Robotic Motion Techniques for Socially Aware Navigation: A Scoping Review

The increasing inclusion of robots in social areas requires continuous improvement of behavioral strategies that robots must follow. Although behavioral strategies mainly focus on operational efficiency, other aspects should be considered to provide a reliable interaction in terms of sociability (e.g., methods for detection and interpretation of human behaviors, how and where human–robot interaction is performed, and participant evaluation of robot behavior). This scoping review aims to answer seven research questions related to robotic motion in socially aware navigation, considering some aspects such as: type of robots used, characteristics, and type of sensors used to detect human behavioral cues, type of environment, and situations. Articles were collected on the ACM Digital Library, Emerald Insight, IEEE Xplore, ScienceDirect, MDPI, and SpringerLink databases. The PRISMA-ScR protocol was used to conduct the searches. Selected articles met the following inclusion criteria. They: (1) were published between January 2018 and August 2025, (2) were written in English, (3) were published in journals or conference proceedings, (4) focused on social robots, (5) addressed Socially Aware Navigation (SAN), and (6) involved the participation of volunteers in experiments. As a result, 22 studies were included; 77.27% of them employed mobile wheeled robots. Platforms using differential and omnidirectional drive systems were each used in 36.36% of the articles. 50% of the studies used a functional robot appearance, in contrast to bio-inspired appearances used in 31.80% of the cases. Among the frequency of sensors used to collect data from participants, vision-based technologies were the most used (with monocular cameras and 3D-vision systems each reported in 7 articles). Processing was mainly performed on board (50%) of the robot. A total of 59.1% of the studies were performed in real-world environments rather than simulations (36.36%), and a few studies were performed in hybrid environments (4.54%). Robot interactive behaviors were identified in different experiments: physical behaviors were present in all experiments. A few studies employed visual behaviors (2 times). In just over half of the studies (13 studies), participants were asked to provide post-experiment feedback.