Papers
4
Total Citations
27
H-Index
3
About
Sumeet Batra is a robotics and machine learning researcher whose work sits at the intersection of multi-agent systems, deep reinforcement learning, and autonomous aerial vehicles. He is best known for advancing end-to-end deep reinforcement learning frameworks for quadrotor swarms, with his 2024 paper on collision avoidance and swarm navigation garnering 13 citations and demonstrating that learned controllers can be deployed effectively across entire teams of UAVs — a significant step beyond single-agent approaches. His development of QuadSwarm, a modular and highly parallelizable multi-quadrotor simulator, directly addresses the data-intensive demands of modern RL algorithms, providing the research community with a critical infrastructure tool for scalable drone learning. Batra has also explored the frontier of Quality Diversity Reinforcement Learning, pursuing the long-term goal of training agents capable of acquiring diverse, generalizable skills. Beyond autonomous systems, his work on augmented reality interfaces for human-swarm interaction reflects a broader interest in making robot collectives accessible and interpretable to human operators. Across his still-emerging publication record, Batra consistently tackles foundational challenges in swarm autonomy, simulation, and adaptive learning that position him as a promising contributor to the next generation of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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