New algorithm encourages robots to move more randomly to collect more diverse data for learning. In tests, robots started with no knowledge and then learned and correctly performed tasks within a single attempt. New model could improve safety and practicality of self-driving cars, delivery drones and more.
Today's robots are stuck—their bodies are usually closed systems that can neither grow nor self-repair, nor adapt to their environment. Now, scientists at Columbia University have developed robots that can physically "grow," "heal," and improve themselves by integrating material from their environment or from other robots.
Home robots could assist humans with the completion of various chores and manual tasks, ranging from washing dishes or doing the laundry to cooking, cleaning and tidying up. While many roboticists and computer scientists have tried to improve the skills of home robots in recent years, many of the robots…
While the capabilities of robots have improved significantly over the past decades, they are not always able to reliably and safely move in unknown, dynamic and complex environments. To move in their surroundings, robots rely on algorithms that process data collected by sensors or cameras and plan future actions accordingly.