Thijs Niesten

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About

Thijs Niesten is a rising star in autonomous systems, whose work bridges the critical gap between theoretical control theory and real-world robotic deployment. His research centers on nonlinear model predictive control (MPC) and embedded systems for autonomous navigation, with a particular focus on ensuring safe, dynamic motion in complex environments. Niesten’s most-cited paper, “Embedded Hierarchical MPC for Autonomous Navigation” (2025, 5 citations), introduces a novel framework that efficiently computes collision-free trajectories for mobile robots, a foundational contribution to safe autonomy. He is also the lead architect of DART (Delft’s Autonomous-driving Robotic Testbed), a compact, cost-effective research platform for autonomous driving (2024, 2 citations). Designed to carry full onboard sensing and computation, DART democratizes access to cutting-edge autonomous driving research, enabling scalable experimentation. By combining hierarchical control architectures with practical hardware design, Niesten’s work directly addresses the computational and safety challenges of deploying robots in human environments. His achievements mark him as a key contributor to the next generation of autonomous navigation systems.