Max Robotics — Global Service Robot Directory + US Certification

About

Elis Stefansson’s research lies at the intersection of optimal control, hierarchical planning, and human-robot interaction, with a focus on making complex, large-scale systems computationally tractable. His most influential work introduces a sequential alternating least squares method for solving high-dimensional Hamilton-Jacobi-Bellman equations, a breakthrough that enables globally optimal control for stochastic affine nonlinear systems—overcoming the notorious curse of dimensionality (20 citations). In the realm of autonomous driving, Stefansson pioneered a hierarchical dynamic game framework for truck platooning, ensuring safe and efficient interaction between autonomous trucks and human-driven vehicles (19 citations). His recent contributions advance hierarchical finite state machines (HFSMs) for optimal planning, developing offline-online algorithms that dramatically reduce computational complexity in large-scale systems. Notably, his 2021 work on complexity-aware planning leverages Kolmogorov complexity to detect regularities in deterministic optimal policies, offering a novel perspective on plan efficiency. With a growing citation record and a clear trajectory from theoretical foundations to practical autonomous systems, Stefansson is establishing himself as a key figure in scalable, safe, and intelligent control.