Pritam Ojha
Papers
3
Total Citations
15
H-Index
2
About
Pritam Ojha is a robotics researcher specializing in motion planning and obstacle avoidance for high-degree-of-freedom systems operating in dynamic environments. His work centers on developing real-time replanning algorithms that enable robots—from manipulators to anguilliform-inspired designs—to navigate unpredictable settings safely and efficiently. Ojha’s most-cited paper, “Real-Time Obstacle Avoidance Algorithm for Dynamic Environment on Probabilistic Road Map” (2021, 11 citations), introduces a hybrid approach combining Probabilistic Road Map (PRM) sampling with A* optimization, achieving robust pathfinding amid moving obstacles. He further advanced the field with “AD*-Based Dynamically Feasible Replanning Technique for Anguilliform-Inspired Robot” (2023, 3 citations) and “Dynamic Obstacle Avoidance Using Path Reshaping on Probabilistic Roadmaps for High-Degree-of-Freedom Robots” (2025, 1 citation), which addresses the critical challenge of real-time replanning for complex manipulators. Ojha’s contributions bridge theoretical motion planning with practical robotic autonomy, offering scalable solutions for industrial and service robotics. His work is particularly notable for tackling the computational bottleneck of high-DOF systems in cluttered, changing spaces—a key hurdle for next-generation autonomous robots.
Research Focus
Key Achievements
Top Papers
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