摘要Biological systems such as mountain goats and felines exhibit remarkable agility and adaptability when traversing com-plex terrains.Inspired by these capabilities,quadruped robots have been developed to mimic legged locomotion and improve mobility over uneven environments.To further enhance locomotion efficiency and terrain versatility,wheeled-legged robots integrate wheels and legs into a hybrid platform,enabling both high-speed traversal and robust ground contact in unstructured terrain.However,planning coordinated locomotion across diverse terrains remains challenging due to the nonlinear dynamics,complex terrain contact constraints,and multimodal locomotion capabilities.In this paper,we propose a real-time,integrated planning framework that jointly optimizes gait scheduling,footstep placement,and whole-body motion trajectories.Our method adopts a two-stage approach.First,a sampling-based planner generates candidate gait sequences and nominal footstep targets based on terrain features and kinematic feasibility.Second,a constrained trajectory optimizer reformulates the planning problem as a Quadratic Programming(QP)task to compute dynamically feasible base trajectories and corresponding ground reaction forces.This hybrid formulation balances planning efficiency and physical realism.The planned trajectories and contact forces are tracked using a hierarchical control architecture combining Model Predictive Control(MPC)and Whole-Body Control(WBC),enabling fast and stable execution on real hardware.Simulation and real-world experiments demonstrate that our approach enables adaptive gait transitions and improves terrain adaptability compared to traditional planners.