A Feedback Strategy for Dextrous Manipulation
نویسنده
چکیده
In a typical dextrous manipulation task, a goal configuration is reached through a sequence of continuous motions. Most often, a motion plan is computed offline and subsequently used as a reference trajectory for a feedback controller. We present an alternative approach that only relies on feedback, no motion planning is necessary. Different feedback controllers are constructed and composed in such a way that the object moves toward the goal configuration. Switches between the controllers are not planned ahead, they result from the feedback itself. Discrete features such as finger gait are therefore generated on-line. The approach is based on our previous results on stabilization of hybrid systems.
منابع مشابه
Learning dextrous manipulation skills using the evolution strategy
This paper presents an approach based on the evolution strategy for autonomous learning of dextrous manipulation primitives with a dextrous robot hand. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning possible. Our system does not rely on simulation; all the experimentation is performed the 16-degree-of-freedom Utah/M...
متن کاملLearning Dextrous Manipulation Skills for Multiingered Robot Hands
We present a method for autonomous learning of dextrous manipulation skills with robot hands. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning tractable. Our approach consists of learning and storing a few manipulation primitives for a few prototypical objects and then using an associative memory to obtain the require...
متن کاملA Machine Learning Approach to Dextrous Manipulation
We present an approach for autonomous learning of dextrous manipulation skills. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning tractable. Our approach consists of learning and storing a few basis manipulation primitives for a few prototypical objects and then using a nearest-neighbor method to compute the required p...
متن کاملLearning Dextrous Manipulation Skills Using Multisensory Information
In this paper we present a method for autonomous learning of dextrous manipulation skills with multiin-gered robot hands. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning tractable. Our approach consists of learning and storing a few basic manipulation primitives for a few prototypical objects and then using an associ...
متن کاملLearning Dextrous Manipulation Skills for Multi ngered Robot Hands
We present a method for autonomous learning of dextrous manipulation skills with mul-tiingered robot hands. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning tractable. Our approach consists of learning and storing a few basic manipulation primitives for a few prototypi-cal objects and then using an associative memory ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002