Dr. Abhinav Sinha is an Assistant Professor in the Department of Aerospace Engineering and Engineering Mechanics at the University of Cincinnati. Dr. Sinha directs the Guidance, Autonomy, Learning, and Control for Intelligent Systems (GALACxIS) Lab. He works at the intersection of control theory, artificial intelligence, and dynamical systems. His overarching research agenda revolves around the design and implementation of advanced strategies with the primary objective of ensuring the safety, robustness, fidelity, reliability, and increased autonomy in high-integrity aerospace and robotic missions, while minimizing or eliminating the need for human intervention.

Prior to joining the University of Cincinnati, Dr. Abhinav Sinha was a postdoctoral researcher affiliated with the Unmanned Systems Lab at The University of Texas at San Antonio. His prior research experience includes a brief postdoctoral fellowship at the Intelligent Systems & Control Lab, Department of Aerospace Engineering, Indian Institute of Technology Bombay. Dr. Sinha also holds the distinction of completing his Ph.D. degree in Aerospace Engineering from the Indian Institute of Technology Bombay in around two years, setting a record for the fastest completion of a Ph.D. in the Department of Aerospace Engineering and one of the fastest in the institute. He is also a recipient of the prestigious Naik and Rastogi Award for excellence in Ph.D. research. Dr. Sinha is a member of IEEE (including Control Systems Society, Aerospace and Electronic Systems Society, and many technical committees of Robotics and Automation Society), IFAC, and is a senior member of AIAA. He also serves as a subcommittee chair for the IEEE TC on Manufacturing, Automation, and Robotic Control.

Featured Works

Multicriteria Intercept Guidance and Control

Addressing terminal constraints on the trajectory of an autonomous vehicle in addition to the primary objective of target interception.

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Multiagent cooperative pursuit-evasion

The celebrated "the lady, the bandit, and the bodyguard" scenario. Our research offers a different viewpoint on this problem.

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Resilience and Robustness in Networked Systems

Building safe, resilient and robust networked cyber-physical systems to ensure fully distributed cooperative behavior.

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Learning and control in autonomous systems

Investigating fundamental aspects in learning and control for an autonomous system, with an emphasis on learning in complex large-scale interconnected systems.

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Multivehicle motion planning and control

Motion planning algorithms that handle uncertainties, adapt to dynamic environments, and maintain consistent performance under adverse conditions.

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High-fidelity Aerial Mobility and Manipulation

Unleashing the future of airborne mobility and precision manipulation, and redefining the boundaries of aerial possibilities.

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Courses, Tutorials, Talks, Seminars

  • AEEM 2013 (Spring Semester at UC, 2024)

Introduction to Systems Engineering

  • AEEM 4042 (Fall Semester at UC, 2024)

Fundamentals of Control Theory

  • AE 410 / AE 641 (Fall Semester at IITB, 2019-2021)

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