Question: How many types of objects are shown in the teaser image of the paper 'Lessons from Learning to Spin “Pens”'? (Please provide a number)
Date: 2024-06-03

Search results:

[2407.18902] Lessons from Learning to Spin "Pens" - arXiv.org
Lessons from Learning to Spin "Pens". Jun Wang, Ying Yuan, Haichuan Che, Haozhi Qi, Yi Ma, Jitendra Malik, Xiaolong Wang. View a PDF of the paper titled Lessons from Learning to Spin "Pens", by Jun Wang and 6 other authors. In-hand manipulation of pen-like objects is an important skill in our daily lives, as many tools such as hammers and ...

Lessons from Learning to Spin "Pens" - arXiv.org
3 Learning to Spin Pens. An overview of our method is shown in Figure 2. Our method consists of three steps. First, we train an oracle policy with privileged information to generate realistic trajectories in simulation. With these trajectories, we pre-train a sensorimotor policy in simulation.

Lessons from Learning to Spin "Pens"
The dynamic skill of spinning pens with a robotic hand is nearly impossible to achieve with human teleoperation and imitation learning alone. Reinforcement learning in simulation is critical for exploring feasible motion. Only a few real-world trajectories are needed for fine-tuning. Although a proprioceptive policy learned purely in simulation ...

[2407.18902] Lessons from Learning to Spin "Pens"
However, current learning-based methods struggle with this task due to a lack of high-quality demonstrations and the significant gap between simulation and the real world. In this work, we push the boundaries of learning-based in-hand manipulation systems by demonstrating the capability to spin pen-like objects.

Paper page - Lessons from Learning to Spin "Pens" - Hugging Face
In this work, we push the boundaries of learning-based in-hand manipulation systems by demonstrating the capability to spin pen-like objects. We first use reinforcement learning to train an oracle policy with privileged information and generate a high-fidelity trajectory dataset in simulation. This serves two purposes: 1) pre-training a ...

Lessons from Learning to Spin "Pens" - NASA/ADS
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 methods struggle with this task due to a lack of high-quality demonstrations and the significant gap between simulation and the real world. In this work, we push the boundaries of learning-based in-hand ...

Lessons from Learning to Spin"Pens" - Semantic Scholar
However, current learning-based methods struggle with this task due to a lack of high-quality demonstrations and the significant gap between simulation and the real world. In this work, we push the boundaries of learning-based in-hand manipulation systems by demonstrating the capability to spin pen-like objects.

Xiaolong Wang
Lessons from Learning to Spin "Pens". arXiv, 2024. [project page] ... Real-Time Bimanual Dexterous Teleoperation for Imitation Learning. arXiv, 2024. [project page] Kang-Won Lee, Yuzhe Qin, Xiaolong Wang, Soo-Chul Lim. ... Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation.

Answer: 12