  In this paper, we present a novel control architecture for the online
adaptation of bipedal locomotion on inclined obstacles. In particular, we
introduce a novel, cost-effective, and versatile foot sensor to detect the
proximity of the robot's feet to the ground (bump sensor). By employing this
sensor, feedback controllers are implemented to reduce the impact forces during
the transition of the swing to stance phase or steeping on inclined unseen
obstacles. Compared to conventional sensors based on contact reaction force,
this sensor detects the distance to the ground or obstacles before the foot
touches the obstacle and therefore provides predictive information to
anticipate the obstacles. The controller of the proposed bump sensor interacts
with another admittance controller to adjust leg length. The walking
experiments show successful locomotion on the unseen inclined obstacle without
reducing the locomotion speed with a slope angle of 12. Foot position error
causes a hard impact with the ground as a consequence of accumulative error
caused by links and connections' deflection (which is manufactured by
university tools). The proposed framework drastically reduces the feet' impact
with the ground.
