Kush Prasad
Papers
1
Total Citations
18
H-Index
1
About
Kush Prasad is a roboticist whose research focuses on advancing autonomous navigation in challenging, perceptually degraded environments. His most cited work, "State lattice with controllers: Augmenting lattice-based path planning with controller-based motion primitives" (2014, 18 citations), addresses a critical limitation in traditional state lattice planning. While state lattices are widely used for ground, water, aerial, and space robots, they rely on precise metric motion primitives that fail in GPS-denied areas. Prasad’s key contribution is augmenting these lattices with controller-based motion primitives, enabling robust path planning even when global positioning is unavailable. This hybrid approach bridges the gap between geometric planning and reactive control, allowing robots to navigate safely using only local sensor data. Though his citation count is modest, the work is notable for its practical impact on field robotics, particularly for autonomous systems operating in indoor, subterranean, or urban canyons where satellite signals are lost. Prasad’s research demonstrates a deep understanding of the trade-offs between plan-based and reactive navigation, offering a scalable solution for real-world deployment. His work continues to influence researchers developing resilient autonomy for robots in GPS-denied and unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1