RoboCup @Home: Service Robotics Competition

Acquiring Data for Learning

Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.

Compliant Control for Robots: Impedance and Variable Stiffness

Explores compliant control for robots through impedance and variable stiffness, enabling safe and adaptive interactions with the environment.

Robots: Safe Collaboration

Covers challenges and solutions for robots to work safely with humans, emphasizing adaptability and predictability.

Improving Robot Design: Data-Driven Approaches

Explores data-driven approaches to improve robot design, focusing on compliance, soft materials, and complex interactions.

Learning Physically-Consistent Gaussian Mixture Model

Explores Physically-Consistent Gaussian Mixture Models for robot control and trajectory learning.