通过单人到多人协作的技能迁移，实现更通用的人形机器人协同操作。
SynAgent: Generalizable Cooperative Humanoid Manipulation via Solo-to-Cooperative Agent Synergy
- 利用单人交互数据，通过协同机制迁移至多人协作场景。
- 在多种物体形状下实现稳定可控的协同操作，优于现有方法。
- 适合研究机器人协作、具身智能与动作生成的学者参考。
可控的协同人形操作是具身智能的基础挑战，受限于数据稀缺、多智能体协调复杂及跨物体泛化能力不足。本文提出SynAgent框架，通过单人到多人协作的智能体协同机制，将单人-物体交互技能迁移到多人-物体-人场景中。为保持运动转移中的语义一致性，引入基于Delaunay四面体化构建的交互网格（Interact Mesh）的保留交互重定向方法，精确维护人与物体间的空间关系。在此基础上，采用单智能体预训练与适配范式，通过去中心化训练和多智能体PPO从丰富的单人数据中提炼协同行为。最后，设计基于条件变分自编码器的轨迹条件生成策略，通过多教师蒸馏学习运动模仿先验，实现稳定的物体级轨迹控制。大量实验表明，SynAgent在协同模仿与轨迹控制任务中显著优于基线方法，并具备跨多样物体几何形状的泛化能力。代码与数据将在发表后公开。项目页：https://yw0208.github.io/synagent/
原文摘要 · Abstract (English)
Controllable cooperative humanoid manipulation is a fundamental yet challenging problem for embodied intelligence, due to severe data scarcity, complexities in multi-agent coordination, and limited generalization across objects. In this paper, we present SynAgent, a unified framework that enables scalable and physically plausible cooperative manipulation by leveraging Solo-to-Cooperative Agent Synergy to transfer skills from single-agent human-object interaction to multi-agent human-object-human scenarios. To maintain semantic integrity during motion transfer, we introduce an interaction-preserving retargeting method based on an Interact Mesh constructed via Delaunay tetrahedralization, which faithfully maintains spatial relationships among humans and objects. Building upon this refined data, we propose a single-agent pretraining and adaptation paradigm that distills synergistic collaborative behaviors from abundant single-human data through decentralized training and multi-agent PPO. Finally, we develop a trajectory-conditioned generative policy using a conditional VAE, trained via multi-teacher distillation from motion imitation priors to achieve stable and controllable object-level trajectory execution. Extensive experiments demonstrate that SynAgent significantly outperforms existing baselines in both cooperative imitation and trajectory-conditioned control, while generalizing across diverse object geometries. Codes and data will be available after publication. Project Page: https://yw0208.github.io/synagent/
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