StROL: Stabilized and Robust Online Learning from Humans
Robots often need to learn the human's reward function online, during the current
interaction. This real-time learning requires fast but approximate learning rules: when the …
interaction. This real-time learning requires fast but approximate learning rules: when the …
Task Adaptation in Industrial Human-Robot Interaction: Leveraging Riemannian Motion Policies
In real-world industrial environments, modern robots often rely on human operators for
crucial decision-making and mission synthesis from individual tasks. Effective and safe …
crucial decision-making and mission synthesis from individual tasks. Effective and safe …
Intent Demonstration in General-Sum Dynamic Games via Iterative Linear-Quadratic Approximations
Autonomous agents should be able to coordinate with other agents without knowing their
intents ahead of time. While prior work has studied how agents can gather information about …
intents ahead of time. While prior work has studied how agents can gather information about …
Modeling and analysis of optimal trajectory for 6-DOF robotic arm
KR Qasim, YIA Mashhadany, ET Yassen - AIP Conference …, 2024 - pubs.aip.org
This paper develops and analyzes 6-DOF robotic arm kinetic models. The planned model
permits skylights to be controlled to achieve any position and direction accessible in an …
permits skylights to be controlled to achieve any position and direction accessible in an …
Dual Performance Optimization of 6-DOF Robotic Arm Trajectories in Biomedical Applications
KR Qasim, Y Al Mashhadany, ET Yassen - Tikrit Journal of Engineering …, 2024 - tj-es.com
For the first time, dual-performance perfection technologies were used to kinematically
operate sophisticated robots. In this study, the trajectory development of a robot arm is …
operate sophisticated robots. In this study, the trajectory development of a robot arm is …