Papers
5
Total Citations
120
H-Index
5
About
Anshul Paigwar is a robotics researcher whose work bridges autonomous driving perception and novel robot design. His primary research areas include autonomous vehicle perception, sensor fusion, and robotic locomotion. Paigwar’s most impactful contribution is **GndNet**, a deep learning framework for fast ground plane estimation and point cloud segmentation from LiDAR data. This work, with 88 citations, addresses a critical precursor for navigable space detection, 3D object detection, and point cloud registration in autonomous vehicles. He further advanced perception with **TransFuseGrid**, a transformer-based architecture for LiDAR-RGB fusion in semantic grid prediction, demonstrating a sophisticated approach to environmental representation. Beyond autonomous driving, Paigwar has made notable contributions to snake robotics. He designed and analyzed the **Compliant Omnidirectional Spherical Modular Snake Robot (COSMOS)** and its predecessor **OSMOS**, tackling the complex challenges of control and motion planning for highly articulated modular robots. His earlier work on optimal velocity trajectory generation for spray painting robots rounds out a career that spans from industrial automation to cutting-edge autonomous systems, showcasing a versatile engineering mind.
Research Focus
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