1. This document discusses robots that utilize their own structure and morphology for locomotion and activity. It provides examples of robots that rely on physical dynamics and morphology for control rather than complex software or sensing.
2. Specific examples discussed include hopping robots that use the natural vibration of their structure for energy-efficient hopping, passive dynamic walkers that can walk solely through interaction with gravity and friction without actuation or control, and soft robots whose flexible materials and pneumatic networks allow intrinsically compliant motion.
3. The document argues that utilizing a robot's physical structure and materials for control can reduce the computational and sensing demands compared to systems relying solely on software control. This morphological computation is inspired by principles observed in biological systems
1. This document discusses robots that utilize their own structure and morphology for locomotion and activity. It provides examples of robots that rely on physical dynamics and morphology for control rather than complex software or sensing.
2. Specific examples discussed include hopping robots that use the natural vibration of their structure for energy-efficient hopping, passive dynamic walkers that can walk solely through interaction with gravity and friction without actuation or control, and soft robots whose flexible materials and pneumatic networks allow intrinsically compliant motion.
3. The document argues that utilizing a robot's physical structure and materials for control can reduce the computational and sensing demands compared to systems relying solely on software control. This morphological computation is inspired by principles observed in biological systems
This slide is my presentation for a reading circle "Machine Learning Professional Series".
Japanese version is here.
http://www.slideshare.net/matsukenbook/ss-50545587
Introduction of Chainer, a framework for neural networks, v1.11. Slides used for the student seminar on July 20, 2016, at Sugiyama-Sato lab in the Univ. of Tokyo.
This slide is my presentation for a reading circle "Machine Learning Professional Series".
Japanese version is here.
http://www.slideshare.net/matsukenbook/ss-50545587
Introduction of Chainer, a framework for neural networks, v1.11. Slides used for the student seminar on July 20, 2016, at Sugiyama-Sato lab in the Univ. of Tokyo.