Snehal Jauhri

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About

Snehal Jauhri is a roboticist whose work sits at the intersection of motion planning, perception, and autonomous manipulation. Her research focuses on enabling robots to operate safely and effectively in unstructured, dynamic environments—moving beyond controlled labs into the real world. Jauhri’s major contributions include developing **Regularized Deep Signed Distance Fields**, a reactive motion generation framework that allows robots to evaluate and avoid collisions in real-time, a critical capability for human-robot collaboration in tight spaces. This work has garnered 32 citations and is foundational for safe, online robot operation. She also introduced **NeuGraspNet**, a novel method that reinterprets 6DoF robotic grasping as a neural rendering problem, enabling effective grasping from any single viewpoint in cluttered scenes without requiring additional scene exploration. Her recent work on **Active-Perceptive Motion Generation** for mobile manipulation integrates onboard sensing with motion planning to extract task-relevant visual information on the fly. Jauhri’s research is shaping the next generation of autonomous systems that can perceive, plan, and act with the dexterity and awareness needed for real-world deployment.