A data-driven environmental planning framework strengthens climate governance through quality control standards, interdisciplinary expertise, and predictive emission modeling. By integrating ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate ...

This project focuses on system identification and PID controller design using measured response data. The objective was to model the system dynamics and improve performance through closed-loop control ...

This repository contains MATLAB codes for solving Linear Quadratic Regulator (LQR) problems using model-free Reinforcement Learning (RL) techniques. It includes methods such as Policy Iteration, Value ...

Mouse primary motor and somatosensory cortices contain detailed information about the many time-varying arm and paw joint angles during reaching and grasping, implying a 'low-level' role in ...

Abstract: The first course of control is under a critical review. Both the teaching material covered and the teaching methods require new considerations. Introducing interactivity in the education ...

The integration of deep reinforcement learning with PD control in humanoid robots enhances gait stability and patient comfort during lower limb rehabilitation.

Abstract: Effective thermal management is of paramount importance to the reliable and safe operation of electric vehicle (EV) batteries. Most traditional single-zone battery thermal management systems ...

During the acquisition of correct rejection response, rankings of functional connection separated for cortical and subcortical regions, which is predictive of the peak timing of visual information ...

Allen Control Systems (ACS), a leader in autonomous precision robotics, today announced the tripling of its Austin, Texas operations to more than 57,000 square feet to meet the de ...