Teleoperation serves as a powerful method for collecting on-robot data essential for robot
learning from demonstrations. The intuitiveness and ease of use of the teleoperation system …

Vision-Language-Action (VLA) models have shown remarkable potential in visuomotor
control and instruction comprehension through end-to-end learning processes. However …

Learned language-conditioned robot policies often struggle to effectively adapt to new real-
world tasks even when pre-trained across a diverse set of instructions. We propose a novel …

Reinforcement learning (RL) is one of the active fields in machine learning, demonstrating
remarkable potential in tackling real-world challenges. Despite its promising prospects, this …

Robots can use visual imitation learning (VIL) to learn manipulation tasks from video
demonstrations. However, translating visual observations into actionable robot policies is …

Robot-assisted feeding has the potential to improve the quality of life for individuals with
mobility limitations who are unable to feed themselves independently. However, there exists …

This paper presents Words2Contact, a language-guided multi-contact placement pipeline
leveraging large language models and vision language models. Our method is a key …

It has been an ambition of many to control a robot for a complex task using natural language
(NL). The rise of large language models (LLMs) makes it closer to coming true. However, an …

In recent years roboticists have achieved remarkable progress in solving increasingly
general tasks on dexterous robotic hardware by leveraging high capacity Transformer …

The ability to reflect on and correct failures is crucial for robotic systems to interact stably with
real-life objects. Observing the generalization and reasoning capabilities of Multimodal …