ExoLaN：面向外骨骼的物理一致性与上下文感知动力学学习

中文摘要 AI 辅助

基于人类意图的任务无关辅助外骨骼控制，比依赖预定义任务或运动模式的传统方法具有更大的灵活性。人类关节扭矩估计通过表征用户动作来实现任务无关的辅助。物理一致性方法如深度拉格朗日网络（DeLaN）已被应用于多用户场景下的人类扭矩估计，但现有方法无法在不重新训练的情况下适应特定用户，且未考虑运动过程中的间歇性接触。我们提出ExoLaN，一种用于人-外骨骼交互的上下文感知DeLaN，它学习完整的耦合系统动力学，同时适应交互上下文的变化。ExoLaN将时间上下文与来自力敏感鞋垫的部分接触力测量相结合，以推断潜在动力学嵌入并估计广义接触扭矩。在7名未见用户执行21项未见任务的测试中，与黑盒基线相比，ExoLaN将扭矩估计均方误差（MSE）降低了7%。超越逆动力学，ExoLaN作为一个统一模型还能实现准确的前向预测：使用多步预测损失训练，相比单步损失，加速度MSE降低了59%，长时域位置和速度误差分别降低了60%和93%。此外，学习到的潜在上下文无需显式任务标签即可捕获任务信息，使其成为任务感知辅助控制的有前景信号。

英文摘要

Task-agnostic assistive exoskeleton control based on human intention offers greater flexibility than conventional approaches that rely on predefined tasks or motion patterns. Human joint torque estimation enables task-agnostic assistance by characterizing user actions. Physics-consistent methods such as Deep Lagrangian Networks (DeLaN) have been applied to estimate the human torques in multi-user settings, but existing approaches cannot adapt to a specific user without retraining, and do not account for intermittent contacts during locomotion. We propose ExoLaN, a Context-Aware DeLaN for human-exoskeleton interaction that learns the full coupled system dynamics while adapting to changes in interaction context. ExoLaN combines temporal context with partial contact-force measurements from force-sensitive insoles to infer latent dynamics embeddings and estimate generalized contact torques. On seven unseen users performing 21 unseen tasks, ExoLaN reduces torque estimation MSE by 7% compared to a black-box baseline. Beyond inverse dynamics, ExoLaN serves as a unified model that also enables accurate forward prediction: training with a multi-step prediction loss reduces acceleration MSE by 59% and long-horizon position and velocity errors by 60% and 93%, respectively, compared with a single-step loss. Moreover, the learned latent context captures task information without explicit task labels, making it a promising signal for task-aware assistive control.

发表机构

• Technical University of Darmstadt（达姆施塔特工业大学）
• Robotics Institute Germany（德国机器人研究所）
• German Research Center for AI (DFKI)（德国人工智能研究中心（DFKI））

机构由 AI 辅助整理，请以论文原文为准。