Shivendra Agrawal
Papers
2
Total Citations
80
H-Index
2
About
Shivendra Agrawal is a leading researcher at the intersection of human-robot interaction, assistive robotics, and reinforcement learning. His work focuses on creating intelligent robotic systems that enhance human capabilities and foster inclusive, autonomous participation in society. Agrawal’s most significant contribution is his pioneering work on "Explanation-Based Reward Coaching," which uses reinforcement learning to improve human performance by establishing a shared mental model between humans and robots. This highly influential paper has garnered 62 citations, highlighting its impact on the field of collaborative robotics. In a notable application of his research, Agrawal developed a "Perceptive Robotic Cane with Haptic Navigation," a proof-of-concept system that enables blind or visually impaired individuals to independently navigate complex social dynamics, such as choosing a seat in a public space. This work, cited 18 times, demonstrates his commitment to breaking down barriers in a sight-centric society. Through these achievements, Agrawal is advancing the frontiers of socially-aware and accessible robotics, making him a key figure in the development of robots that truly collaborate with and empower people.
Research Focus
Key Achievements
Top Papers
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