Planning and Control Framework for a Quadruped Robot With Changeable Configuration

Multiconfiguration quadruped robots offer enhanced adaptability and mobility by adopting diverse locomotion morphologies inspired by different biological counterparts. However, their control frameworks remain insufficiently explored. In this paper, a control framework is proposed that integrates a nonlinear constraint‐based whole‐body planner with a hierarchical whole‐body controller. This framework enables configuration switching and multiconfiguration motion on complex terrains. The motion planner formulates an optimal control problem that incorporates nonlinear constraints, such as reference poses, system dynamics, and foothold positions, to compute optimal states and control inputs. Depending on the terrain, the most suitable configuration of the robot is selected, such as mammal‐like or reptile‐like, to effectively traverse complex environments and obstacles. The hierarchical whole‐body controller accurately tracks prioritized motion tasks of the torso and limbs through QP‐based optimization. The proposed framework is validated through real‐world experiments, demonstrating robust and versatile performance across challenging scenarios, including slopes, irregular brick terrain, overhanging obstacles, and dual‐platform bridges.