| Popis: |
In the rapidly evolving world of remote work, mobile telepresence robots (MTRs) have become increasingly popular, providing new avenues for people to actively engage in activities at a distance. The existing studies indicate, however, that remote navigation around humans in dense environments can be challenging for humans, resulting in a decreased level of satisfaction. Work on shared autonomy for navigation has generally addressed static environments or situations where only one pedestrian interacts with the robot. In this paper, we present our ongoing work on SocNavAssist, a haptic shared autonomy framework for navigation assistance of mobile telepresence robots in human-populated environments. It uses a modified approach of reciprocal velocity obstacles to consider social constraints in dynamic collision avoidance. We also provide visualization of system intent via predicted trajectories on an augmented visual feedback interface to enhance transparency and cooperation. In addition, we outline the proposed experiment to be used in future work to evaluate the proposed framework. |
