Radhika Tekade
Papers
1
Total Citations
38
H-Index
1
About
Dr. Radhika Tekade is a leading researcher in autonomous mobile robotics, with a primary focus on perception and navigation in complex, unstructured environments. Her work is pivotal in advancing the capabilities of robots for critical applications such as urban search and rescue, surveillance, and industrial inspection. Dr. Tekade’s most notable contribution is her pioneering deep learning-based approach for stair detection and traversal, a fundamental challenge for robots operating in human-centric spaces. Her highly cited 2019 paper, “Deep Learning Based Stair Detection and Statistical Image Filtering for Autonomous Stair Climbing,” which has garnered 38 citations, introduces a robust method that combines convolutional neural networks with statistical filtering to enable reliable stair identification and safe climbing. This work directly addresses a key bottleneck in field robotics, moving beyond simple planar navigation. By integrating deep perception with control, Dr. Tekade has significantly improved the autonomy and operational range of mobile robots, enabling them to navigate multi-level environments where stairs are a common obstacle. Her research continues to shape the future of resilient, terrain-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1