Cooperative humanoid robots carry objects with realistic shared motions
CoCarry: Contact-Support-Structured Retargeting for Dual-Humanoid Cooperative Carrying
Robotics
Summary
Carrying objects together with two robots is harder than making one robot move correctly. The authors created a large set of videos showing two people carrying objects and designed a method to make two robot models move together naturally while holding the same object. Their method keeps the robots' hands on the object correctly and avoids unrealistic clashes between the robots. They tested their method on simulations and with real robots, showing the motions worked well.
What this means in practice
- •For robot developers: Generate coordinated motion plans for two humanoid robots to carry objects together realistically and safely.
- •For robotics simulation engineers: Use realistic reference motions for simulating dual-robot interaction during cooperative object manipulation tasks.
Authors
Ziyu Lin, Shihang Du, Tianhang Wang, Xiaodong Liu, Runze Zhang, Zongyou Yu, Haodong Zhang, Alois Knoll, Guang Chen
Abstract
Recent advances in large-scale human motion data, motion retargeting, and motion imitation have enabled increasingly capable whole-body control for individual humanoids. Cooperative carrying is more challenging because successful coordination requires not only plausible individual motions, but also consistent cross-agent and agent-object relations, including shared grasp, relative configuration, and whole-body support. We introduce CoCarry, a cooperative-carrying dataset containing 220 synchronized two-person sequences across 21 task schemes, five shared-object geometries, four terrain types, and approximately 61 minutes of motion. We further propose Contact-Support-Structured Retargeting, which starts from nominal individual motions and jointly refines both humanoids around the same prescribed object trajectory. Cooperation-aware object-local hand anchors preserve compatible four-hand grasp relations, while complementary upper object-interaction and lower support structures retain object-relative geometry and coordinated support. Across all 220 CoCarry sequences retargeted to two A3 humanoids, our method achieves 0.9995 contact preservation, reduces penetration duration by 67.0% and 71.0% relative to GMR and OmniRetarget, respectively, and maintains a 100% retargeting success rate. On CORE4D with Unitree G1 humanoids, it achieves 0.9906 contact preservation with zero measured sliding. We further validate the generated references through physics simulation and multiple real-world cooperative carrying experiments on two physical A3 humanoids, demonstrating their usability for downstream dual-humanoid control.