Anisotropic compliance of robot legs improves recovery from swing-phase collisions

Abstract

vertical limb stiffness enabled the leg to move upwards more freely. The virtual compliance methods slightly increased variability along the limb's planned pathway, but the anisotropic compliance control improved the successful negotiation of step obstacles by over 70% compared to isotropic compliance and positional control methods. We confirmed these findings in simulation and using a self-propelling bipedal robot walking along a linear rail over bumpy terrain. While the importance of limb compliance for stance interactions have been known, our results highlight how limb compliance in the swing-phase can enhance walking performance in naturalistic environments.