Gravitational forces can induce deviations in body posture from desired configurations in multi-legged arboreal robot locomotion with low leg stiffness, affecting the contact angle between the swing leg's end-effector and the climbing surface during the gait cycle. The relationship between desired and actual foot positions is investigated here in a leg-stiffness-enhanced model under external forces, focusing on the challenge of unreliable end-effector attachment on climbing surfaces in such robots. Inspired by the difference in ceiling attachment postures of dead and living geckos, feedforward compensation of the stance phase legs is the key to solving this problem. A feedforward gravity compensation (FGC) strategy, complemented by leg coordination, is proposed to correct gravity-influenced body posture and improve adhesion stability by reducing body inclination. The efficacy of this strategy is validated using a quadrupedal climbing robot, EF-I, as the experimental platform. Experimental validation on an inverted surface (ceiling walking) highlight the benefits of the FGC strategy, demonstrating its role in enhancing stability and ensuring reliable end-effector attachment without external assistance. In the experiment, robots without FGC only completed in 3 out of 10 trials, while robots with FGC achieved a 100\% success rate in the same trials. The speed was substantially greater with FGC, achieved 9.2 mm/s in the trot gait. This underscores the proposed potential of FGC strategy in overcoming the challenges associated with inconsistent end-effector attachment in robots with low leg stiffness, thereby facilitating stable locomotion even at inverted body attitude.

翻译：重力作用会导致多足仿生机器人在低腿部刚度条件下的树栖运动中出现身体姿态偏离预期构型，进而影响摆动腿末端执行器与攀爬表面在步态周期中的接触角度。本文针对此类机器人在攀爬表面末端执行器附着不可靠的挑战，在考虑外力作用的腿部刚度增强模型中研究了期望足端位置与实际足端位置的关系。受死亡与存活壁虎在倒置表面附着姿态差异的启发，支撑相腿的前馈补偿是解决该问题的关键。本文提出了一种结合腿部协调的前馈重力补偿（FGC）策略，通过纠正受重力影响的身体姿态并减小身体倾斜角来提高附着稳定性。以四足攀爬机器人EF-I为实验平台验证了该策略的有效性。在倒置表面（天花板行走）的实验验证凸显了FGC策略的优势，证明了其在无需外部辅助条件下增强稳定性、确保末端执行器可靠附着的作用。实验中，未采用FGC的机器人仅在10次试验中成功3次，而采用FGC的机器人在相同试验中实现了100%的成功率。采用FGC时采用踱步步态可实现9.2 mm/s的显著更高速度。这充分表明了所提出的FGC策略在克服低腿部刚度机器人末端执行器附着不一致挑战方面的潜力，从而在倒置姿态下也能实现稳定运动。