P. N. Pournami

About

P. N. Pournami’s research bridges the critical gap between autonomous navigation and precision control in robotics. Her work spans two key areas: visual odometry for agent localization and sliding mode control for robotic manipulators. In visual odometry, she introduced the ViT VO technique, a novel CNN-Transformer hybrid architecture that enables autonomous agents—such as vehicles and robots—to accurately track their paths and detect obstacles. This work, published in 2023, has already garnered citations for its innovative fusion of convolutional and transformer networks. In control systems, Pournami developed a novel discrete reaching law for sliding mode control of robotic manipulators, specifically designed to reduce the quasi-sliding mode band while improving reaching dynamics. Her 2019 paper addresses the persistent challenge of chattering in sliding mode control, offering a solution that enhances end-effector positioning accuracy. With her contributions cited in both autonomous localization and robust control, Pournami demonstrates a rare ability to advance fundamental theory while solving practical challenges in robotics—from path tracking to precise manipulation.

Research Focus

Key Achievements

Top Papers

1. 1
   ViT VO - A Visual Odometry technique Using CNN-Transformer Hybrid Architecture

   2 citations · 2023
2. 2
   Novel Discrete Reaching Law for Sliding Mode Control of Robotic Manipulators to Reduce Quasi Sliding Mode Band with Improved Reaching

   2 citations · 2019

Key Collaborators

Contact & Links