Evaluation of ROS Navigation Stack for Social Navigation in Simulated Environments

Accuracy and safety are necessary characteristics in social navigation. These characteristics still constitute a challenge in this area. Yet, human comfort is the main goal in interactions involving human beings. The ROS Navigation Stack (RNS) allows the variation of local path planning methods. This paper consists in a comparative study of methods related to social navigation. This study promotes better social navigation on Home Environment Robot Assistant (HERA). This is a robot platform developed by FEI University Center. This work evaluated various parameter combinations: type of environments, types of obstacles, local and global planning algorithms and costmaps. The work also evaluated people in static, dynamic and interacting ways. This study observed aspects of safety, accuracy of estimated time and space. Other aspects observed are the smooth trajectory realized and respect for personal space. The experiments performed 1000 attempts for 37 combinations of methods, environments and sensors. In total, the experiments counted 37000 attempts. With these experiments, was possible to select a configuration for the navigation system. The point to the Timed Elastic Band (TEB) as a local planner and a proxemic costmap as a good combination. The results reach 97.6% of success in a more complex environment with this combination.