Papers
47
Total Citations
1,131
H-Index
16
About
Abhijeet Ravankar is a robotics researcher whose work centers on mobile robot navigation, path planning, and autonomous systems. He is best known for his foundational contributions to path smoothing techniques, with his 2018 survey on the subject accumulating nearly 300 citations and becoming an essential reference for researchers tackling the challenge of generating efficient, hardware-compatible robot trajectories. His development of novel algorithms—including Smooth Hypocycloidal Paths (SHP) and the Hybrid Potential-based Probabilistic Roadmap (HPPRM)—has meaningfully advanced how robots plan and adapt their movement in complex, dynamic environments. Beyond single-robot systems, Ravankar has made notable strides in multi-robot coordination, proposing symbiotic navigation frameworks that enable robots to share environmental knowledge and improve collective efficiency. His work also spans indoor localization using LiDAR-based feature fusion, SLAM mapping in noisy environments, and heterogeneous air-ground robot teams with autonomous UAV docking capabilities. More recently, he has extended these navigation principles to agricultural robotics, demonstrating safe autonomous operation in vineyard settings. With over 700 cumulative citations across his top papers, Ravankar's research reflects a consistent commitment to making autonomous robots smarter, safer, and more practically deployable across diverse real-world environments.
Research Focus
Key Achievements
Top Papers
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- 3A Single LiDAR-Based Feature Fusion Indoor Localization Algorithm83 citations · 2018
- 4Autonomous VTOL-UAV Docking System for Heterogeneous Multirobot Team55 citations · 2020
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