Gokul S. Sankar

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About

Gokul S. Sankar is a researcher advancing the frontier of safe and optimal motion planning for autonomous systems. His primary research areas lie at the intersection of robotics, control theory, and data-driven decision-making, with a focus on ensuring provable safety guarantees in complex, dynamic environments. Sankar’s most notable contribution is the development of **DaSP-RRT** (Data-Driven Safe Performance-Aware RRT), a novel motion planning algorithm that generates collision-free paths with guaranteed optimality. This work is distinguished by its use of invariant sets—mathematical constructs that ensure a robot remains within a safe region of its state space—while leveraging data to improve performance. By integrating these theoretical guarantees with practical data-driven techniques, Sankar’s approach addresses a critical gap in robotics: how to plan paths that are not only safe but also provably optimal under real-world uncertainties. His paper on DaSP-RRT has already garnered attention with 1 citation shortly after its 2025 publication, signaling its potential impact. Through this work, Sankar is helping to build a foundation for trustworthy autonomous navigation in applications ranging from self-driving cars to aerial drones.