Real-Life Experiment Metrics for Evaluating Human-Robot Collaborative Navigation Tasks

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.

I. Introduction

If we plan to have robotics partners in the future, these partners need to be embedded with human-like navigation behaviors. Also, these behaviors need not only to focus on accomplishing the task satisfactorily. These behaviors must include those robots move predictably and socially to increase the number of potential users for these robots and the satisfaction to use the robots [1]–[3], as well as people’s trust in robots [4], and people’s comfort [5], along with people’s perception of safety [6].