Shreya Bollimuntha
Papers
1
Total Citations
5
H-Index
1
About
Shreya Bollimuntha is a rising force in robotics, specializing in dual-arm manipulation and adaptive control systems. Her most-cited work, "Da-Vil: Adaptive Dual-Arm Manipulation with Reinforcement Learning and Variable Impedance Control" (2025, 5 citations), introduces a groundbreaking framework that combines reinforcement learning with variable impedance control to enable robots to perform complex, coordinated bimanual tasks. This approach allows robotic systems to dynamically adjust their stiffness and compliance, making them safer and more effective in human-centric environments. Bollimuntha’s research addresses critical challenges in handling large objects, assembling components, and executing human-like interactions—areas of growing importance in manufacturing, healthcare, and service robotics. Her work stands out for its practical integration of learning-based methods with real-time control, bridging the gap between simulation and deployment. As an early-career researcher, her contributions have already garnered attention for their potential to advance autonomous manipulation in unstructured settings. Bollimuntha’s innovative approach to dual-arm coordination promises to reshape how robots collaborate with humans and each other, marking her as a promising talent in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1