Andres Kwasinski
Papers
3
Total Citations
39
H-Index
3
About
Andres Kwasinski is a leading researcher at the intersection of robotics, artificial intelligence, and industrial automation, with a primary focus on transforming modern warehousing and logistics. His work addresses critical challenges in autonomous mobile robot (AMR) coordination, localization, and human-robot collaboration. Kwasinski’s most influential contribution is a deep reinforcement learning framework using deep Q-networks (DQNs) to solve the combined dispatching and routing problem for AMRs in warehouses, achieving practical deployment in both virtual and physical environments (22 citations). He further advanced warehouse automation with KF-Loc, a novel system integrating Kalman filters with machine learning to enable fast, low-cost localization using consumer-grade millimeter-wave hardware (11 citations). His recent work on intent communication between humans and robots (6 citations) is pioneering the next frontier of human-robot synergy, aiming to unlock safer and more efficient collaborative workflows. With a cumulative impact of nearly 40 citations on these three core papers alone, Kwasinski is shaping the future of Industry 4.0 and beyond, providing scalable, intelligent solutions that bridge the gap between theoretical AI and real-world industrial deployment.
Research Focus
Key Achievements
Top Papers
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