Poorva Agrawal

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About

Poorva Agrawal is a researcher at the forefront of multi-robot systems and bio-inspired artificial intelligence, with a primary focus on cooperative hunting and intelligent transportation. Her work addresses the critical challenge of enabling robot teams to collaboratively track and capture moving evaders—a problem with direct applications in surveillance, search-and-rescue, and autonomous defense. Agrawal’s most significant contribution is the development of the novel Corner Dragging Algorithm (CDA), a bio-inspired approach that allows robot swarms to adaptively coordinate their movements in real-time, even when the target’s location is continuously changing. This work, published in 2019, has garnered 4 citations and builds on her earlier foundational study from 2018, which has accumulated 9 citations and established key principles for adaptive algorithm design in multi-robot hunting scenarios. Beyond pursuit-evasion, Agrawal has also explored the integration of robotics into Intelligent Transportation Systems (ITS), contributing a simulation study in 2014 that examines how multi-robot coordination can enhance road safety. Her most recent comprehensive review, published in 2024, synthesizes the rapid evolution of AI and robotics, highlighting their potential to reduce human error and bias across industries. With a growing citation record and a focus on practical, real-world applications, Agrawal is shaping the future of autonomous, cooperative robotics.