The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Examination of the Recent Research Trends on Controllers in the AI Powered UAV
|
|
Author(s): B. Swapna (Dr. M.G.R. Educational and Research Institute, India), A. Lavanya (Dr. M.G.R. Educational and Research Institute, India), G. Kavitha (Dr. M.G.R. Educational and Research Institute, India), M. Sujitha (Dr. M.G.R. Educational and Research Institute, India), C. Anuradha (SRM Institute of Science and Technology, India), S. Vijayalakshmi (SRM Institute of Science and Technology, India), K. Jeevitha (Dr. M.G.R. Educational and Research Institute, India), R. Kasthuri (Dr. M.G.R. Educational and Research Institute, India)and M. Kamalahasan (Dr. M.G.R. Educational and Research Institute, India)
Copyright: 2025
Pages: 16
Source title:
Humans and Generative AI Tools for Collaborative Intelligence
Source Author(s)/Editor(s): Jingyuan Zhao (University of Toronto, Canada), V. Vinoth Kumar (Vellore Institute of Technology, India), Polinpapilinho F. Katina (University of South Carolina Upstate, USA)and Joseph Richards (California State University, Sacramento, USA)
DOI: 10.4018/979-8-3693-8332-2.ch012
Purchase
|
Abstract
The development of AI is based on research into the patterns and processes of human thought. Improved software and systems are developed as a direct outcome of these research initiatives. Deep learning (DL), a subfield of AI, allows computers to robotically acquire new abilities by analysing training sets, which are collections of previously received data. The AI technique known as deep reinforcement learning is very useful for autonomous UAVs. The fundamental characteristics of autonomous driving, particularly talks and human conversations, including making choices, make robotic motor vehicles the perfect fit for reinforcement learning. This paper presents a new viewpoint by exploring the AI features realized in current journals. This article aims to realize the attitude control is so important for UAVs and moreover AI controller is better than a conventional one. This article explores the abundant AI technologies that may be utilized for attitude control, path planning and obstacle avoidance of UAVs with many applications. Illustrates the way AI in UAV systems on an everyday basis.
Related Content
|
Bikash Kumar, Rhythm Gaba, Rabi Shaw.
© 2026.
40 pages.
|
|
R. Velmurugan, J. Sudarvel, R. Bhuvaneswari, Ravi Thirumalaisamy.
© 2026.
28 pages.
|
|
J. Vijaya, Soumya Chandrakar, Pragya Shrivastava.
© 2026.
42 pages.
|
|
Yamini Ghanghorkar, Amruta Deshpande.
© 2026.
28 pages.
|
|
B. Bharathi, B. Kalaivani, Kasu Manaswi, Kantabathina Tejaswini.
© 2026.
28 pages.
|
|
Moumita Chowdhury, Aastha Agarwal, Alisha Parveen, Abhishek Mukhopadhyay.
© 2026.
42 pages.
|
|
Utkarsh Trivedi, Yash Vardhan, Piyush Kumar, Ansh Aryan, Parth Batra, Hitesh Mohapatra.
© 2026.
28 pages.
|
|
|