Categories: AI/ML News

Advancing human-like perception in self-driving vehicles

How can mobile robots perceive and understand the environment correctly, even if parts of the environment are occluded by other objects? This is a key question that must be solved for self-driving vehicles to safely navigate in large crowded cities. While humans can imagine complete physical structures of objects even when they are partially occluded, existing artificial intelligence (AI) algorithms that enable robots and self-driving vehicles to perceive their environment do not have this capability.

Delivery robots’ green credentials make them more attractive to consumers

The smaller carbon footprint, or wheel print, of automatic delivery robots can encourage consumers to use them when ordering food, according to a new study. The suitcase-sized, self-driving electric vehicles are much greener than many traditional food delivery methods because they have low, or even zero, carbon emissions. In this…

August 14, 2024

In "AI/ML News"

Reinforcement learning allows underwater robots to locate and track objects underwater

A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.

July 31, 2023

In "FAANG"

Reinforcement learning allows underwater robots to locate and track objects underwater

A research team has shown for the first time that reinforcement learning—i.e., a neural network that learns the best action to perform at each moment based on a series of rewards—allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.

July 29, 2023

In "AI/ML News"

AI Generated Robotic Content