Papers
8
Total Citations
70
H-Index
4
About
Rahee Walambe is a leading researcher in autonomous mobile robotics, with a primary focus on trajectory generation, motion planning, and decision-making under uncertainty for nonholonomic systems. Her most cited work, "Optimal Trajectory Generation for Car-type Mobile Robot using Spline Interpolation" (39 citations), introduces a spline-based approach that yields continuous, smooth, and optimized paths for car-like robots—a critical contribution to autonomous navigation. She has also advanced the field through comprehensive reviews on inverse reinforcement learning (2025, 8 citations), bridging the gap between handcrafted reward functions and real-world decision-making. Her practical implementations include military surveillance robots using the Robot Operating System (2018, 6 citations) and probabilistic decision-making frameworks based on Partially Observable Markov Decision Processes (POMDPs) for path planning in collaborative systems (2024, 5 citations). Walambe’s work on auto-parking and collision avoidance algorithms (2020, 4 citations) further demonstrates her commitment to real-world deployment. Supported by a DST WOS-A grant from the Government of India, her research consistently integrates theoretical rigor with hardware implementation, making her a key figure in advancing autonomous vehicle technologies.
Research Focus
Key Achievements
Top Papers
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- 3Military Surveillance Robot Implementation Using Robot Operating System6 citations · 2018
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