Top Tweets for #simulatelypapers
#SimulatelyPapers | May 29, 2025
π DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation π https://t.co/0QwdpHKcLM
π SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning π https://t.co/L0tc9Ht48P | [Project](https://t.co/fEoli6PwHS)
π LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents π https://t.co/TMD5N1IrH7
π FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control π https://t.co/TMBJ0wMayZ
π Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt π https://t.co/Otb1bWLZ89
π Learning Unified Force and Position Control for Legged Loco-Manipulation π https://t.co/bCiyruZVMR
π Hume: Introducing System-2 Thinking in Visual-Language-Action Model π https://t.co/tdH6nSVTQm
π CLAMP: Crowdsourcing a LArge-scale in-the-wild haptic dataset with an open-source device for Multimodal robot Perception π https://t.co/KNT2SkGaKo | [Project](https://t.co/zYgleu2ShT)
π MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation π https://t.co/HS1H3J0kOI
π Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance π https://t.co/gYSxqPtsYT
π ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning π https://t.co/cEeYXHRQZW | [Project](https://t.co/dEanxRhHYM)
π EgoZero: Robot Learning from Smart Glasses π https://t.co/9wQUHnaUJh | [Project](https://t.co/OYA6IvH26s.)
Find more daily insights here: https://t.co/nXJyIf9GmN
π LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents π https://t.co/TMD5N1IrH7
π FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control π https://t.co/TMBJ0wMayZ
π Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt π https://t.co/Otb1bWLZ89
π Learning Unified Force and Position Control for Legged Loco-Manipulation π https://t.co/bCiyruZVMR
π Hume: Introducing System-2 Thinking in Visual-Language-Action Model π https://t.co/tdH6nSVTQm
π CLAMP: Crowdsourcing a LArge-scale in-the-wild haptic dataset with an open-source device for Multimodal robot Perception π https://t.co/KNT2SkGaKo | [Project](https://t.co/zYgleu2ShT)
π MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation π https://t.co/HS1H3J0kOI
π Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance π https://t.co/gYSxqPtsYT
π ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning π https://t.co/cEeYXHRQZW | [Project](https://t.co/dEanxRhHYM)
π EgoZero: Robot Learning from Smart Glasses π https://t.co/9wQUHnaUJh | [Project](https://t.co/OYA6IvH26s.)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GtImk2DaoAA9sbB.jpg)
π LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents π https://t.co/TMD5N1IrH7
π FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control π https://t.co/TMBJ0wMayZ
π Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt π https://t.co/Otb1bWLZ89
π Learning Unified Force and Position Control for Legged Loco-Manipulation π https://t.co/bCiyruZVMR
π Hume: Introducing System-2 Thinking in Visual-Language-Action Model π https://t.co/tdH6nSVTQm
π CLAMP: Crowdsourcing a LArge-scale in-the-wild haptic dataset with an open-source device for Multimodal robot Perception π https://t.co/KNT2SkGaKo | [Project](https://t.co/zYgleu2ShT)
π MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation π https://t.co/HS1H3J0kOI
π Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance π https://t.co/gYSxqPtsYT
π ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning π https://t.co/cEeYXHRQZW | [Project](https://t.co/dEanxRhHYM)
π EgoZero: Robot Learning from Smart Glasses π https://t.co/9wQUHnaUJh | [Project](https://t.co/OYA6IvH26s.)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GtImk0kboAAqVYv.jpg)
π LabUtopia: High-Fidelity Simulation and Hierarchical Benchmark for Scientific Embodied Agents π https://t.co/TMD5N1IrH7
π FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control π https://t.co/TMBJ0wMayZ
π Learning Generalizable Robot Policy with Human Demonstration Video as a Prompt π https://t.co/Otb1bWLZ89
π Learning Unified Force and Position Control for Legged Loco-Manipulation π https://t.co/bCiyruZVMR
π Hume: Introducing System-2 Thinking in Visual-Language-Action Model π https://t.co/tdH6nSVTQm
π CLAMP: Crowdsourcing a LArge-scale in-the-wild haptic dataset with an open-source device for Multimodal robot Perception π https://t.co/KNT2SkGaKo | [Project](https://t.co/zYgleu2ShT)
π MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation π https://t.co/HS1H3J0kOI
π Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance π https://t.co/gYSxqPtsYT
π ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning π https://t.co/cEeYXHRQZW | [Project](https://t.co/dEanxRhHYM)
π EgoZero: Robot Learning from Smart Glasses π https://t.co/9wQUHnaUJh | [Project](https://t.co/OYA6IvH26s.)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GtImk0hbMAYL9tC.jpg)
#SimulatelyPapers | February 26, 2025
π OpenFly: A Versatile Toolchain and Large-scale Benchmark for Aerial Vision-Language Navigation π https://t.co/M0KT2eAEpt
π Impact of Object Weight in Handovers: Inspiring Robotic Grip Release and Motion from Human Handovers π https://t.co/R8U5uxb5fN
π FetchBot: Object Fetching in Cluttered Shelves via Zero-Shot Sim2Real π https://t.co/MiX111dHl4
π From planning to policy: distilling $\texttt{Skill-RRT}$ for long-horizon prehensile and non-prehensile manipulation π https://t.co/1V6AI3Rc7g
π Retrieval Dexterity: Efficient Object Retrieval in Clutters with Dexterous Hand π https://t.co/TjujvJWO71 | [Project](https://t.co/q0iSCc89va.)
π COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis π https://t.co/j0BpBRz3Is
π AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency π https://t.co/H9gAgKTqhs
π DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning π https://t.co/BmoGgfOXmz
π FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning π https://t.co/aPQZ9Js9st | [Project](https://t.co/SBiT2KzKz2)
Find more daily insights here: https://t.co/nXJyIf9GmN
π COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis π https://t.co/j0BpBRz3Is
π AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency π https://t.co/H9gAgKTqhs
π DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning π https://t.co/BmoGgfOXmz
π FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning π https://t.co/aPQZ9Js9st | [Project](https://t.co/SBiT2KzKz2)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GlGCxpmWMAAcVIY.jpg)
π COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis π https://t.co/j0BpBRz3Is
π AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency π https://t.co/H9gAgKTqhs
π DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning π https://t.co/BmoGgfOXmz
π FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning π https://t.co/aPQZ9Js9st | [Project](https://t.co/SBiT2KzKz2)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GlGCxpjXkAAVQNX.jpg)
π COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis π https://t.co/j0BpBRz3Is
π AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency π https://t.co/H9gAgKTqhs
π DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning π https://t.co/BmoGgfOXmz
π FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning π https://t.co/aPQZ9Js9st | [Project](https://t.co/SBiT2KzKz2)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GlGCxpQa4AAxjYZ.jpg)
π COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis π https://t.co/j0BpBRz3Is
π AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency π https://t.co/H9gAgKTqhs
π DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning π https://t.co/BmoGgfOXmz
π FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning π https://t.co/aPQZ9Js9st | [Project](https://t.co/SBiT2KzKz2)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GlGCxpLagAA37a2.jpg)
#SimulatelyPapers | February 17, 2025
π MuJoCo Playground π https://t.co/vMkGDokyWI
π Learning Humanoid Standing-up Control across Diverse Postures π https://t.co/wNuHtnyMV8 | [Project](https://t.co/UIUNUWeCrc.)
π A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards π https://t.co/mQtFDeg29P
π Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation π https://t.co/Pvft60ijA6 | [Project](https://t.co/2mklQXXKh4.)
Find more daily insights here: https://t.co/nXJyIf9GmN
π A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards π https://t.co/mQtFDeg29P
π Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation π https://t.co/Pvft60ijA6 | [Project](https://t.co/2mklQXXKh4.)
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/GlBzYFnWsAAShTA.jpg)
#SimulatelyPapers | January 28, 2025
π SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model π https://t.co/fTMKK2Klvf
Find more daily insights here: https://t.co/qCbfpBdOuu
#SimulatelyPapers | January 20, 2025
π FoundationStereo: Zero-Shot Stereo Matching π https://t.co/Vs0a8vT0G2
π SLIM: Sim-to-Real Legged Instructive Manipulation via Long-Horizon Visuomotor Learning π https://t.co/bcgshMUvzR
π Robotic World Model: A Neural Network Simulator for Robust Policy Optimization in Robotics π https://t.co/RxzOyVHsO5
π DexForce: Extracting Force-informed Actions from Kinesthetic Demonstrations for Dexterous Manipulation π https://t.co/C0ByUBBEu3
Find more daily insights here: https://t.co/nXJyIf9GmN
#SimulatelyPapers | January 09, 2025
π Learning to Transfer Human Hand Skills for Robot Manipulations π https://t.co/IqEaYGUvkU | [Project](https://t.co/tcB8R8dJyS.)
π Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics π https://t.co/x8cGBNJXEF | [Project](https://t.co/6KF0Nn7mUS.)
π MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data π https://t.co/0SOueLQlll
π FrontierNet: Learning Visual Cues to Explore π https://t.co/SylBSgRtym
π Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding π https://t.co/tETdUT7acY
Find more daily insights here: https://t.co/nXJyIf9GmN
π Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics π https://t.co/x8cGBNJXEF | [Project](https://t.co/6KF0Nn7mUS.)
π MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data π https://t.co/0SOueLQlll
π FrontierNet: Learning Visual Cues to Explore π https://t.co/SylBSgRtym
π Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding π https://t.co/tETdUT7acY
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gg1FphEaMAQX22u.png)
π Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics π https://t.co/x8cGBNJXEF | [Project](https://t.co/6KF0Nn7mUS.)
π MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data π https://t.co/0SOueLQlll
π FrontierNet: Learning Visual Cues to Explore π https://t.co/SylBSgRtym
π Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding π https://t.co/tETdUT7acY
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gg1FphDbsAAUjTm.jpg)
π Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics π https://t.co/x8cGBNJXEF | [Project](https://t.co/6KF0Nn7mUS.)
π MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data π https://t.co/0SOueLQlll
π FrontierNet: Learning Visual Cues to Explore π https://t.co/SylBSgRtym
π Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding π https://t.co/tETdUT7acY
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gg1FphDbcAA3ovN.jpg)
π Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics π https://t.co/x8cGBNJXEF | [Project](https://t.co/6KF0Nn7mUS.)
π MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data π https://t.co/0SOueLQlll
π FrontierNet: Learning Visual Cues to Explore π https://t.co/SylBSgRtym
π Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding π https://t.co/tETdUT7acY
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gg1FphDaoAAf3ac.jpg)
#SimulatelyPapers | November 22, 2024
π Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics π https://t.co/q8HETYeEiN
π Bimanual Dexterity for Complex Tasks π https://t.co/Ih95k0NbvC | [Project](https://t.co/erQRkTn63T)
π Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation π https://t.co/ni8L0fRLwq
π Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation π https://t.co/GHWZtR5k28
π Learning thin deformable object manipulation with a multi-sensory integrated soft hand π https://t.co/Un7klmlkPg
π Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots π https://t.co/RFnuj4hstR
π SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching π https://t.co/RDgTj6vgyF
π Learning Humanoid Locomotion with Perceptive Internal Model π https://t.co/MdaznUqgB8
π 23 DoF Grasping Policies from a Raw Point Cloud π https://t.co/bwmX05tkDS
Find more daily insights here: https://t.co/nXJyIf9GmN
π Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation π https://t.co/ni8L0fRLwq
π Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation π https://t.co/GHWZtR5k28
π Learning thin deformable object manipulation with a multi-sensory integrated soft hand π https://t.co/Un7klmlkPg
π Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots π https://t.co/RFnuj4hstR
π SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching π https://t.co/RDgTj6vgyF
π Learning Humanoid Locomotion with Perceptive Internal Model π https://t.co/MdaznUqgB8
π 23 DoF Grasping Policies from a Raw Point Cloud π https://t.co/bwmX05tkDS
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gc9jhxsbMAAh2AD.jpg)
π Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation π https://t.co/ni8L0fRLwq
π Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation π https://t.co/GHWZtR5k28
π Learning thin deformable object manipulation with a multi-sensory integrated soft hand π https://t.co/Un7klmlkPg
π Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots π https://t.co/RFnuj4hstR
π SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching π https://t.co/RDgTj6vgyF
π Learning Humanoid Locomotion with Perceptive Internal Model π https://t.co/MdaznUqgB8
π 23 DoF Grasping Policies from a Raw Point Cloud π https://t.co/bwmX05tkDS
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gc9jhxrbgAAC2Ry.jpg)
π Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation π https://t.co/ni8L0fRLwq
π Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation π https://t.co/GHWZtR5k28
π Learning thin deformable object manipulation with a multi-sensory integrated soft hand π https://t.co/Un7klmlkPg
π Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots π https://t.co/RFnuj4hstR
π SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching π https://t.co/RDgTj6vgyF
π Learning Humanoid Locomotion with Perceptive Internal Model π https://t.co/MdaznUqgB8
π 23 DoF Grasping Policies from a Raw Point Cloud π https://t.co/bwmX05tkDS
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gc9jhxragAAH1AK.jpg)
π Arm Robot: AR-Enhanced Embodied Control and Visualization for Intuitive Robot Arm Manipulation π https://t.co/ni8L0fRLwq
π Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation π https://t.co/GHWZtR5k28
π Learning thin deformable object manipulation with a multi-sensory integrated soft hand π https://t.co/Un7klmlkPg
π Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots π https://t.co/RFnuj4hstR
π SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching π https://t.co/RDgTj6vgyF
π Learning Humanoid Locomotion with Perceptive Internal Model π https://t.co/MdaznUqgB8
π 23 DoF Grasping Policies from a Raw Point Cloud π https://t.co/bwmX05tkDS
Find more daily insights here: https://t.co/nXJyIf9GmN](https://pbs.twimg.com/media/Gc9jhxqaAAIwG2H.jpg)
#SimulatelyPapers | November 18, 2024
π Whole-Body Impedance Coordinative Control of Wheel-Legged Robot on Uncertain Terrain π https://t.co/1hniSq2QR5
π ALPHA-$Ξ±$ and Bi-ACT Are All You Need: Importance of Position and Force Information/Control for Imitation Learning of Unimanual and Bimanual Robotic Manipulation with Low-Cost System π https://t.co/UJJ91YgqRi | [Project](https://t.co/AbcetX3qoh)
Find more daily insights here: https://t.co/nXJyIf9GmN
Autonomous actions are executed based on learned Bi-ACT from only 5 collected demonstration data. The findings demonstrated that Bi-ACT model with force control, utilizing the ALPHA-Ξ±, exhibited high success rates and confirmed its applicability to bimanual tasks.
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