This paper presents a framework to navigate visually impaired people through unfamiliar environments by means of a mobile manipulator. The Human-Robot system consists of three key components: a mobile base, a robotic arm, and the human subject who gets guided by the robotic arm via physically coupling their hand with the cobot's end-effector. These components, receiving a goal from the user, traverse a collision-free set of waypoints in a coordinated manner, while avoiding static and dynamic obstacles through an obstacle avoidance unit and a novel human guidance planner. With this aim, we also present a legs tracking algorithm that utilizes 2D LiDAR sensors integrated into the mobile base to monitor the human pose. Additionally, we introduce an adaptive pulling planner responsible for guiding the individual back to the intended path if they veer off course. This is achieved by establishing a target arm end-effector position and dynamically adjusting the impedance parameters in real-time through a impedance tuning unit. To validate the framework we present a set of experiments both in laboratory settings with 12 healthy blindfolded subjects and a proof-of-concept demonstration in a real-world scenario.

翻译：本文提出一种通过移动机械臂引导视障者在陌生环境中导航的框架。该人-机器人系统包含三个核心组件：移动底座、机械臂以及通过手部与协作机器人末端执行器物理耦合以获得引导的人类受试者。这些组件在接收用户目标后，以协调方式遍历无碰撞路径点序列，同时通过避障单元与新型人类引导规划器规避静态及动态障碍物。为此，我们提出一种利用集成于移动底座的二维激光雷达传感器追踪人体姿态的腿部追踪算法。此外，我们引入自适应牵引规划器，当个体偏离预定路径时，该规划器通过设定机械臂末端执行器目标位置，并经由阻抗调节单元实时动态调整阻抗参数，将个体引导回正确路径。为验证该框架，我们开展两组实验：实验室环境下12名健康蒙眼受试者的测试，以及真实场景中的概念验证演示。