Badri N. Ranganathan

About

Badri N. Ranganathan is a leading researcher at the intersection of bio-inspired robotics, autonomous systems, and soft sensing. His work is defined by translating biological principles into engineering solutions for small, agile unmanned aerial vehicles (UAVs). A major contribution is the development of a bio-inspired, large-area soft sensing skin that measures UAV wing deformation in flight, a breakthrough for real-time structural health monitoring (32 citations). Ranganathan has also pioneered autonomous small-object detection and avoidance strategies for lightweight drones, overcoming severe payload and computational constraints (27 citations). His interdisciplinary impact extends to precision agriculture, where he designed a low-cost UAV system using deep convolutional neural networks to detect Cercospora leaf spot in okra (19 citations). Most recently, he has expanded the operational capabilities of quadrotor-based cable-driven parallel manipulators through multi-objective optimization and machine learning (4 citations). With a portfolio that consistently bridges biology, sensing, and autonomy, Ranganathan’s work is shaping the next generation of resilient, perceptive, and practical aerial robots.

Research Focus

Key Achievements

Top Papers

1. 1
   Bio‐Inspired Large‐Area Soft Sensing Skins to Measure UAV Wing Deformation in Flight

   32 citations · 2021
2. 2
   Bioinspired Approaches for Autonomous Small-Object Detection and Avoidance

   27 citations · 2019
3. 3
   A low-cost UAV for detection of Cercospora leaf spot in okra using deep convolutional neural network

   19 citations · 2022
4. 4
   Autonomous Bio-Inspired Small-Object Detection and Avoidance

   8 citations · 2018
5. 5
   Expanding the wrench feasible workspace of quadrotor-based mobile cable-driven parallel manipulators using multi-objective optimization and machine learning

   4 citations · 2024

Key Collaborators

Contact & Links