Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting
mimicrobotics.github.io · 816 words · saved by 1 readers
Smooth Operator is a real-time sampling-based algorithm for kinematic hand retargeting.
1Soft Robotics Lab, ETH Zurich 2Autonomous Systems Lab, Stanford University 3mimic robotics Abstract Advances in learning-based robotic manipulation, such as Vision- Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-quality teleoperation data. Their capabilities are strictly upper-bounded by the quality of the underlying human demonstrations. Current gradient-based retargeting algorithms converge to local minima, resulting in jitter that affects data quality and teleoperation experience. To address this, we introduce the Sampling- Based Retargeter (SBR), a…
saved by
related reading
- FORTE: Tactile Force and Slip Sensing on Compliant Fingers for Delicate Manipulationarxiv.org
- Generating Robot Hands from Human Demonstrationsarxiv.org
- Precise Manipulation with Efficient Online RLpi.website
- Diffusion Policy: Visuomotor Policy Learning via Action Diffusiondiffusion-policy.cs.columbia.edu
- A Unified Model for Motion-Conditioned Robot Co-designtransformer-transformer.github.io
- Differentiable Robot Renderingdrrobot.cs.columbia.edu
- OSMO: Open-Source Tactile Glove for Human-to-Robot Skill Transferarxiv.org
- Emergent Dexterity via Diverse Resets and Large-Scale Reinforcement Learningarxiv.org
- ManipulationNet: An Infrastructure for Benchmarking Real-World Robot Manipulation with Physical Skill Challenges and Embodied Multimodal Reasoningh2t.iar.kit.edu
- Scalable Behavior Cloning with Open Data, Training, and Evaluationabc.bot
- Development of a High-speed Multifingered Hand System and Its Application to Catchingishikawa-vision.org
- A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulationtoyotaresearchinstitute.github.io