Kiran G. Krishnan
Papers
2
Total Citations
7
H-Index
2
About
Kiran G. Krishnan is a robotics researcher whose work focuses on the intersection of reinforcement learning and autonomous systems. His primary research areas include robotic arm manipulation, mobile robot navigation, and the application of AI-driven control systems to real-world challenges. Krishnan’s most notable contributions center on using deep reinforcement learning to enhance robot arm control, particularly for medical applications such as instrument-assisted surgery, where precision and adaptability are critical. His 2022 paper on this topic has garnered 4 citations, reflecting its relevance in advancing surgical robotics. Additionally, his work on path planning for mobile robots using reinforcement learning—cited 3 times—addresses complex tasks like object manipulation, outdoor navigation, and exploration in uncharted environments. By demonstrating how modern robots can complement or replace human effort in intricate operations, Krishnan’s research underscores the potential of reinforcement learning to solve practical problems in healthcare and beyond. His achievements highlight a commitment to bridging theoretical AI algorithms with tangible, high-impact applications, making his work a valuable resource for students and researchers interested in autonomous systems and robotics.
Research Focus
Key Achievements
Top Papers
- 1Using Deep Reinforcement Learning For Robot Arm Control4 citations · 2022
- 2Path Planning of Mobile Robot Using Reinforcement Learning3 citations · 2022