Learning Variable Impedance Control for Contact Sensitive Tasks
نویسندگان
چکیده
منابع مشابه
Learning Variable Impedance Control Learning Variable Impedance Control
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not t...
متن کاملLearning variable impedance control
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not t...
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One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not t...
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A human performs a variety of skillful movements by adjusting dynamic characteristics of his or her musculoskeletal system according to a task involved. Such characteristics of human movements can be described by mechanical impedance parameters. If the regulation mechanism of human impedance properties during the task can be clarified and modeled, there is a possibility that human skillful stra...
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Biological motor control is capable of learning complex movements containing contact transitions and unknown force requirements while adapting the impedance of the system. In this work, we seek to achieve robotic mimicry of this compliance, employing stiffness only when it is necessary for task completion. We use path integral reinforcement learning which has been successfully applied on torque...
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ژورنال
عنوان ژورنال: IEEE Robotics and Automation Letters
سال: 2020
ISSN: 2377-3766,2377-3774
DOI: 10.1109/lra.2020.3011379