Vishnu Prem
Papers
1
Total Citations
2
H-Index
1
About
Vishnu Prem is a robotics researcher whose work centers on safe and uncertainty-aware autonomous navigation. His primary research areas include model predictive control, probabilistic motion planning, and robot decision-making under environmental and state estimation uncertainty. Prem’s most notable contribution is his 2024 paper, “Unconstrained Model Predictive Control for Robot Navigation under Uncertainty,” which introduces a novel closed-form approximation of collision probability that propagates uncertainty over the planning horizon. This formulation enables real-time, unconstrained optimization for robots operating in unpredictable environments—a significant advance over traditional constrained approaches that often struggle with computational tractability. Though early in his career, his work has already garnered attention for its theoretical elegance and practical applicability in field robotics. Prem’s research bridges the gap between rigorous probabilistic guarantees and computationally efficient control, making it highly relevant for autonomous vehicles, drones, and mobile manipulators. As his citation count grows, his contributions are poised to influence the next generation of risk-aware navigation systems.
Research Focus
Key Achievements
Top Papers
- 1