Real-time application for monitoring human daily activity and risk situations in robot-assisted living

Abstract

In thiswork,we present a real-time application in the scope of human daily activity recognition for robot-assisted living as an extension of our previouswork [1]. We implemented our approach using Robot Operating System (ROS) environment, combining different modules to enable a robot to perceive the environment using different sensor modalities. Thus, the robot can move around, detect, track and follow a person to monitor daily activities wherever the person is. We focus our attention mainly on the robotic application by integrating several ROSmodules for navigation, activity recognition and decision making. Reported results show that our framework accurately recognizes human activities in a real time application, triggering proper robot (re)actions, including spoken feedback for warnings and/or appropriate robot navigation tasks. Results evidence the potential of our approach for robot-assisted living applications.