Rongjun Jin — accepted AI-conference papers

2026

Act2Goal: From World Model To General Goal-conditioned Policy

Pengfei Zhou, Liliang Chen, Shengcong Chen, Di Chen, Wenzhi Zhao, Rongjun Jin +2

RSS 2026poster

Specifying robotic manipulation tasks in a manner that is both expressive and precise remains a central challenge. While visual goals provide a compact and unambiguous task specification, existing goal-conditioned policies often struggle with long-horizon manipulation due to their reliance on single…

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2026

Coordinated Humanoid Robot Locomotion with Symmetry Equivariant Reinforcement Learning Policy

Buqing Nie, Yang Zhang, Rongjun Jin, Zhanxiang Cao, Huangxuan Lin, Xiaokang Yang +1

AAAI 2026technical

The human nervous system exhibits bilateral symmetry, enabling coordinated and balanced movements. However, existing Deep Reinforcement Learning (DRL) methods for humanoid robots neglect morphological symmetry of the robot, leading to uncoordinated and suboptimal behaviors. Inspired by human motor c

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