Effective destination determination for semi-autonomous smart electric wheelchair based on history of human activity

A smart electric wheelchair for use as a personal mobility tool (PMT) is proposed. To reduce the load on the user, the PMT is integrated with autonomous mobile robot navigation and human input. It is able to reach a destination autonomously based on a directional input from the user. The accuracy of the destination detection depends on the user´s input. Therefore, to realize stress-free and efficient movement of the PMT, an appropriate means of destination detection based on inaccurate human input is required. We propose an approach whereby the PMT can determine its destination based not only on the user´s input but also on a history of human activity in the living environment. To enable the use of a history of human activity to determine a destination, this paper proposes a map-building method to express a history of human activity on a grid map. An experiment is conducted to evaluate the usefulness of the proposed approach for destination determination based on the subjects´ performance of the PMT operation and their mental workload.