Smoothly adjustable autonomy for the low-level remote control of mobile robots that is independent of the navigation algorithm

Abstract

Autonomy in robotics can be seen as a continuum in which we can select different levels of collaborative control between humans and robots, ranging from tele-operation (full control by the human) to full autonomy. In many practical applications, the main issues are which intermediate levels of autonomy are available and how to change from one to another. In this paper we are interested in providing smoothly adjustable autonomy to remotely controlled mobile robots, that is, an automatic mechanism for selecting the degree of collaborative control that remains mostly unnoticed to the human in normal situations, providing him/her the maximum sense of control that is possible at every time. Adjustable autonomy has been reported previously, but not pursuing simultaneously: i) to control remotely a mobile robot at the servo-process level (i.e., direct control commands), ii) to be independent from the use of a given particular navigation algorithm, and iii) to change the autonomy level smoothly. Our solution is based on a motion demultiplexer that predicts, using the robot kinematics, target locations where the user intends to place the mobile platform in the future. Our experiments show that all the requirements of our approach can be satisfied with minimum modifications to existing robotic control software.