| Summary: | Autonomous adaptive locomotion over irregular terrain is one important topic in robotics research. Postural control, meaning movement generation for robot legs in order to attain balance, is a first step in this direction. In this article, we focus on the essential issue of modeling the interaction between the central nervous system and the peripheral information in the locomotion context. This issue is crucial for autonomous and adaptive control, and has received little attention so far. This modeling is based on the concept of dynamical systems whose intrinsic robustness against perturbations allows for an easy integration of sensory-motor feedback and thus for closed-loop control. Herein, we focus on achieving balance without locomotion. The developed controller is modeled as discrete, sensory driven corrections of the robot joint values in order to achieve balance. The robot lateral tilt information modulates the generated trajectories thus achieving balance. The system is demonstrated on a quadruped robot which adjusts its posture until reducing the lateral tilt to a minimum.
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