Dexterous Manipulation:
Learning and Control with Diverse Modalities

CoRL 2025 Workshop PROPOSAL

Introduction

Fine manipulation involves making precise movements with robotic hands and fingers to handle small objects or perform intricate tasks, such as threading a needle. Dexterous manipulation goes further, requiring highly skilled, accurate, and versatile manipulation of objects through complex interactions among multiple fingers and joints. The ability to achieve fine and dexterous manipulation with high speed, accuracy, and dexterity is becoming increasingly important in robotics research. However, it also poses many challenges, such as frequent making and breaking of contact, real-time feedback control with high-dimensional observations, high-dimensional control spaces, and objects being in unstable configurations. Traditional methods rely on precise robot and environment models but often struggle with real-world uncertainties and lack generalizability. Despite decades of research, most demonstrations of dexterous manipulation still rely heavily on teleoperation. Achieving robust and generalizable dexterous manipulation requires advancements in perception integration, data collection, and control. Advances in robot learning, including machine learning and transfer learning, offer promising pathways to enhance robotic performance in fine and dexterous manipulation tasks. This event seeks to convene researchers from diverse disciplines to share insights on pushing this critical boundary.

This workshop aims to bring together junior and senior researchers to discuss the latest advancements, challenges, and future directions in learning-based approaches for robot fine manipulation skills, one of the most challenging areas in robotics. We will delve into the current state-of-the-art across relevant areas, including the hardware and mechanical design of dexterous manipulators, generalizable skill learning techniques, and sensing modalities such as tactile sensors and vision systems. Researchers will have opportunities to present posters, give contributed talks, and engage in thought-provoking discussions.

We will explore the following focused research questions:

Synergy between Learning and Control Perception: Seeing & Feeling the World Hardware: Redesigning Dexterous Hands Scaling Robot Skill Learning Reinforcement Learning and Demonstration Data

Invited Speakers


Call for Papers/Demos

In this workshop, our goal is to bring together researchers from various fields of robotics, such as control, optimization, learning, planning, sensing, hardware, etc., who work on dexterous manipulation. We encourage researchers to submit work in the following areas (the list is not exhaustive):

Submission Guidelines

Timeline

TBD

Workshop Schedule

Schedule

Time (UTC+9, Korean Standard Time) Event
09:30 - 09:35 Workshop Introduction
09:35 - 10:00 Invited Talk 1 and Q&A
10:00 - 10:30 Spotlight Session 1
10:30 - 11:30 Poster / Demo Session
11:30 - 12:00 Invited Talk 3 and Q&A
12:00 - 12:30 Invited Talk 4 and Q&A
12:30 - 13:30 Lunch Break
13:30 - 14:00 Invited Talk 5 and Q&A
14:00 - 14:30 Invited Talk 6 and Q&A
14:30 - 15:30 Poster / Demo Session
15:30 - 16:25 Panel Discussion
16:25 - 16:30 Closing Remark & Award

Organizers

Contact

For questions and comments, please contact us.
© CoRL 2025 Learning Dexterous Manipulation Workshop