Grant: Engage Grants Program

A socially aware robot navigation systems that enables a mobile robot to autonomously navigate in social environments such as airports, shopping malls, museums is highly expected to deploy mobile robots for our daily services. The first and most important issue to allow a mobile robot to work in a social environment is that the robot must avoid not only regular obstacles but also humans while navigating safely and socially towards a given goal.We will investigate and develop a socially aware robot navigation system by incorporating socio-spatio-temporal characteristics of humans on a social reactive motion model. In this project, we will develop a social reactive motion model (SRM) added on the conventional robot navigation scheme to enable the mobile robot to deal with different social situations of individuals and human groups when navigating in social environments. SRM is composed of four functional blocks: (1) human detection and tracking is to detect and track humans in the vicinity of the robot; (2) human state extraction is to extract human position, orientation, velocity and human postures; (3) human group estimation is to estimate groups of interactive humans; (4) social reactive control incorporates information of individuals and human groups into an extended social force model. SRM can be integrated on a conventional path planning, e.g. D*, RRT, to generate a socially aware robot motion planning that enables the robot to navigate towards the given goal while socially and reactively avoiding individuals, human group, other robots, and environmental obstacles. The socially aware robot navigation system will be developed on a ROS-based software platform that will be integrated and tested on QBot2 provided by Quanser.