A shared control architecture based on electrooculogram signal and global vision for smart assistive robots
Lei Sun, Hua Chen, YangQuan Chen · 2017 IEEE International Conference on Unmanned Systems (ICUS) · 2017
Assistive robots play an increasingly important role in the lives of people with disabilities. More and more research efforts are being focused on using Electrooculogram (EOG) signals in driving assistive robots. This paper presents a new shared control architecture based on EOG signal and global vision for assistive robots. This paper firstly introduces the shared control concept with detailed block diagrams and then presents the work flow process of EOG signal acquisition and angle recognition. A state machine design is also presented that makes the control command transfer sequentially. Finally, control strategies of intent conflict and intent consistency, respectively, are also presented for different intent expression scenarios. Experiment results demonstrate that the shared control architecture proposed in this paper is effective that can reduce the user's operational load significantly.