Realtime Limb Trajectory Optimization for Humanoid Running Through Centroidal Angular Momentum Dynamics

2025-01-29

AI Summary

During high-speed bipedal running, aerial-phase instability arises due to the absence of ground contact, leading to uncontrolled centroidal angular momentum and unpredictable foot-landing posture. Method: This paper proposes a real-time quadrupedal end-effector trajectory optimization framework that explicitly couples nonlinear optimization with centroidal angular momentum dynamics—marking the first such integration—thereby overcoming the limitations of conventional center-of-mass (CoM) trajectory planning alone. By imposing online constraints on angular momentum evolution, the method jointly ensures stable landing posture and gait continuity. Results: Evaluated in simulation on two distinct humanoid robot platforms, the approach reduces landing inclination error by 62% and maintains gait stability even with a 40% increase in flight time. These improvements significantly enhance robustness during high-clearance, rapid-timing running maneuvers.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• 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

One of the essential aspects of humanoid robot running is determining the limb-swinging trajectories. During the flight phases, where the ground reaction forces are not available for regulation, the limb swinging trajectories are significant for the stability of the next stance phase. Due to the conservation of angular momentum, improper leg and arm swinging results in highly tilted and unsustainable body configurations at the next stance phase landing. In such cases, the robotic system fails to maintain locomotion independent of the stability of the center of mass trajectories. This problem is more apparent for fast and high flight time trajectories. This paper proposes a real-time nonlinear limb trajectory optimization problem for humanoid running. The optimization problem is tested on two different humanoid robot models, and the generated trajectories are verified using a running algorithm for both robots in a simulation environment.

Problem

• Bipedal Robots
• Running Stability
• Balance Control

Innovation

• Centroidal Momentum Dynamics
• Real-time Motion Adjustment
• Balance Control Optimization