General in-hand object rotation with vision and touch
We introduce Rotateit, a system that enables fingertip-based object rotation along multiple
axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it …
axes by leveraging multimodal sensory inputs. Our system is trained in simulation, where it …
Sequential dexterity: Chaining dexterous policies for long-horizon manipulation
Many real-world manipulation tasks consist of a series of subtasks that are significantly
different from one another. Such long-horizon, complex tasks highlight the potential of …
different from one another. Such long-horizon, complex tasks highlight the potential of …
The future lies in a pair of tactile hands
NF Lepora - Science Robotics, 2024 - science.org
The future lies in a pair of tactile hands | Science Robotics news careers commentary Journals
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Dexcap: Scalable and portable mocap data collection system for dexterous manipulation
Imitation learning from human hand motion data presents a promising avenue for imbuing
robots with human-like dexterity in real-world manipulation tasks. Despite this potential …
robots with human-like dexterity in real-world manipulation tasks. Despite this potential …
Survey of Learning Approaches for Robotic In-Hand Manipulation
Human dexterity is an invaluable capability for precise manipulation of objects in complex
tasks. The capability of robots to similarly grasp and perform in-hand manipulation of objects …
tasks. The capability of robots to similarly grasp and perform in-hand manipulation of objects …
On the utility of koopman operator theory in learning dexterous manipulation skills
Despite impressive dexterous manipulation capabilities enabled by learning-based
approaches, we are yet to witness widespread adoption beyond well-resourced …
approaches, we are yet to witness widespread adoption beyond well-resourced …
Twisting lids off with two hands
Manipulating objects with two multi-fingered hands has been a long-standing challenge in
robotics, attributed to the contact-rich nature of many manipulation tasks and the complexity …
robotics, attributed to the contact-rich nature of many manipulation tasks and the complexity …
Estimator-coupled reinforcement learning for robust purely tactile in-hand manipulation
This paper identifies and addresses the problems with naively combining (reinforcement)
learning-based controllers and state estimators for robotic in-hand manipulation …
learning-based controllers and state estimators for robotic in-hand manipulation …
TEXterity--Tactile Extrinsic deXterity: Simultaneous Tactile Estimation and Control for Extrinsic Dexterity
We introduce a novel approach that combines tactile estimation and control for in-hand
object manipulation. By integrating measurements from robot kinematics and an image …
object manipulation. By integrating measurements from robot kinematics and an image …
Lessons from Learning to Spin" Pens"
In-hand manipulation of pen-like objects is an important skill in our daily lives, as many tools
such as hammers and screwdrivers are similarly shaped. However, current learning-based …
such as hammers and screwdrivers are similarly shaped. However, current learning-based …