Jumping Control for a Quadrupedal Wheeled-Legged Robot via NMPC and DE Optimization

2026-02-25

AI Summary

This work addresses the challenge of dynamic jumping in wheeled-legged robots, which becomes increasingly difficult with added leg degrees of freedom. To overcome this, the authors propose a synergistic control framework that integrates nonlinear model predictive control (NMPC) with differential evolution (DE)—a novel combination for jumping control in such robots. The approach optimizes jump trajectories while leveraging coordinated wheel motion to enhance takeoff performance. Experimental validation on a custom-built small-scale wheeled-legged robot demonstrates successful execution of diverse maneuvers, including vertical jumps reaching 0.5 m, forward jumps clearing a 0.12 m obstacle, and backflips. Both simulations and real-world tests confirm the effectiveness and superiority of the proposed method.

Technology Category

• Intelligent Robots: Manipulation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Distributed Problem Solving

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Quadrupedal wheeled-legged robots combine the advantages of legged and wheeled locomotion to achieve superior mobility, but executing dynamic jumps remains a significant challenge due to the additional degrees of freedom introduced by wheeled legs. This paper develops a mini-sized wheeled-legged robot for agile motion and presents a novel motion control framework that integrates the Nonlinear Model Predictive Control (NMPC) for locomotion and the Differential Evolution (DE) based trajectory optimization for jumping in quadrupedal wheeled-legged robots. The proposed controller utilizes wheel motion and locomotion to enhance jumping performance, achieving versatile maneuvers such as vertical jumping, forward jumping, and backflips. Extensive simulations and real-world experiments validate the effectiveness of the framework, demonstrating a forward jump over a 0.12 m obstacle and a vertical jump reaching 0.5 m.

Problem

• quadrupedal wheeled-legged robot
• dynamic jumping
• jumping control
• locomotion
• degrees of freedom

Innovation

• NMPC
• Differential Evolution
• wheeled-legged robot
• jumping control
• trajectory optimization