Supernumerary robotic limbs (SLs) have the potential to transform a wide range of human activities, yet their usability remains limited by key technical challenges, particularly in ensuring safety and achieving versatile control. Here, we address the critical problem of maintaining balance in the human-SLs system, a prerequisite for safe and comfortable augmentation tasks. Unlike previous approaches that developed SLs specifically for stability support, we propose a general framework for preserving balance with SLs designed for generic use. Our hierarchical three-layer architecture consists of: (i) a prediction layer that estimates human trunk and center of mass (CoM) dynamics, (ii) a planning layer that generates optimal CoM trajectories to counteract trunk movements and computes the corresponding SL control inputs, and (iii) a control layer that executes these inputs on the SL hardware. We evaluated the framework with ten participants performing forward and lateral bending tasks. The results show a clear reduction in stance instability, demonstrating the framework's effectiveness in enhancing balance. This work paves the path towards safe and versatile human-SLs interactions. [This paper has been submitted for publication to IEEE.]

翻译：超数机器人肢体（SLs）具有变革广泛人类活动的潜力，但其可用性仍受关键技术挑战的限制，特别是在确保安全性和实现通用控制方面。本文针对人-SLs系统维持平衡这一关键问题展开研究，这是实现安全舒适增强任务的先决条件。与以往专门为稳定性支撑开发SLs的方法不同，我们提出了一种通用框架，用于为通用设计的SLs保持平衡。我们的分层三层架构包括：（i）预测层，用于估计人体躯干和质心（CoM）动力学；（ii）规划层，用于生成最优CoM轨迹以抵消躯干运动，并计算相应的SL控制输入；（iii）控制层，在SL硬件上执行这些输入。我们通过十名参与者执行前屈和侧屈任务对该框架进行了评估。结果显示站立不稳定性显著降低，证明了该框架在增强平衡方面的有效性。这项工作为安全、通用的人-SLs交互铺平了道路。[本文已提交至IEEE待发表。]