As robots move from laboratories and industries to the real world, they must develop new abilities to collaborate with humans in various aspects, including human-robot collaborative navigation (HRCN) tasks. Then, it is required to develop general methodologies to evaluate these robots' behaviors. These methodologies should incorporate objective and subjective measurements. Objective measurements for evaluating a robot's behavior while navigating with others can be accomplished using social distances in conjunction with task characteristics, people-robot relationships, and physical space. Additionally, the objective evaluation of the task must consider human behavior, which is influenced by changes and the structure of their environment. Subjective evaluations of robot's behaviors can be conducted using surveys that address various aspects of robot usability. This includes people's perceptions of their interaction during their collaborative task with the robot, focusing on aspects such as sociability, comfort, and task-intelligence. Moreover, the communicative interaction between the agents (people and robots) involved in the collaborative task should also be evaluated. Therefore, this paper presents a comprehensive methodology for objectively and subjectively evaluating HRCN tasks.

This work has been supported by the Artificial Intelligence for HumanRobot Interaction (AI4HRI) project ANR-20-IADJ-0006. Also, this Work has been supported under the EU project grant CANOPIES (H2020- ICT-2020-2-101016906) and by the JST Moonshot R D Grant Number JPMJMS2011. Ely Repiso was also supported during her PhD by Spanish Ministry of Science and Innovation under a FPI-grant (BES-2014-067713) and during her Post Doc by the project AI4HRI

Trabajo presentado en el 32nd IEEE International Conference on Robot and Human Interactive Communication, celebrado en Busan (Corea del Sur), del 28 al 31 de agosto de 2023

Peer reviewed