Active Compliance with Stability Compensation

Abstract

It is a widespread idea that animal legged locomotion is better than wheeled locomotion on natural rough terrain. However, the use of legs as a locomotion system for vehicles and robots still has a long way to go before it can compete with wheels and trucks, even on natural ground. This work aims to solve one disadvantages plaguing walking robots: their inability to react to external disturbances (which is also a drawback of wheeled robots. An active-compliance controller with a new term that compensates for stability variations is proposed, thus helping the robot react stably in the face of disturbances. As a result, the approach helps the robot achieve faster, stabler compliant motions than conventional controllers. Experiments performed with the SILO4 quadruped robot show a relevant improvement in the walking gait.

Legged robots are still far from being considered as real locomotion systems in industrial and service applications. Two main obstacle, are found: one is the very low velocity that walking robots feature for stable motion. The second obstacle is that walking robots easily tumble down due to unexpected external and internal disturbances and rarely recover from the fall.

Active compliance has been used to control walking robot gaits successfully and it helps the robot recover from small perturbations. However, when walking on inclined surfaces, or with big disturbances, the compliant motion can itself produce instability. Our goal here is to control the gait by means of an active compliance system. However, we propose to combine it with a dynamic stability measurement, to improve machine speed and stability in the presence of internal and environmental perturbations.

The principle of active compliance in a walking robot consists in controlling the motion of each leg in support so that steady-state force errors at the foot are considered linearly proportional to displacement errors according to Hook's law, or it can also be realized with a velocity servo system as we have done here. Therefore, foot-force errors are converted to foot-velocity errors and later mapped to desired joint speed. Thus the active compliance equation for each supporting leg finds a trade off among desired foot forces, position and velocity.

However, this compliant motion, that seems to be more robust to disturbances, presents a problem: reduces the gait stability margin, which is the lowest stability margin along a gait cycle. This can be a problem when walking uphill or in natural environments, where the gait stability margin usually gets reduced. Therefore, to achieve a compliant and stable motion we propose to combine the active compliance and the dynamic stability controllers to allow their interaction.

To show the improvement on the walking, we have done some experiments with our SILO4 robot as usual.

The first experiment is aimed at showing the better adaptation to the environment and to disturbances that is achieved by using the proposed active compliance with stability compensation. The SILO4 robot has been placed in a 10º-inclined ground and commanded to start walking using first a conventional active-compliance controller and later compared with the proposed active-compliance with stability compensation.

Video 1: SILO4 walking uphill using a conventional Video 2: SILO4 walking uphill using active compliance with stability compensation.