Person-aware autonomous navigation for an indoor sanitizing robot in ROS2

In recent decades, intelligent systems have increasingly become part of our everyday lives to the point that robots able to perceive their surrounding environment and interact with it are not a dream anymore. Nowadays, robots are employed extensively in a variety of industries, including manufacturing, packing, transportation, search and rescue, healthcare and surgery. The usage of robots in social contexts, on the other hand, is still in an earlier stage. The areas of localization, mapping, and exploration for autonomous mobile robots have been the subject of substantial research, mainly focused on unknown environments where the robot is able to build 2D map based on its sensor's output. In particular, in the last few years there has been an increase in research on autonomous navigation in social environments, which is noteworthy in terms of how much attention this subject is receiving recently. Person-aware indoor navigation focuses on the ability of the robot to automatically detect a person, its position and velocity in real time. Indeed, this skill is crucial for people-aware indoor mapping, obstacle avoidance and path planning. This thesis project aims to improve the navigation strategy of a sanitizing robot by introducing a person-aware module. Through the usage of ROS2 the local and global costmap of Nav2 are modified to address the presence of people and maintain an acceptable social distance. A research about the autonomous navigation problem in social contexts has been carried out and the solution we propose uses computer vision to detect people and distinguish them from static obstacles. The developed algorithms are subsequently used to determine the optimal path through the environment by combining multiple probabilities of success based on each sensor's output. This project is linked to a collaboration between the Interdepartmental Centre for Service Robotics of Politecnico di Torino (PIC4SeR) and the Innovation Centre of Intesa San Paolo. The proposed solution intends to build the groundwork for more extensive and focused approach to tackle the issue of autonomous navigation in social contexts.