Abstract
As the global population ages, many seniors face the problem of loneliness. Companion robots offer a potential solution. However, current companion robots often lack advanced functionality, while task-oriented robots are not designed for social interaction, limiting their suitability and acceptance by seniors. Our work introduces a senior-oriented system for quadruped robots that allows for more intuitive user input and provides more socially expressive output. For user input, we implemented a MediaPipe-based module for hand gesture and head movement recognition, enabling control without a remote. For output, we designed and trained robotic dog gestures using curriculum-based reinforcement learning in Isaac Gym, progressing from simple standing to three-legged balancing and leg extensions, and more. The final tests achieved over 95\% success on average in simulation, and we validated a key social gesture (the paw-lift) on a Unitree robot. Real-world tests demonstrated the feasibility and social expressiveness of this framework, while also revealing sim-to-real challenges in joint compliance, load distribution, and balance control. These contributions advance the development of practical quadruped robots as social companions for the senior and outline pathways for sim-to-real adaptation and inform future user studies.
Abstract (translated)
随着全球人口老龄化，许多老年人面临着孤独的问题。陪伴机器人提供了一种潜在的解决方案。然而，目前的伴侣机器人通常功能较为有限，而任务导向型机器人则不是为社交互动设计的，这限制了它们在老年群体中的适用性和接受度。我们的工作介绍了一个面向老年人的四足机器人的系统，该系统允许更加直观的用户输入，并提供了更具社会表达性的输出。 对于用户输入，我们实现了一个基于MediaPipe的手势和头部动作识别模块，从而可以在不使用遥控器的情况下进行控制。在输出方面，我们在Isaac Gym中利用基于课程的学习强化学习方法设计并训练了机器狗的姿态，从简单的站立到三足平衡再到腿部伸展等复杂动作。最终的测试在模拟环境中平均达到了超过95%的成功率，并且我们还在一个Unitree机器人上验证了一个关键的社会互动手势（举起爪子）。 实地测试证明了该框架的实际可行性和社会表达性，同时揭示了一些从仿真环境到现实世界的挑战，例如关节顺应性、负载分布和平衡控制等问题。这些贡献推动了实用四足机器人的开发，使其成为老年人社交伙伴，并为未来如何将虚拟设计转化为实际应用提供了指导路径以及未来的用户研究方向。
URL
https://arxiv.org/abs/2512.17136
