Rodrigo Matos Carnier

The University of Tokyo, Yokohama National University

Papers

Total Citations

H-Index

About

Rodrigo Matos Carnier is a researcher at the intersection of robotics, optimal control, and structural dynamics. His work focuses on developing energy-efficient locomotion strategies for bipedal robots, primarily through the application of advanced optimal control theory. In his 2017 paper on "Energy-efficient optimal control of robotic leg by indirect methods," Carnier explored how indirect optimization techniques can generate more efficient and natural gaits, addressing long-standing performance issues in biped robotics. He extended this line of inquiry in 2020 with "Assessment of Machine Learning of Optimal Solutions for Robotic Walking," where he investigated how machine learning can approximate and accelerate the computation of optimal walking trajectories. Demonstrating versatility, Carnier also applies sensor technology to fluid-structure interaction problems, as seen in his 2023 work on "Flow-Induced Vibration Analysis Using a Low-Cost Inertial Measurement Unit," which proposes an affordable monitoring alternative for vortex-induced movements in offshore platforms. While his citation counts are currently modest, his work represents a meaningful convergence of theoretical control methods and practical robotic applications.