8 papers
HierKick: Hierarchical Reinforcement Learning for Vision-Guided Soccer Robot Control
Yizhi Chen, Zheng Zhang, Zhanxiang Cao +7
Controlling soccer robots involves multi-time-scale decision-making, which requires balancing long-term tactical planning and short-term motion execution. Traditional end-to-end re…
HiWET: Hierarchical World-Frame End-Effector Tracking for Long-Horizon Humanoid Loco-Manipulation
Zhanxiang Cao, Liyun Yan, Yang Zhang +7
Humanoid loco-manipulation requires executing precise manipulation tasks while maintaining dynamic stability amid base motion and impacts. Existing approaches typically formulate c…
FocusNav: Spatial Selective Attention with Waypoint Guidance for Humanoid Local Navigation
Yang Zhang, Jianming Ma, Liyun Yan +4
Robust local navigation in unstructured and dynamic environments remains a significant challenge for humanoid robots, requiring a delicate balance between long-range navigation tar…
Coordinated Humanoid Robot Locomotion with Symmetry Equivariant Reinforcement Learning Policy
Buqing Nie, Yang Zhang, Rongjun Jin +4
The human nervous system exhibits bilateral symmetry, enabling coordinated and balanced movements. However, existing Deep Reinforcement Learning (DRL) methods for humanoid robots n…
Keep on Going: Learning Robust Humanoid Motion Skills via Selective Adversarial Training
Yang Zhang, Zhanxiang Cao, Buqing Nie +6
Humanoid robots are expected to operate reliably over long horizons while executing versatile whole-body skills. Yet Reinforcement Learning (RL) motion policies typically lose stab…
Learning Motion Skills with Adaptive Assistive Curriculum Force in Humanoid Robots
Zhanxiang Cao, Yang Zhang, Buqing Nie +3
Learning policies for complex humanoid tasks remains both challenging and compelling. Inspired by how infants and athletes rely on external support--such as parental walkers or coa…