Papers
9
Total Citations
55
H-Index
4
About
Satheeshkumar Veeramani is a leading researcher at the intersection of reinforcement learning, multi-robot coordination, and autonomous manufacturing. His work centers on developing intelligent path planning and affordance-based human-robot interaction systems, with a particular focus on SwarmItFIX—a self-reconfigurable swarm fixture system for sheet metal milling and drilling processes. Veeramani’s major contributions include pioneering the use of Markov Decision Processes and reinforcement learning to solve complex multi-agent locomotion and fixturing problems, enabling precise coordination between serial manipulators and swarm robots. His most cited paper, “Affordance-Based Human–Robot Interaction With Reinforcement Learning” (2023, 14 citations), addresses the challenge of grasp and release operations in human-robot collaboration. He has also advanced autonomous workflows through the LIRA module for self-driving labs and the GenCo framework for adaptive peg-in-hole robotics using Vision Language Models. With over 55 total citations across nine publications, Veeramani’s work is shaping the future of intelligent manufacturing, swarm robotics, and closed-loop autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Affordance-Based Human–Robot Interaction With Reinforcement Learning14 citations · 2023
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