With global concern regarding the aging population and an increase in the number of single-person households, there is a growing need for monitoring methods for single-person households. Our research group has proposed a new type of living system, called the “Biofied Building”, in which a robot works in conjunction with the living space to support the physical and mental health of the residents.
Previous studies have proposed a system to monitor the physical health of residents. The role of the robot in these systems is to acquire appropriate information about the space and the residents. In such a situation, decisions about the robot’s waiting position are an important factor affecting data acquisition for later analysis. The robot’s activities must be conducted in a way that does not disturb the residents’ lives. These methods can be widely used to determine a robot’s waiting position, with consideration of multiple conditions. In previous studies, the following four conditions have been used to determine the robot waiting position:
1) There is an appropriate distance from obstacles.
2) Areas in which the resident’s walking frequency is low.
3) Location information about the resident can be obtained.
4) There is an appropriate distance from the resident.
However, due to the constraints of conventional methods, optimal waiting positions often cannot be determined because the residents’ whole walking history is reflected in the potential field. Furthermore, the appropriate distance from the resident is typically determined on a trial-and-error basis and the effects of individual and environmental differences are not considered.
In addition, robots are expected to play a role in communication in the monitoring of mental health. However, there has been little research on the positional relationship between residents and robots in the living space, and an architectural planning approach has not been applied for determining robots’ waiting positions and movement paths for communication with residents in daily life.
The purpose of the current study was to quantitatively clarify the optimal positional relationship for communication between residents and robots, considering individual differences and environmental factors, and to propose a method to estimate the robot’s optimal waiting position for communication between the resident and the robot in a living space. Furthermore, to solve the problem of being unable to determine an appropriate waiting position, we created a repulsive potential field based on the probability of choosing the next walking path, which is predicted based on the resident’s current location, instead of using the resident’s total walking history.
We first conducted an experiment to extract the factors that affect the personal space for communication. As a result, we revealed that the distance to the wall behind the robot and the resident’s posture (standing/sitting) affect the interaction distance. Thus, personal space descriptions can be generalized using these two factors.
The validity and versatility of the proposed method were tested using a simulation. The proposed method reliably estimated an appropriate waiting position of the robot, and achieved safety with a high probability of avoiding collision. Compared with a method that did not use behavioral patterns, the current method revealed the usefulness of considering residents’ behavioral patterns. In future research, we plan to investigate differences in dialogue distance between a wide range of age groups, and to examine the adaptability of the proposed method for living spaces with multiple people.
