Shivansh Beohar
Papers
1
Total Citations
2
H-Index
1
About
Dr. Shivansh Beohar is a robotics researcher specializing in visual simultaneous localization and mapping (SLAM) and semantic scene understanding for autonomous navigation. His work addresses a critical challenge in mobile robotics: enabling reliable, drift-free localization using low-cost, budget-grade cameras without relying on traditional loop closures. His most-cited paper, "SLAM and Map Learning using Hybrid Semantic Graph Optimization" (2022), introduces a novel hybrid approach that integrates semantic object-level information into the SLAM pipeline, allowing robots to correct cumulative drift continuously during everyday navigation—even when loops are absent. This contribution has earned 2 citations and represents an important step toward practical, long-term autonomy in unstructured environments. Dr. Beohar’s research sits at the intersection of computer vision, graph optimization, and machine learning, with potential applications in service robotics, warehouse automation, and autonomous inspection. His work is particularly notable for its focus on making advanced SLAM techniques accessible and robust on resource-constrained hardware, bridging the gap between theoretical SLAM research and real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1SLAM and Map Learning using Hybrid Semantic Graph Optimization2 citations · 2022