A Novel Shared Position Control Method for Robot Navigation Via Low Throughput Human-Machine Interfaces

Abstract

In this paper, we analyze systems with low throughput human-machine interfaces (such as a brain-computer interface, single switch interface) from the controls perspective. We develop some principles for performance improvement in such systems based on the parallelization of inference and robot motion. The proposed principles are used to design a novel shared position control to navigate a circular massless holonomic robot in a known environment. The system is implemented in simulation and integrated with a real robotic wheelchair. Robot experiments demonstrated the viability of the proposed navigation method in various modes of operation.