Forrest Laine

Vanderbilt University, University of California, Berkeley

Papers

Total Citations

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About

Forrest Laine is a researcher at the forefront of robotics and control theory, specializing in multi-agent interaction, game-theoretic planning, and constrained optimal control. His work addresses the fundamental challenge of enabling robots to make robust decisions under uncertainty, particularly in dynamic, multi-agent environments. Laine’s major contribution includes the development of "Contingency Games for Multi-Agent Interaction," a novel framework that merges contingency planning with game theory, allowing robots to generate adaptive plans conditioned on uncertain events—a critical capability for safe autonomous driving and human-robot collaboration. This influential paper has already garnered 18 citations since its 2024 publication. Additionally, Laine has advanced control theory with his efficient algorithms for solving the Linear Quadratic Regulator (LQR) problem under linear equality constraints, as detailed in his 2019 work, also cited 18 times. These methods provide explicit feedback control laws, significantly improving computational efficiency for constrained robotic systems. With a growing citation impact and a focus on practical, real-world applications, Laine’s research is shaping the next generation of intelligent, interactive autonomous systems.