Empowering robots with social cues: an initiative pose control framework for human–robot interaction

In human communication, people often turn and gaze at a specific person in a crowd to signal their intention to interact with them. Similarly, it has been proposed that robots should also use social cues such as facing their human interaction partner during human–robot interaction tasks. This study introduces an initiatively interactive pose control (IPC) framework that allows a robot to face its task-relevant human interaction partner and proactively use this social cue while carrying out desired actions based on the ongoing task state. The IPC framework integrates a task planning module and a 3D identity recognition module. The task planning module can generate task states that include information about the desired human interaction partner’s name and the expected actions of robots, including social cues. The 3D identity recognition module implemented in the IPC framework can identify potential human interaction partners and estimate their pose in relation to the robot. The relative pose serves as the control parameter for orienting the robot toward the selected human interaction partner. The experimental results show that the IPC framework achieves a relative pose estimation error ranging from 0.04 to 6.56 degrees, which signifies a substantial enhancement compared to traditional sound source localization methods. Moreover, experiments also demonstrate that the robot can proactively turn toward the interaction partner and execute expected actions using the IPC framework. In conclusion, this paper introduces a new protocol for interactive pose control, enabling robots to actively select their human interaction partners and exhibit social cues and associated interaction actions.