{"id":800,"date":"2010-07-27T13:27:02","date_gmt":"2010-07-27T04:27:02","guid":{"rendered":"http:\/\/www.cns.atr.jp\/bri\/?page_id=800"},"modified":"2018-11-02T14:17:54","modified_gmt":"2018-11-02T05:17:54","slug":"balance","status":"publish","type":"page","link":"https:\/\/bicr.atr.jp\/bri\/en\/research\/balance\/","title":{"rendered":"Postural control"},"content":{"rendered":"
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Compliant Balancing and Push Recovery
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Objective<\/span><\/h3>\n

Balancing (postural control) is one of the fundamental motor functions for humans. Without this ability, we would have difficulty performing daily tasks, even biped walking. This topic is mainly studied in the physiology community, and many hypotheses have been tested on human bodies in physiology and medical contexts. A human being is a hyper-redundant system, and the vast size of its motor commands is determined on-line to solve various motor tasks in different environments.<\/span><\/p>\n

In our project, we are pursuing this crucial research topic by utilizing control theory and machine learning under plausible physiological constraints. If we try to reproduce the same behavior on computer models or robots with similar body functions, we encounter such computational problems involving coordinate transformation and internal model prediction. Our humanoid robot can simulate human musculo-skeletal systems. Using this experimental tool, we explore reasonable control and learning mechanisms for balancing\/walking based on the mechanical properties of the given body. Our humanoid robot\u2019s capability, in some sense, imposes a strong constraint on our approach to study human motor control.<\/span><\/p>\n

We believe that reproducing the similar behaviors of humans on humanoid robots with similar body structure is a fast methodology, not only for understanding our own motor control\/learning mechanisms but also for such practical applications as rehabilitation or the development of human-friendly robots.<\/span><\/p>\n<\/div>\n

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1. Full-body torque control<\/span><\/h3>\n

Humans can control their joint torques. First we implemented a computer program to precisely control whole-body joint torques using force sensors attached to CB-i’s body. Then we developed several motion control algorithms in which the control input is defined as the joint torque. The extra benefit is that we can easily simulate the robot behaviors on multi-body dynamic simulators without considering the actuator dynamics that are required in conventional position-control-based robots.<\/span><\/p>\n

With the full-body torque controller, the robot can freely move its limbs or compensate for gravity to passively follow the external forces applied by humans (see the movie).<\/span><\/p>\n