Brain–Computer Interface for Shared Controls of Unmanned Aerial Vehicles

Bi, Zhuming; Mikkola, Aki; Ip, Andrew W. H.; Yung, Kai Leung; Luo, Chaomin

doi:10.1109/taes.2024.3368402

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2024

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Collaborative human and computer controls of smart machines – A proposed hybrid control

Bilal,

Bi,

Younis

et al. 2024

Journal of Industrial Information Integration

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Collaborative human and computer controls of smart machines – A proposed hybrid control

Bilal,

Bi,

Younis

et al. 2024

Journal of Industrial Information Integration

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Enhancing Robotic Autonomy and Deep Reinforcement Learning Applications

Goel,

Singla

2024

Robo-Advisors in Management

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The integration of Deep Reinforcement Learning (DRL) into the realm of robotics and autonomous systems has emerged as a groundbreaking paradigm shift, empowering machines to tackle intricate tasks through interaction with their environments. This chapter offers a comprehensive examination of the current research landscape at the intersection of DRL and robotics within this dynamic field. This chapter navigates through the conceptualization of DRL and explores its diverse applications in controlling robotics and object manipulation. The chapter showcases the autonomy and adaptability enabled by DRL while addressing prevalent challenges such as sample efficiency, safety concerns, and scalability. In conclusion, this chapter serves as a valuable resource for future researchers and practitioners intrigued by the intersection of DRL and robotics. It synthesizes current knowledge, underscores significant progress made, and maps out exciting avenues for further exploration, ultimately propelling the advancement of robotic systems in the era of machine learning and artificial intelligence.

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Brain–Computer Interface for Shared Controls of Unmanned Aerial Vehicles

Cited by 2 publications

References 63 publications

Collaborative human and computer controls of smart machines – A proposed hybrid control

Collaborative human and computer controls of smart machines – A proposed hybrid control

Enhancing Robotic Autonomy and Deep Reinforcement Learning Applications

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