Evolution of machine learning algorithms on autonomous robots

M Mainampati… - 2020 10th Annual …, 2020 - ieeexplore.ieee.org
In this paper, an overview of the use of machine learning algorithms on autonomous robotic
systems is presented. The concept of hardware and software integration and development is …

Artificial intelligence (ai) framework for multi-modal learning and decision making towards autonomous and electric vehicles

G Ramesh, J Praveen - E3S Web of Conferences, 2021 - e3s-conferences.org
An electric vehicle with autonomous driving is a possibility provided technology innovations
in multi-disciplinary approach. Electric vehicles leverage environmental conditions and are …

Check for updates Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning

M Kogan, J Karns - … , EvoApplications 2022, Held as Part of …, 2022 - books.google.com
Selecting an appropriate neural architecture for a given dataset is an open problem in
machine learning. Neuroevolution algorithms, such as NEAT, have shown great promise in …

Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning

M Kogan, J Karns, T Desell - … of Evolutionary Computation (Part of EvoStar …, 2022 - Springer
Selecting an appropriate neural architecture for a given dataset is an open problem in
machine learning. Neuroevolution algorithms, such as NEAT, have shown great promise in …

Linear-Quadratic Regulator Design for the Control of a Differential Drive Ground Robot: Quanser QBot 2

V Longi - 2018 - search.proquest.com
Autonomous ground vehicles have gained considerable popularity in recent years for a wide
variety of applications, in fields such as the industrial, logistics, and agricultural. One class of …