Human-inspired bipedal locomotion: from neuromechanics to mathematical modelling and robotic applications

Human bipedal locomotion arises from continuous, closed-loop interactions between neural control and biomechanical structure-collectively referred to as neuromechanics. The relationship between human locomotion and robotic locomotion is deeply interconnected through shared principles of neuromechanics, thereby providing a comprehensive framework for understanding human movement and informing robotic system design. In this review, we synthesize insights from neuroscience, biomechanics, computational modelling and robotics to establish a cohesive perspective on human-inspired bipedal locomotion. We begin by outlining essential anatomical and physiological principles, such as spinal circuits, supraspinal coordination and musculoskeletal structure. Next, we analyse mathematical models-ranging from simplified neural oscillators to complex musculoskeletal simulations-that formalize these mechanisms. Finally, we discuss the embodiment of these models in bipedal robots, which promotes reciprocal advancements in both biological understanding and engineering innovation. Rather than offering a comprehensive literature survey, we focus on pivotal developments, emerging trends and unresolved questions that shape this interdisciplinary domain. By integrating diverse fields, this review aims to enhance the design of agile, energy-efficient robots and deepen our understanding of human locomotion.