Navigating a service robot for indoor complex environments

This paper investigates the use of an autonomous service robot in an indoor complex environment, such as a hospital ward or a retirement home. This type of service robot not only needs to plan and find paths around obstacles, but must also interact with caregivers or patients. This study presents a type of service robot that combines the image from a 3D depth camera with infrared sensors, and the inputs from multiple sonar sensors in an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based approach in path planning. In personal contacts, facial features are used to perform person recognition in order to discriminate between staff, patients, or a stranger. In the case of staff, the service robot can perform a follow-me function if requested. The robot can also use an additional feature which is to classify the person's gender. The purpose of facial and gender recognition includes helping to present choices for suitable destinations to the user. Experiments were done in cramped but open spaces, as well as confined passages scenarios, and in almost all cases, the autonomous robots were able to reach their destinations.