Boxi Xia

Postdoctoral Researcher | Duke University | Legged Robotics & Machine Learning

I build robots that learn to act in the physical world, from the mechanical hardware up through sim-to-real reinforcement learning. My focus spans humanoids, quadrupeds, soft robots, and generative AI for robot design. I hold a Ph.D. from Columbia University (advised by Prof. Hod Lipson) and am a postdoctoral researcher at Duke University in the General Robotics Lab, advised by Prof. Boyuan Chen.

News
2026 Argus paper published in Science Robotics — dynamic symmetry enables orientation-invariant locomotion in a 20-leg spherical robot.
Sep 2025 Duke Humanoid accepted at IROS 2025 — passive dynamics RL reduces cost of transport by 31% on real hardware.
May 2025 Text2Robot published at ICRA 2025 — generative AI designs and manufactures walking quadrupeds from text descriptions.
2025 Named inventor on Duke University provisional patent DU8960PROV (Argusbot).
Selected Publications
Extreme dynamic symmetry enables omnidirectional and multifunctional robots
Science Robotics
Extreme dynamic symmetry enables omnidirectional and multifunctional robots
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.
The Duke Humanoid: Design and control for energy-efficient bipedal locomotion using passive dynamics
IROS 2025
The Duke Humanoid: Design and control for energy-efficient bipedal locomotion using passive dynamics
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: Evolutionary robot design from text descriptions
ICRA 2025
Text2Robot: Evolutionary robot design from text descriptions
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.
A legged soft robot platform for dynamic locomotion
ICRA 2021
A legged soft robot platform for dynamic locomotion
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.

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