Vishrut Kaushik

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About

Vishrut Kaushik is a researcher focused on advancing safe, real-time motion planning for autonomous vehicles and robots. His primary research areas include reachability-based trajectory design, robust control, and risk-aware planning under uncertainty. Kaushik’s major contributions center on developing algorithms that guarantee safety while overcoming the conservatism of traditional deterministic methods. His most notable work, the REFINE framework (2022–2024, 8 citations), introduces a novel approach using robust feedback linearization and zonotopes to predict ego vehicle behavior without costly online numerical integration, enabling real-time receding horizon planning with formal safety guarantees. Building on this, his RADIUS framework (2023, 4 citations) addresses the challenge of overly conservative behavior in deterministic motion planning by incorporating chance-constrained optimization, allowing robots to operate safely amidst uncertain obstacle locations without sacrificing performance. Kaushik’s work bridges the gap between theoretical safety guarantees and practical real-time implementation, making him a rising contributor to the field of autonomous systems. His research has significant implications for self-driving cars, drones, and other robotic platforms operating in dynamic, uncertain environments.