Touch the Invisible Sky

This is a book funded by NASA to develop a way to let people who cannot see - read what space looks like through their fingers. The book is filled with color images captured from telescopes. Each image is embossed with lines, bumps and texture that denote the the size shape and feel of things shown in the image.

Even the colors are denoted in the textures on the picture... even though they may not be sure of the true empact of the color itself. The pages give them tactile variations in the surface that which allow a sense of what is created by those colors. Then after reading what causes those colors from the brail pages they can get a better understanding of outer space in a way the blind had no possiblity to understand before.

Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination

Abstract
A central goal of robotics and AI is to be able to de- ploy an agent to act autonomously in the real world over an extended period of time. It is commonly asserted that in order to do so, the agent must be able to learn to deal with unexpected environmental conditions. However an ability to learn is not suf- ficient. For true extended autonomy, an agent must also be able to recognize when to abandon its cur- rent model in favor of learning a new one; and how to learn in its current situation. This paper presents a fully implemented example of such autonomy in the context of color map learning on a vision-based mobile robot for the purpose of image segmenta- tion. Past research established the ability of a robot to learn a color map in a single fixed lighting con- dition when manually given a “curriculum,” an ac- tion sequence designed to facilitate learning. This paper introduces algorithms that enable a robot to i) devise its own curriculum; and ii) recognize when the lighting conditions have changed sufficiently to warrant learning a new color map.

Read the Paper.

Okay, super nerdy. But the investigation into artificial intelligence is fascinating. Color input and the ability to recognize inputs and make decisions about abandoning current models in favor of learning a new one... um, super cool. Autonomy at is purest, more terrifying.