This paper introduces a novel approach to interactive robots by leveraging the form-factor of
cards to create thin robots equipped with vibrational capabilities for locomotion and haptic …

This study focuses on the locomotion capability improvement in a tendon-driven soft
quadruped robot through an online adaptive learning approach. Leveraging the inverse …

Despite numerous improvements regarding the sample-efficiency of Reinforcement
Learning (RL) methods, learning from scratch still requires millions (even dozens of millions) …

To perform versatile mobile manipulation tasks in human-centered environments, the ability
to efficiently transfer learned tasks and experiences from one robot to another or across …

Generalist robot manipulation policies (GMPs) have the potential to generalize across a
wide range of tasks, devices, and environments. However, existing policies continue to …

Recent advances in artificial intelligence have been fueled by the development of
foundation models such as BERT, GPT, T5, and Vision Transformers. These models are first …

While contemporary reinforcement learning research and applications have embraced
policy gradient methods as the panacea of solving learning problems, value-based methods …

Robot manipulation with simulation has become a mainstream approach in the robotics field
recently. It entails lower risk and cost compared to direct training a real robot. Various …

Abstract 3D concrete printing has the potential to substantially impact the construction
industry. Nevertheless, the physical processes are not yet fully understood often resulting in …

In spite of the rapid advancements in AI, tasks like laundry, tidying, and general household
assistance remain challenging for robots due to their limited capacity to generalize …