Molecular robots guided by prescriptive landscapes
نویسندگان
چکیده
منابع مشابه
Chapter 2 Molecular Robots Guided by Prescriptive
Traditional robots [Siegwart, 2004] rely for their function on computing to store internal representations of their goals and environment and to coordinate sensing and any actuating of components required in response. Moving robotics to the single-molecule level is possible in principle, but faces the limited ability of individual molecules to store complex information and programs. One strateg...
متن کاملAppendix A Partial Supplementary Material for Molecular Robots Guided by Prescriptive
Robots are often defined by their ability to sense their environment, perform computations, and take actions; as such, they have revolutionized our ability to automate factories, send autonomous vehicles to remote or dangerous locations, and improve our daily lives. The potential for autonomous sensing and acting at the molecular scale is illustrated by the sophisticated machinery within biolog...
متن کاملVisually Guided Mobile Robots
Our mobile robots use trinocular stereo sensors to sense their environment, navigate around obstacles in a dynamic, unknown world and partner with humans in various tasks. Fundamental to these abilities is the capacity to build a map and locate themselves relative to it, while operating. Here we review a collection of methods that permit mobile robots to acquire spatial and visual maps of their...
متن کاملEvolving Visually Guided Robots
We have developed a methodology grounded in two be liefs that autonomous agents need visual processing ca pabilities and that the approach of hand designing con trol architectures for autonomous agents is likely to be superseded by methods involving the arti cial evolution of comparable architectures In this paper we present results which demonstrate that neural network control architectures ca...
متن کاملextremal region detection guided by maxima of gradient magnitude
a problem of computer vision applications is to detect regions of interest under dif- ferent imaging conditions. the state-of-the-art maximally stable extremal regions (mser) detects affine covariant regions by applying all possible thresholds on the input image, and through three main steps including: 1) making a component tree of extremal regions’ evolution (enumeration), 2) obtaining region ...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature
سال: 2010
ISSN: 0028-0836,1476-4687
DOI: 10.1038/nature09012