Autonomous Functional Movements in a Tendon-Driven Limb via Limited Experience.

ABSTRACT: Robots will become ubiquitously useful only when they can use few attempts to teach themselves to perform different tasks, even with complex bodies and in dynamical environments. Vertebrates, in fact, use sparse trial-and-error to learn multiple tasks despite their intricate tendon-driven anatomies-which are particularly hard to control because they are simultaneously nonlinear, under-determined, and over-determined. We demonstrate-for the first time in simulation and hardware-how a model-free, open-loop approach allows few-shot autonomous learning to produce effective movements in a 3-tendon 2-joint limb. We use a short period of motor babbling (to create an initial inverse map) followed by building functional habits by reinforcing high-reward behavior and refinements of the inverse map i

SUBMITTER: Marjaninejad A 

PROVIDER: S-EPMC6544439 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature