As the number of Persons with Disabilities (PWD), particularly those with one or more physical impairments, increases, there is an increasing demand for assistive robotic technologies that can support independent mobility in the built environment and reduce the burden on caregivers. Current assistive mobility platforms (e.g., robotic wheelchairs) often fail to incorporate user preferences and control, leading to reduced trust and efficiency. Existing shared control algorithms do not allow the incorporation of the user control preferences inside the navigation framework or the path planning algorithm. In addition, existing dynamic local planner algorithms for robotic wheelchairs do not take into account the social spaces of people, potentially leading such platforms to infringe upon these areas and cause discomfort. To address these concerns, this work introduces a novel socially-aware shared autonomy-based navigation system for assistive mobile robotic platforms. Our navigation framework comprises a Global Planner and a Local Planner. To implement the Global Planner, the proposed approach introduces a novel User Preference Field (UPF) theory within its global planning framework, explicitly acknowledging user preferences to adeptly navigate away from congested areas. For the Local Planner, we propose a Socially-aware Shared Control-based Model Predictive Control with Dynamic Control Barrier Function (SS-MPC-DCBF) to adjust movements in real-time, integrating user preferences for safer, more autonomous navigation. Evaluation results show that our Global Planner aligns closely with user preferences compared to baselines, and our Local Planner demonstrates enhanced safety and efficiency in dynamic and static scenarios. This integrated approach fosters trust and autonomy, crucial for the acceptance of assistive mobility technologies in the built environment.

翻译：随着残障人士（特别是具有一项或多项身体损伤者）数量的增加，对能够在建筑环境中支持独立移动并减轻护理人员负担的辅助机器人技术的需求日益增长。当前的辅助移动平台（如机器人轮椅）往往未能纳入用户偏好与控制，导致信任度和效率降低。现有的共享控制算法无法将用户控制偏好整合到导航框架或路径规划算法中。此外，现有机器人轮椅的动态局部规划器算法未考虑人的社交空间，可能导致此类平台侵犯这些区域并引发不适。为解决这些问题，本研究提出了一种面向辅助移动机器人平台的新型社会感知共享自主导航系统。我们的导航框架包含全局规划器与局部规划器。为实现全局规划器，所提方法在其全局规划框架中引入了一种新颖的用户偏好场理论，明确考虑用户偏好以灵活避开拥挤区域。对于局部规划器，我们提出了一种基于社会感知共享控制的模型预测控制与动态控制屏障函数方法，用于实时调整运动，整合用户偏好以实现更安全、更自主的导航。评估结果表明，与基线方法相比，我们的全局规划器更贴合用户偏好；我们的局部规划器在动态和静态场景中均表现出更高的安全性和效率。这种集成方法增强了信任与自主性，这对于辅助移动技术在建筑环境中的接受至关重要。