Manik Vashisht

Jaypee University of Information Technology

Papers

1

Total Citations

9

H-Index

1

About

Manik Vashisht’s research centers on robotics, motion planning, and computational geometry, with a particular focus on enabling safe, efficient navigation in dynamic environments. His most-cited work introduces an innovative method for collision-free path planning using offset Non-Uniform Rational B-Splines (NURBS), a technique that mathematically models robot trajectories around polygonal obstacles through vector addition. This approach allows mobile robots to adapt their paths in real time as the environment changes, addressing a critical challenge in autonomous navigation. Although his citation count is modest, the paper’s application of NURBS—a tool more commonly associated with computer-aided design—to robotics represents a creative interdisciplinary contribution. Vashisht’s work is notable for bridging geometric modeling and practical robotic control, offering a foundation for further research in dynamic obstacle avoidance. His contributions are particularly relevant for students and researchers exploring motion planning in cluttered or unpredictable settings, demonstrating how mathematical elegance can solve real-world robotic challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Robot motion planning in a dynamic environment using offset Non-Uniform Rational B-Splines (NURBS)
9 citations · 2011
📈 Most Prolific Year: 2011 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Jaypee University of Information Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago