With the increasing demand for the dexterity of robotic operation, dexterous manipulation of
multi-fingered robotic hands with reinforcement learning is an interesting subject in the field …

We introduce Diffusion Policy Policy Optimization, DPPO, an algorithmic framework
including best practices for fine-tuning diffusion-based policies (eg Diffusion Policy) in …

Humans excel at dexterous manipulation; however, achieving human-level dexterity
remains a significant challenge for robots. Technological breakthroughs in the design of …

Humans are capable of completing a range of challenging manipulation tasks that require
reasoning jointly over modalities such as vision, touch, and sound. Moreover, many such …

Generating human-like behavior on robots is a great challenge especially in dexterous
manipulation tasks with robotic hands. Scripting policies from scratch is intractable due to …

Industries, such as manufacturing, are accelerating their embrace of the metaverse to
achieve higher productivity, especially in complex industrial scheduling. In view of the …

Recent advances in behavior cloning (BC), like action-chunking and diffusion, have led to
impressive progress. Still, imitation alone remains insufficient for tasks requiring reliable and …

This paper uses robot programming techniques, such as Deep Q Network, Artificial Neural
Network, and Artificial Deep Q Network, to address challenges related to controlling robotic …

The emergency collision avoidance capabilities of autonomous vehicles (AVs) are crucial for
enhancing their active safety performance, particularly in extreme scenarios where standard …

Introduction Robotic assembly tasks require precise manipulation and coordination, often
necessitating advanced learning techniques to achieve efficient and effective performance …