Boxi Xia

We propose CEER, a compliant end-effector–root (EE-root) control abstraction for modular humanoid loco-manipulation within a hierarchical planning framework. CEER enables compliance-aware whole-body control in an interpretable task space defined by root motion commands and end-effector pose targets, and supports plug-and-play integration with heterogeneous high-level planners. Experiments in simulation and on hardware demonstrate 3.3 cm end-effector tracking accuracy with substantially reduced jerk, stable contact-rich manipulation under teleoperation, and up to 70% success in simulated single-object loco-manipulation tasks within a room-scale environment.

We introduce dynamic symmetry — the uniformity of a robot's attainable center-of-mass accelerations — and show that maximizing it consistently improves trajectory tracking, robustness, and energy efficiency across 1,000+ simulated morphologies. We build Argus, a 20-leg spherical robot achieving near-extreme dynamic isotropy, demonstrating orientation-invariant locomotion, agile terrain traversal, and resilience to partial actuator failures.

We present the Duke Humanoid, an open-source 10-DOF child-sized bipedal robot designed for energy-efficient locomotion using passive dynamics. We develop a reinforcement learning policy deployable zero-shot on hardware for velocity-tracking walking, and propose an end-to-end RL algorithm that encourages passive dynamics — reducing cost of transport by up to 50% in simulation and 31% in real-world tests.

Text2Robot converts user text descriptions into physical quadrupedal robots. Within minutes, text-to-3D models initialize diverse morphologies; within a day, geometric processing and body-control co-optimization produce a walking robot that accounts for real-world electronics and manufacturability. The framework enables rapid prototyping and opens new opportunities for generative robot design.

We present Flexipod, an open-source untethered quadrupedal soft robot platform for dynamic locomotion. The robot is 80 vol.% soft with 3D-printed gyroid-infill flexible legs that passively stabilize on multi-terrain environments. With gaits tuned in a CUDA-accelerated soft-body simulator, the real robot achieves 0.9 m/s (2.5 body lengths/sec) — faster than most untethered legged soft robots — and can execute backflips.