Adheesh Shenoy
Papers
3
Total Citations
37
H-Index
2
About
Adheesh Shenoy is a leading researcher in robotic manipulation, with a focused expertise in **multi-object grasping**—a domain that pushes the boundaries of how robots interact with cluttered, real-world environments. His work addresses a fundamental inefficiency in traditional robotics: the single-object pick-and-place paradigm. Shenoy’s major contribution lies in developing policies that enable robots to **estimate, grasp, and transfer multiple objects simultaneously** from a pile, dramatically improving throughput for applications like warehouse fulfillment. His most-cited paper (2021, 20 citations) tackles the core challenge of using tactile sensing to predict how many objects a robot will successfully lift before it even moves, a critical step toward human-like dexterity. Building on this, his 2022 work (15 citations) introduces a complete batch-picking policy that integrates with warehouse management systems to optimize multi-order fulfillment. Shenoy’s research is not just theoretical; it directly addresses the practical demands of logistics, where efficiency gains from multi-object grasping can revolutionize supply chain operations. By bridging the gap between tactile perception and action planning, he is laying the groundwork for the next generation of autonomous, high-speed robotic pickers.
Research Focus
Key Achievements
Top Papers
- 1Multi-Object Grasping – Estimating the Number of Objects in a Robotic Grasp20 citations · 2021
- 2
- 3