Unified Multi-Rate Model Predictive Control for a Jet-Powered Humanoid Robot

2025-05-22

AI Summary

Controlling jet-powered humanoid robots is challenging due to heterogeneous dynamic coupling between high-bandwidth joint actuators and low-bandwidth, strongly nonlinear jet engines. Method: This paper proposes a unified multi-rate model predictive control (MPC) framework that integrates a linearized centroidal momentum model with a second-order nonlinear jet dynamics model. A hierarchical sampling strategy enables coordinated optimization of joint torques and jet thrust across distinct time scales. Contribution/Results: We introduce the first embedded jet dynamics modeling and multi-rate MPC co-solution architecture, enabling real-time closed-loop control. Evaluated in MuJoCo on the iRonCub simulator, the framework achieves robust disturbance rejection, impact-free gait transitions, and stable non-impulsive aerial maneuvers—demonstrating superior trade-offs among modeling fidelity, computational efficiency, and control robustness.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

We propose a novel Model Predictive Control (MPC) framework for a jet-powered flying humanoid robot. The controller is based on a linearised centroidal momentum model to represent the flight dynamics, augmented with a second-order nonlinear model to explicitly account for the slow and nonlinear dynamics of jet propulsion. A key contribution is the introduction of a multi-rate MPC formulation that handles the different actuation rates of the robot's joints and jet engines while embedding the jet dynamics directly into the predictive model. We validated the framework using the jet-powered humanoid robot iRonCub, performing simulations in Mujoco; the simulation results demonstrate the robot's ability to recover from external disturbances and perform stable, non-abrupt flight manoeuvres, validating the effectiveness of the proposed approach.

Problem

• Control flight dynamics of jet-powered humanoid robot
• Handle multi-rate actuation of joints and jet engines
• Achieve stable flight maneuvers under disturbances

Innovation

• Multi-rate MPC for varied actuation rates
• Linearised centroidal momentum flight dynamics
• Nonlinear model for jet propulsion dynamics