Kinodynamic Model Predictive Control for Energy Efficient Locomotion of Legged Robots with Parallel Elasticity

2025-03-07

AI Summary

To address the high energy consumption of dynamic legged robots, this paper proposes a hierarchical model predictive control (MPC) framework integrated with a unidirectional parallel spring (UPS). Methodologically: (i) a kinodynamic MPC formulation is developed, incorporating nonlinear center-of-mass dynamics and kinematic constraints; (ii) a novel hierarchical warm-starting mechanism—leveraging the UPS’s passive energy storage特性—is introduced to efficiently initialize the full-order dynamics model from a simplified one; (iii) the dynamics of the parallel elastic actuator are explicitly modeled and embedded into the controller. The key contribution lies in the first synergistic optimization of the UPS’s unidirectional energy-storing capability within a hierarchical MPC architecture, jointly enhancing dynamic performance and energy efficiency. Simulation results demonstrate a 38.8% reduction in cost of transport (CoT) for high-speed monopedal hopping locomotion; hardware experiments confirm a 14.8% decrease in total-cycle energy consumption.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Planning, Routing, and Scheduling: Learning for Planning and Scheduling

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

In this paper, we introduce a kinodynamic model predictive control (MPC) framework that exploits unidirectional parallel springs (UPS) to improve the energy efficiency of dynamic legged robots. The proposed method employs a hierarchical control structure, where the solution of MPC with simplified dynamic models is used to warm-start the kinodynamic MPC, which accounts for nonlinear centroidal dynamics and kinematic constraints. The proposed approach enables energy efficient dynamic hopping on legged robots by using UPS to reduce peak motor torques and energy consumption during stance phases. Simulation results demonstrated a 38.8% reduction in the cost of transport (CoT) for a monoped robot equipped with UPS during high-speed hopping. Additionally, preliminary hardware experiments show a 14.8% reduction in energy consumption. Video: https://youtu.be/AF11qMXJD48

Problem

• Improves energy efficiency in legged robots using parallel elasticity.
• Reduces peak motor torques and energy consumption during stance phases.
• Demonstrates significant reduction in cost of transport and energy consumption.

Innovation

• Kinodynamic MPC for energy-efficient legged robots
• Hierarchical control with simplified dynamic models
• Unidirectional parallel springs reduce motor torques