The paper presents a method for generating lower‑limb joint‑angle gait trajectories using conditional diffusion models. It compares a baseline transformer diffusion model with a controllable diffusion transformer that includes adaptive normalization and classifier‑free guidance. Experiments on 4,590 gait cycles demonstrate that these diffusion models can produce realistic, periodic gait patterns while allowing some control over gait characteristics such as step length.
arXiv:2609.18490v1 Announce Type: new Abstract: "What I cannot create, I do not understand."Human wisdom reveals that creation is one of the highest forms of learning. For example, Diffusion Models h...
arXiv:2606. 27918v1 Announce Type: cross Abstract: As a prominent symptom of Parkinson's disease (PD), turning impairment is evaluated through parameters such as turning angle, duration, and particularly, the number of steps required to complete a turn, which directly reflects motor dysfunction.
PhysMoDPO is a Direct Preference Optimization framework that integrates a Whole-Body Controller into the training of diffusion models for text-conditioned human motion generation. By using physics-based and task-specific rewards to assign preferences to synthesized trajectories, it ensures that the resulting motions are both physically realistic and faithful to the original text instructions. Experiments on simulated robots and a real G1 humanoid robot show consistent improvements in physical realism and task performance, including zero‑shot motion transfer.
arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring ac...
arXiv:2512. 00691v2 Announce Type: replace Abstract: Gait patterns play a critical role in human identification and healthcare analytics, yet current progress remains constrained by small, narrowly designed models that fail to scale or generalize.
arXiv:2512. 08280v3 Announce Type: replace-cross Abstract: Offline decision-making via diffusion models often produces trajectories that are misaligned with system dynamics, limiting their reliability for control.
arXiv:2603. 12408v2 Announce Type: replace-cross Abstract: Motion imitation learning (IL) is increasingly used in robotics and human gait modeling, yet its ability to recover biomechanically consistent joint moments without explicit kinetic information remains unclear.
arXiv:2408. 08182v5 Announce Type: replace-cross Abstract: People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses.
arXiv:2606. 00153v1 Announce Type: cross Abstract: Cross-modal 2D-3D gait recognition is impeded by inherent domain discrepancies between 2D silhouette and 3D LiDAR range-view representations.
arXiv:2603. 12408v3 Announce Type: replace-cross Abstract: Motion imitation learning (IL) is increasingly used in robotics and human gait modeling, yet its ability to recover biomechanically consistent joint moments without explicit kinetic information remains unclear.
arXiv:2609.09670v1 Announce Type: new Abstract: Monocular pose estimation enables low-cost gait analysis but is sensitive to missing keypoints caused by occlusion, detection errors, or efficiency-dri...
The integration of large-scale foundation models with physical embodiments has led to significant advancements in robotics known as Generative Physical Artificial Intelligence (GPAI). These agentic AI...