A waypoint-based framework in brain-controlled smart home environments: Brain interfaces, domotics, and robotics integration

Atsunori Kanemura, Yoichi Morales Saiki, Motoaki Kawanabe, Hiroshi Morioka, Nagasrikanth Kallakuri, Tetsushi Ikeda, Takahiro Miyashita, Norihiro Hagita, Shin Ishii

Abstract: The noninvasive brain-machine interface (BMI) is anticipated to be an effective tool of communication not only in laboratory settings but also in our daily livings. The direct communication channel created by BMI can assist aging societies and the handicapped and improve human welfare. In this paper we propose and experiment a BMI framework that combines BMI with a robotic house and autonomous robotic wheelchair. Autonomous navigation is achieved by placing waypoints within the house and, from the user side, the user performs BMI to give commands to the house and wheelchair. The waypoint framework can offer essential services to the user with an effectively improved information-transfer rate and is an excellent examples of the fusion of data measured by sensors in the house, which can offer insight into further studies.