| Resumo: | Autonomous adaptive locomotion over irregular terrain is one important topic in robotics research. Balance control, meaning movement generation for robot legs, 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 is an important issue 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. In this article, balance is achieved without locomotion. The developed controller is modeled as discrete, sensory driven corrections of the robot joint values. The robot sagittal tilt information modulates the generated trajectories thus achieving balance. The system is demonstrated on a quadruped robot which adjusts its posture until reducing the sagittal tilt to a minimum.
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