GES framework uses Gaussian-partitioned specialist policies to co-optimize morphology and control for buoyancy-assisted legged robots, reporting 5-25% performance gains, 3x hardware obstacle improvement, and 37% faster design search versus baselines.
Multi-loco: Unifying multi-embodiment legged loco- motion via reinforcement learning augmented diffusion
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DynaWM adds a world model as dynamics regularizer and momentum targets to teacher-student distillation, yielding better terrain encoding and smoother stair traversal for bipedal-wheeled robots.
Any2Any transfers humanoid whole-body tracking models across embodiments via kinematic alignment followed by targeted PEFT, matching full-training performance with 1% of the data and compute on tested platforms.
A JAX-implemented flow-based equivariant model for multi-embodiment grasping that deduces kinematics from geometry to support variable-DoF grippers with a new dataset of 25k scenes and 20M grasps.
citing papers explorer
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Rapid co-design of Buoyancy-assisted robots for Challenging Locomotion using Gaussian Evolutionary Specialists
GES framework uses Gaussian-partitioned specialist policies to co-optimize morphology and control for buoyancy-assisted legged robots, reporting 5-25% performance gains, 3x hardware obstacle improvement, and 37% faster design search versus baselines.
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DynaWM: Dynamics-Aware Distillation with World Model and Momentum Targets for Smooth Locomotion over Continuous Stairs
DynaWM adds a world model as dynamics regularizer and momentum targets to teacher-student distillation, yielding better terrain encoding and smoother stair traversal for bipedal-wheeled robots.
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Any2Any: Efficient Cross-Embodiment Transfer for Humanoid Whole-Body Tracking
Any2Any transfers humanoid whole-body tracking models across embodiments via kinematic alignment followed by targeted PEFT, matching full-training performance with 1% of the data and compute on tested platforms.
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Towards a Multi-Embodied Grasping Agent
A JAX-implemented flow-based equivariant model for multi-embodiment grasping that deduces kinematics from geometry to support variable-DoF grippers with a new dataset of 25k scenes and 20M grasps.