🤖 AI Summary
Legged robots operating in non-inertial environments—such as moving, tilting, or accelerating platforms—face significant challenges in motion reliability, as conventional approaches relying on static-ground assumptions become inadequate. This work presents the first systematic review of dynamic modeling, state estimation, and robust control strategies tailored to such scenarios, offering a thorough analysis of the underlying causes of performance degradation. It clarifies critical open issues, including robot–environment coupling, observability limitations, and experimental validation gaps. By integrating biologically inspired strategies with a holistic system-level design perspective, the study establishes a comprehensive technical framework for legged locomotion in dynamically complex real-world settings, thereby providing both theoretical foundations and a forward-looking research roadmap for achieving high-reliability motion control.
📝 Abstract
Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environments, where the supporting ground moves, tilts, or accelerates. Such conditions arise in ground transportation, maritime platforms, and aerospace settings, and they introduce persistent time-varying disturbances that break the stationary-ground assumptions underlying conventional legged locomotion. This survey reviews the state of the art in modeling, state estimation, and control for legged robots in non-inertial environments. We summarize representative application domains and motion characteristics, analyze the root causes of locomotion performance degradation, and review existing methods together with their key assumptions and limitations. We further identify open problems in robot-environment coupling, observability, robustness, and experimental validation, and discuss future directions in autonomy, system-level design, bio-inspired strategies, safety, and testing. The survey aims to clarify the technical foundations of this emerging area and support the development of reliable legged robots for real-world dynamic environments.