O. Patrick Kreidl
Papers
13
Total Citations
165
H-Index
5
About
O. Patrick Kreidl is a leading researcher in multi-robot systems, specializing in information gathering, path planning, and secure coordination for environmental monitoring and precision agriculture. His work addresses the fundamental challenge of enabling teams of autonomous robots to efficiently collect data from unknown environments while maintaining communication and security constraints. Kreidl’s most impactful contributions include pioneering approaches to multi-robot informative path planning with continuous connectivity constraints (37 citations) and continuous region partitioning for unknown environments (31 citations), which have become foundational in the field. His comprehensive survey on multi-robot information gathering for precision agriculture (54 citations) provides a critical roadmap for applying these technologies to real-world agricultural challenges. More recently, Kreidl has advanced the field by integrating deep reinforcement learning for information sampling (12 citations) and developing blockchain-based solutions for secure multi-robot coordination (3 citations), addressing emerging concerns about data integrity in distributed robotic systems. His work on secure multi-robot adaptive information sampling (7 citations) represents a novel intersection of robotics and cybersecurity. With over 150 total citations across his publications, Kreidl continues to shape the future of autonomous robotic systems for environmental monitoring and precision agriculture.
Research Focus
Key Achievements
Top Papers
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- 5Secure Multi-Robot Adaptive Information Sampling7 citations · 2021
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- 9Algorithmic decision making for robot navigation in unknown environments3 citations · 2017
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