Hybrid robust disturbance rejection position-force control to adjust the motion of mobile manipulator in automatic aluminum foundry recycling industries

ABSTRACT

This study presents the development of an event-driven hybrid control for position and force tracking applied on a mobile robotic manipulator for metal recycling tasks. The suggested controller operates in a sequenced strategy starting from a fixed spot, moving the mobile device towards a targeted zone (${\Omega }_i^r$) from where the i-th piece-to-be-recycled is attainable (considering the arm manipulation). Once the event of entering the zone is completed, the mobile robot is fixed at a position, and the end-effector of the robotic arm is enforced towards the piece-to-be-recycled. When the end-effector touches the piece in a given spot (${\Omega }_i^e$), the hybrid control changes to the force tracking intending to carry the piece towards the spot (${\Omega }_i^p$) where it ill be processed. Each piece location is identified based on a vision-based system that applies deep learning tools using convolutional neural networks. A multi-physics numerical simulation illustrated the application of the developed controller in a realistic scenario, showing all the elements of the event-driven operation. To validate the suggested controller, the comparison with a robust control that works on a wide range of carrying mass confirms the operational improvement of the event-driven hybrid position and force design.

KEYWORDS:

• Disturbance rejection control
• hybrid position-force control
• mobile robotic manipulator
• adaptive controller
• recycling industry

Acknowledgments

The authors would like to thank the Tecnologico de Monterrey Challenge-Based Research Program project ID IJXT070-22TE60001 and Programa para la Vinculación de Empresas con Instituciones de Educación Superior y Centros de Investigación Comecyt-EdoMex número de proyecto Vinculacion/2023/009.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, [author initials], upon reasonable request.

Additional information

Funding

The work was supported by the Instituto Tecnologico de Estudios Superiores de Monterrey, Challenge-Based Research Program [ID IKXT025-22UI60001].

Notes on contributors

Karen Mendoza-Bautista

Karen Mendoza-Bautista received a B.S. degree in biomedical engineering from the National Polytechnic Institute (IPN), Mexico City, Mexico, in 2019 and a master’s degree in Robotics and Advanced Manufacturing, Center of Investigation and Advanced Researching (CINVESTAV) campus Saltillo, IPN, in 2022. Actually, she is studying for a PhD at the Technological Institute of Monterrey (ITESM) in Engineering Sciences. She is also working as a part-time professor on the ITESM campus in Guadalajara. Her current research interests include robot control theory, surgical robots, adaptive control, and vision systems applied to robots. She has published about 3 papers in recognized technical journals.

Mariel Alfaro-Ponce

Mariel Alfaro-Ponce is an assistant professor in the Biomedical Engineering Program at Tecnológico de Monterrey Ciudad de Mexico; she received a bachelor’s degree in Biomedical Engineering, a Master of Science in Microelectronic Engineering, and a Ph.D. in Computer Science from the Instituto Politecnico Nacional, Mexico. Her research interests include artificial intelligence, rehabilitation devices, and intelligent bioinstrumentation. She has been a member of the National System of Researchers of Mexico (SNI-Level I). From 2022 until now, is the head of the Manufacturing Processes for Advanced Materials CDMX research unit.

Isaac Chairez

Isaac Chairez earned the B.S. degree in biomedical engineering from the National Polytechnic Institute (IPN), Mexico City, Mexico, in 2002, and the master’s and Ph.D. degrees from the Department of Automatic Control, Center of Investigation and Advanced Researching (CINVESTAV), IPN, in 2004 and 2007, respectively. He is currently with the National School of Sciences and Engineering of the Tecnológico de Monterrey and the Professional Interdisciplinary Unit of Biotechnology, IPN. He has published over 230 contributions in indexed journals and 300 in international conferences. He has published two books on the applications of neural networks on diverse disciplines. His current research interests include neural networks, fuzzy control theory, nonlinear control, adaptive control, and game theory.