<p>Animals can adapt to their surroundings by modifying their trunk morphology, whereas legged robots currently utilize rigid trunks. This study introduces a single-degree-of-freedom (DoF), six-revolute (6R) morphing trunk mechanism designed to equip legged robots with variable-width capabilities. Subsequently, a morphology-aware locomotion learning pipeline, based on reinforcement learning, is proposed for real-time trunk-width deformation and adaptive legged locomotion. The proposed variable-width trunk is integrated into a quadrupedal robot, and the learning pipeline is employed to train the adaptive locomotion controller of this robot. This study has three key contributions: (1) An overconstrained morphing mechanism is designed to achieve single-DoF trunk-width deformation, thereby minimizing power consumption and simplifying motion control. (2) A novel morphology-adaptive learning pipeline is introduced that utilizes adversarial joint-level motion imitation to ensure coordination consistency during morphological adaptation. This method addresses dynamic disturbances and interlimb coordination disruptions caused by width modifications. (3) A historical proprioception-based asymmetric neural network architecture is utilized to attain implicit terrain perception without visual input. Collectively, these developments enable the proposed variable-width legged robot to maintain consistent locomotion across complex terrains and facilitate rapid width deformation in response to environmental changes. Extensive simulation experiments validate the proposed design and control methodology.</p>