How AI could enable autonomous robot workers in workplaces—and maybe homes

In a world where self-driving robotaxis glide through major city streets without drivers behind the wheel and delivery drones ...
Tech Xplore

Researchers discover a smarter way to solve vehicle routing problems using adaptive swarm learning

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Aerospace and Mechanical Insider on MSN

Landmark-driven DRL boosts mobile robot navigation

Mobile robots are increasingly deployed in applications ranging from household cleaning to hazardous industrial inspection, ...
GitHub

Reinforcement Learning in Python

Sichkar V. N. "Reinforcement Learning Algorithms in Global Path Planning for Mobile Robot", 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi, ...
Purdue University

Brain-inspired AI hardware helps autonomous devices operate efficiently and independently

WEST LAFAYETTE, Ind. — The human brain constantly makes decisions without us noticing. It requires minimal power to move our bodies in the desired direction or avoid an object. A Purdue University ...
GitHub

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning

Architecture Modular pipeline with object detection, mapping, and planning End-to-end policy network End-to-end framework without middle modules, avoiding error ...
Analytics Insight

Machine Learning Algorithms for Robotic Path Planning

These include such learning paradigms as Q-Learning and the Deep Q-Networks setups. Reinforcement Learning paradigms essentially aim at teaching robots to undertake certain actions that will be used ...
acm.org

A Brief History of Embodied Artificial Intelligence, and its Outlook

Embodied Artificial Intelligence (EAI) integrates artificial intelligence into physical entities like robots, endowing them with the ability to perceive, learn from, and dynamically interact with ...
IEEE

Robot Training and Navigation through the Deep Q-Learning Algorithm

Abstract: The paper aims to present the results of an assessment of adherence to the Deep Q-learning algorithm, applied to a vehicular navigation robot. The robot's job was to transport parts through ...