Nijil George
Papers
5
Total Citations
23
H-Index
3
About
Nijil George is a robotics researcher specializing in soft robotic manipulation, reinforcement learning-based grasp planning, and autonomous retail robotics. His most influential work addresses a critical gap in robotic grasping: the inability of conventional vision-based planners to account for the compliant, adaptive nature of soft grippers. In his widely cited 2022 paper (8 citations), George pioneered a reinforcement learning framework to augment traditional grasp plans specifically for soft robotic end-effectors, followed by a 2023 contribution (6 citations) establishing simulation-ready models of soft grippers to enable scalable RL-based training. Beyond manipulation, George has extended his expertise into intelligent retail automation, developing concept-based anomaly detection systems for identifying misplaced inventory (5 citations) and designing a fully autonomous dual-arm omnidirectional robot integrated with a novel soft gripper for shelf management. His 2024 work further explores teleoperated shared-control systems that bridge the gap between full autonomy and human oversight in dynamic retail environments. With over 20 cumulative citations across five publications, George's research represents a cohesive vision for deploying intelligent, dexterous robots in real-world unstructured settings.
Research Focus
Key Achievements
Top Papers
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