://4ajournal.com/article/view/91
  8. Lu, Y., Xue, Z., Gui-Song, X., Zhang, L. (2018). A Survey on Vision-based UAV Navigation. Geo-Spatial Information Science, 21(1), 32. https://doi.org/10.1080/10095020.2017.1420509
  9. Maddula, S. S. (2018). The Impact of AI and Reciprocal Symmetry on Organizational Culture and Leadership in the Digital Economy. Engineering International, 6(2), 201–210. https://doi.org/10.18034/ei.v6i2.703
  10. Maddula, S. S., Shajahan, M. A., & Sandu, A. K. (2019). From Data to Insights: Leveraging AI and Reciprocal Symmetry for Business Intelligence. Asian Journal of Applied Science and Engineering, 8(1), 73–84. https://doi.org/10.18034/ajase.v8i1.86
  11. Mercado, D., Castillo, P., Lozano, R. (2018). Sliding Mode Collision-free Navigation for Quadrotors Using Monocular Vision. Robotica, 36(10), 1493-1509. https://doi.org/10.1017/S0263574718000516
  12. Mohammed, M. A., Kothapalli, K. R. V., Mohammed, R., Pasam, P., Sachani, D. K., & Richardson, N. (2017). Machine Learning-Based Real-Time Fraud Detection in Financial Transactions. Asian Accounting and Auditing Advancement, 8(1), 67–76. https://4ajournal.com/article/view/93
  13. Mullangi, K. (2017). Enhancing Financial Performance through AI-driven Predictive Analytics and Reciprocal Symmetry. Asian Accounting and Auditing Advancement, 8(1), 57–66. https://4ajournal.com/article/view/89
  14. Mullangi, K., Maddula, S. S., Shajahan, M. A., & Sandu, A. K. (2018). Artificial Intelligence, Reciprocal Symmetry, and Customer Relationship Management: A Paradigm Shift in Business. Asian Business Review, 8(3), 183–190. https://doi.org/10.18034/abr.v8i3.704
  15. Mullangi, K., Yarlagadda, V. K., Dhameliya, N., & Rodriguez, M. (2018). Integrating AI and Reciprocal Symmetry in Financial Management: A Pathway to Enhanced Decision-Making. International Journal of Reciprocal Symmetry and Theoretical Physics, 5, 42-52. https://upright.pub/index.php/ijrstp/article/view/134
  16. Nguyen, P. H., Arsalan, M., Koo, J. H., Naqvi, R. A., Truong, N. Q. (2018). LightDenseYOLO: A Fast and Accurate Marker Tracker for Autonomous UAV Landing by Visible Light Camera Sensor on Drone. Sensors, 18(6), 1703. https://doi.org/10.3390/s18061703
  17. Nizamuddin, M., Natakam, V. M., Sachani, D. K., Vennapusa, S. C. R., Addimulam, S., & Mullangi, K. (2019). The Paradox of Retail Automation: How Self-Checkout Convenience Contrasts with Loyalty to Human Cashiers. Asian Journal of Humanity, Art and Literature, 6(2), 219-232. https://doi.org/10.18034/ajhal.v6i2.751
  18. Nonami K. (2018). Research and Development of Drone and Roadmap to Evolution. Journal of Robotics and Mechatronics, 30(3), 322-336. https://doi.org/10.20965/jrm.2018.p0322
  19. Patel, B., Mullangi, K., Roberts, C., Dhameliya, N., & Maddula, S. S. (2019). Blockchain-Based Auditing Platform for Transparent Financial Transactions. Asian Accounting and Auditing Advancement, 10(1), 65–80. https://4ajournal.com/article/view/92
  20. Pydipalli, R. (2018). Network-Based Approaches in Bioinformatics and Cheminformatics: Leveraging IT for Insights. ABC Journal of Advanced Research, 7(2), 139-150. https://doi.org/10.18034/abcjar.v7i2.743
  21. Pydipalli, R., & Tejani, J. G. (2019). A Comparative Study of Rubber Polymerization Methods: Vulcanization vs. Thermoplastic Processing. Technology & Management Review, 4, 36-48. https://upright.pub/index.php/tmr/article/view/132
  22. Richardson, N., Pydipalli, R., Maddula, S. S., Anumandla, S. K. R., & Vamsi Krishna Yarlagadda. (2019). Role-Based Access Control in SAS Programming: Enhancing Security and Authorization. International Journal of Reciprocal Symmetry and Theoretical Physics, 6, 31-42. https://upright.pub/index.php/ijrstp/article/view/133
  23. Rodriguez, M., Tejani, J. G., Pydipalli, R., & Patel, B. (2018). Bioinformatics Algorithms for Molecular Docking: IT and Chemistry Synergy. Asia Pacific Journal of Energy and Environment, 5(2), 113-122. https://doi.org/10.18034/apjee.v5i2.742
  24. Sachani, D. K. (2018). Technological Advancements in Retail Kiosks: Enhancing Operational Efficiency and Consumer Engagement. American Journal of Trade and Policy, 5(3), 161–168. https://doi.org/10.18034/ajtp.v5i3.714
  25. Sachani, D. K. (2020). Assessing the Impact of Brand Loyalty on Tobacco Purchasing Decisions and Spending Patterns. ABC Research Alert, 8(3), 147–159. https://doi.org/10.18034/ra.v8i3.661
  26. Sachani, D. K., & Vennapusa, S. C. R. (2017). Destination Marketing Strategies: Promoting Southeast Asia as a Premier Tourism Hub. ABC Journal of Advanced Research, 6(2), 127-138. https://doi.org/10.18034/abcjar.v6i2.746
  27. Sanchez-Rodriguez, J-P., Aceves-Lopez, A. (2018). A Survey on Stereo Vision-based Autonomous Navigation for Multi-rotor MUAVs. Robotica, 36(8), 1225-1243. https://doi.org/10.1017/S0263574718000358
  28. Shajahan, M. A. (2018). Fault Tolerance and Reliability in AUTOSAR Stack Development: Redundancy and Error Handling Strategies. Technology & Management Review, 3, 27-45. https://upright.pub/index.php/tmr/article/view/126
  29. Shajahan, M. A., Richardson, N., Dhameliya, N., Patel, B., Anumandla, S. K. R., & Yarlagadda, V. K. (2019). AUTOSAR Classic vs. AUTOSAR Adaptive: A Comparative Analysis in Stack Development. Engineering International, 7(2), 161–178. https://doi.org/10.18034/ei.v7i2.711
  30. Vennapusa, S. C. R., Fadziso, T., Sachani, D. K., Yarlagadda, V. K., & Anumandla, S. K. R. (2018). Cryptocurrency-Based Loyalty Programs for Enhanced Customer Engagement. Technology & Management Review, 3, 46-62. https://upright.pub/index.php/tmr/article/view/137
  31. Yarlagadda, V. K., & Pydipalli, R. (2018). Secure Programming with SAS: Mitigating Risks and Protecting Data Integrity. Engineering International, 6(2), 211–222. https://doi.org/10.18034/ei.v6i2.709
  32. Ying, D., Patel, B., & Dhameliya, N. (2017). Managing Digital Transformation: The Role of Artificial Intelligence and Reciprocal Symmetry in Business. ABC Research Alert, 5(3), 67–77. https://doi.org/10.18034/ra.v5i3.659

Similar Articles

11-11 of 11

You may also start an advanced similarity search for this article.