MSK-Bench: Benchmarking Full-Body Musculoskeletal Motor Control Across Tasks, Control Paradigms, and Physiological Metrics
cs.RO
Submitted: 2026-09-22
Updated: 2026-09-22
Project page: https://zzongzheng0918.github.io/MSK-Bench
Terminology
Sources
- Solving Rubik's Cube with a Robot Hand
- LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion
- Residual Reinforcement Learning from Demonstrations
- Arnold: A multi-task, multi-embodiment muscle transformer policy
- Residual Off-Policy RL for Finetuning Behavior Cloning Policies
- OpenAI Gym
- MyoSuite -- A contact-rich simulation suite for musculoskeletal motor control
- KinTwin: Imitation Learning with Torque and Muscle Driven Biomechanical Models Enables Precise Replication of Able-Bodied and Impaired Movement from Markerless Motion Capture
- D4RL: Datasets for Deep Data-Driven Reinforcement Learning
- OpenCap Monocular: 3D Human Kinematics and Musculoskeletal Dynamics from a Single Smartphone Video
- ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
- DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
- OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning
- Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance
- SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending
- Towards Embodied AI with MuscleMimic: Unlocking full-body musculoskeletal motor learning at scale
- How to Peel with a Knife: Aligning Fine-Grained Manipulation with Human Preference
- Imitation Learning from Human Motion Alone Does Not Guarantee Biomechanically Plausible Gait Kinetics
- Mimicking-Bench: A Benchmark for Generalizable Humanoid-Scene Interaction Learning via Human Mimicking
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