5 accepted papers
Humanoid whole-body locomotion control is a critical approach for humanoid robots to leverage their inherent advantages. Learning-based control methods derived from retargeted human motion data provide an effective means of addressing this issue. However, because most current human datasets lack mea…
Reinforcement learning has emerged as a principled post-training paradigm for Temporal Video Grounding (TVG) due to its on-policy optimization, yet existing GRPO-based methods remain fundamentally constrained by sparse reward signals and substantial computational overhead. We propose Video-OPD, an e…
Temporal Video Grounding (TVG), the task of locating specific video segments based on language queries, is a core challenge in long-form video understanding. While recent Large Vision-Language Models (LVLMs) have shown early promise in tackling TVG through supervised fine-tuning (SFT), their ability…
Flexibility and softness play a significant role in dynamic human motions. This includes the flexibility owing to ligaments in the human body and the softness of external structures such as a leaf-spring-type prosthesis. Thus, robotic systems need to utilize such flexibility to achieve dynamic and e…
As a basic part of the centroidal dynamics, an-gular momentum plays a critical role in humanoid motion control. Therefore, how to explicitly express and control an-gular momentum through whole-body motion is an important topic for researchers. This study discusses the selection of the generalized ve…