Abhishek Nayak

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About

Abhishek Nayak’s research lies at the intersection of robotics, path planning, and combinatorial optimization, with a focus on curvature-constrained motion for unmanned vehicles. His work addresses fundamental challenges in mission planning for fixed-wing aerial robots and ground vehicles that must navigate with minimum turning radius constraints. In his highly cited 2023 paper, “Heuristics and Learning Models for Dubins MinMax Traveling Salesman Problem” (11 citations), Nayak tackles a critical variant of the multiple traveling salesman problem, where Dubins vehicles must equitably distribute tour lengths—a problem essential for surveillance and search-and-rescue operations. He further advances the field with “G*: A New Approach to Bounding Curvature Constrained Shortest Paths through Dubins Gates” (3 citations), introducing an elegant relaxation technique that provides optimality guarantees for shortest paths through obstacles. By replacing hard constraints with “gates,” G* enables efficient, provably good solutions to otherwise intractable motion planning problems. Though early in his career, Nayak’s contributions are already shaping how autonomous systems plan efficient, real-world trajectories under kinematic limits. His work is particularly valuable for students and researchers interested in the intersection of robotics, control theory, and operations research.