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About

Alexis Mifsud is a robotics researcher specializing in state estimation, sensor fusion, and whole-body control for humanoid and legged robots. His work addresses one of the most fundamental challenges in humanoid robotics: accurately reconstructing the dynamic state of a robot's floating base — its pose, velocity, and interaction forces — in real time and under realistic conditions. Mifsud's most influential contribution, "Experimental Evaluation of Simple Estimators for Humanoid Robots" (2017, 52 citations), introduced a family of lightweight yet effective estimators for floating-base state reconstruction, directly enabling high-rate whole-body control. Complementing this, his earlier work on IMU-based contact force estimation (2015, 19 citations) and Extended Kalman Filter-based sensor fusion (2015, 8 citations) demonstrated that reliable humanoid kinematics and dynamics observation is achievable even with minimal or low-cost sensing. His 2018 paper on model-based external force estimation (22 citations) further extended this philosophy by eliminating the need for expensive torque sensors entirely. Through his involvement in the Loco3D project (2017, 14 citations), Mifsud also contributed to advancing multi-contact locomotion in complex environments. Collectively, his research has meaningfully shaped how the robotics community approaches robust, sensor-efficient state estimation for autonomous humanoid systems.