As the global population ages, there is a growing need for assistive technologies to help older adults maintain their independence. This work presents a cost-effective autonomous socially assistive robot designed for object retrieval and delivery, enhancing accessibility in home environments. The system is built on the Robot Operating System (ROS) framework and integrates three key components: the Pioneer P3-DX mobile robot for autonomous navigation, the ReactorX-200 robotic arm for pick-and-place operations, and the Kinect v2 RGB-D camera for object detection and localization. Users interact with the robot through natural language processing by issuing voice commands to retrieve various objects. Microsoft Azure-powered speech recognition processes these commands to extract keywords and then localize requested objects on a predefined building map. Pioneer P3-DX, equipped with a Hokuyo LiDAR, enables autonomous navigation and obstacle avoidance, while Kinect v2, integrated with the YOLOv8 algorithm, facilitates object recognition and localization. The robot retrieves and delivers the user’s requested objects while following the shortest available path. Experimental evaluations in a home environment demonstrate the system’s effectiveness in identifying and retrieving requested objects. The subsystems achieve a success rate of 85–95% across more than 50 runs, highlighting their strong performance. The proposed approach provides a proof of concept for future advancements in assistive robotics, demonstrating the seamless integration of advanced technologies into a cost-effective and user-friendly platform.
Li et al. (Thu,) studied this question.