Vivekanandan Suryamurthy
Papers
1
Total Citations
34
H-Index
1
About
Vivekanandan Suryamurthy’s research lies at the intersection of robotics, computer vision, and autonomous navigation, with a particular focus on enabling robots to perceive and adapt to unstructured, real-world terrains. His most cited work, “Terrain Segmentation and Roughness Estimation using RGB Data: Path Planning Application on the CENTAURO Robot” (2019, 34 citations), introduces a novel approach that allows robots to assess terrain roughness using only standard RGB cameras—bypassing the need for expensive depth sensors. This contribution is critical for field robotics, where environmental conditions are unknown and unpredictable. By integrating terrain segmentation with roughness estimation, Suryamurthy’s method directly informs path planning, helping robots like the CENTAURO—a highly capable centaur-like platform—navigate safely and efficiently over uneven ground. His work demonstrates a practical, sensor-efficient solution to a core challenge in autonomous mobility, achieving notable impact within the robotics community. Through this research, Suryamurthy has advanced the goal of deploying resilient robots in disaster response, exploration, and industrial inspection, where robust terrain understanding is essential for mission success.
Research Focus
Key Achievements
Top Papers
- 1