Human-Machine Interface for Remote Training of Robot Tasks

Regardless of their industrial or research application, the streamlining of robot operations is limited by the proximity of experienced users to the actual hardware. Be it massive open online robotics courses, crowd-sourcing of robot task training, or remote research on massive robot farms for machine learning, the need to create an apt remote Human-Machine Interface is quite prevalent. The paper at hand proposes a novel solution to the programming/training of remote robots employing an intuitive and accurate user-interface which offers all the benefits of working with real robots without imposing delays and inefficiency. The system includes: a vision-based 3D hand detection and gesture recognition subsystem, a simulated digital twin of a robot as visual feedback, and the "remote" robot learning/executing trajectories using dynamic motion primitives. Our results indicate that the system is a promising solution to the problem of remote training of robot tasks.Comment: Accepted in IEEE International Conference on Imaging Systems and Techniques - IST201

An Analytical Approach to Avoid Obstacles in Mobile Robot Navigation

A nonlinear supervised globally stable controller is proposed to reactively guide a mobile robot to avoid obstacles while seeking a goal. Whenever the robot detects an object nearby, its orientation is changed to be aligned with the tangent to the border of the obstacle. Then, the robot starts following it, looking for a feasible path to its goal. The supervisor is responsible for deciding which path to take when the robot faces some particular obstacle configurations that are quite difficult to deal with. Several simulations and experiments were run to validate the proposal, some of which are discussed here. To run the experiments, the proposed controller is programmed into the onboard computer of a real unicycle mobile platform, equipped with a laser range scanner. As for the simulations, the models of the same experimental setup were used. The final conclusion is that the nonlinear supervised controller proposed to solve the problem of avoiding obstacles during goal seeking has been validated, based on the theoretical analysis, and the simulated and experimental results.Fil: Brandao, Alexandre Santos. Federal University of Viçosa. Department of Electrical Engineering; BrasilFil: Sarcinelli Filho, Mário . Federal University of Espírito Santo. Department of Electrical Engineering; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Universidad Nacional de San Juan. Facultad de Ingenieria. Instituto de Automática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin