9 research outputs found

    Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

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    [EN] The rise of collaborative robots urges the consideration of them for different industrial tasks such as sanding. In this context, the purpose of this article is to demonstrate the feasibility of using collaborative robots in processing operations, such as orbital sanding. For the demonstration, the tools and working conditions have been adjusted to the capacity of the robot. Materials with different characteristics have been selected, such as aluminium, steel, brass, wood, and plastic. An inner/outer control loop strategy has been used, complementing the robot¿s motion control with an outer force control loop. After carrying out an explanatory design of experiments, it was observed that it is possible to perform the operation in all materials, without destabilising the control, with a mean force error of 0.32%. Compared with industrial robots, collaborative ones can perform the same sanding task with similar results. An important outcome is that unlike what might be thought, an increase in the applied force does not guarantee a better finish. In fact, an increase in the feed rate does not produce significant variation in the finish¿less than 0.02 m; therefore, the process is in a ¿saturation state¿ and it is possible to increase the feed rate to increase productivity.Rodrigo Perez-Ubeda is grateful to the Ph.D. Grant CONICYT PFCHA/Doctorado Becas Chile/2017-72180157 and the University of Antofagasta, Chile.Pérez Ubeda, R.; Gutiérrez, SC.; Zotovic Stanisic, R.; Perles, A. (2020). Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials. Materials. 14(1):1-19. https://doi.org/10.3390/ma14010067S11914

    Propuesta de inclusión de esfuerzos en el control de un brazo robot para asegurar el cumplimiento de la rugosidad superficial durante operaciones de lijado en diferentes materiales

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    Tesis por compendio[ES] El mecanizado con brazos robots ha sido estudiado aproximadamente desde los años 90, durante este tiempo se han llevado a cabo importantes avances y descubrimientos en cuanto a su campo de aplicación. En general, los robots manipuladores tienen muchos beneficios y ventajas al ser usados en operaciones de mecanizado, tales como, flexibilidad, gran área de trabajo y facilidad de programación, entre otras, frente a las Máquinas Herramientas de Control numérico (MHCN) que necesitan de una gran inversión para trabajar piezas muy grandes o incrementar sus grados de libertad. Como desventajas, frente a las MHCN, los brazos robóticos poseen menor rigidez, lo que combinado con las altas fuerzas producidas en los procesos de mecanizado hace que aparezcan errores de precisión, desviaciones en las trayectorias, vibraciones y, por consiguiente, una mala calidad en las piezas fabricadas. Entre los brazos robots, los brazos colaborativos están en auge debido a su programación intuitiva y a sus medidas de seguridad, que les permiten trabajar en el mismo espacio que los operadores sin que estos corran riesgos. Como desventaja añadida de los robots colaborativos se encuentra la mayor flexibilidad que estos tienen en sus articulaciones, debido a que incluyen reductores del tipo Harmonic drive. El uso de un control de fuerza en procesos de mecanizado con brazos robots permite controlar y corregir en tiempo real las desviaciones generadas por la flexibilidad en las articulaciones del robot. Utilizar este método de control es beneficioso en cualquier brazo robot; sin embargo, el control interno que incluyen los robots colaborativos presenta ventajas que permiten que el control de fuerza pueda ser aplicado de una manera más eficiente. En el presente trabajo se desarrolla una propuesta real para la inclusión del control de esfuerzos en el brazo robot, así como también, se evalúa y cuantifica la capacidad de los robots industriales y colaborativos en tareas de mecanizado. La propuesta plantea cómo mejorar la utilización de un control de fuerza por bucle interior/exterior aplicado en un brazo colaborativo cuando se desconocen los pares reales de los motores del robot, así como otros parámetros internos que los fabricantes no dan a conocer. Este bucle de control interior/exterior ha sido utilizado en aplicaciones de pulido y lijado sobre diferentes materiales. Los resultados indican que el robot colaborativo es factible para realizar tales operaciones de mecanizado. Sus mejores resultados se obtienen cuando se utiliza un bucle de control interno por velocidad y un bucle de control externo de fuerza con algoritmos, Proporcional-Integral-Derivativo o Proporcional más Pre-Alimentación de la Fuerza.[CA] El mecanitzat amb braços robots ha estat estudiat aproximadament des dels anys 90, durant aquest temps s'han dut a terme importants avanços i descobriments en el que fa al seu camp d'aplicació. En general, els robots manipuladors tenen molts beneficis i avantatges al ser usats en operacions de mecanitzat, com ara, flexibilitat, gran àrea de treball i facilitat de programació, entre d'altres, davant de Màquines Eines de Control Numèric (MECN) que necessiten d'una gran inversió per treballar peces molt grans o incrementar els seus graus de llibertat. Com a desavantatges, enfront de les MECN, els braços robòtics posseeixen menor rigidesa, el que combinat amb les altes forces produïdes en els processos de mecanitzat fa que apareguin errors de precisió, desviacions en les trajectòries, vibracions i, per tant, una mala qualitat en les peces fabricades. Entre els braços robots, els braços col·laboratius estan en auge a causa de la seva programació intuïtiva i a les seves mesures de seguretat, que els permeten treballar en el mateix espai que els operadors sense que aquests corrin riscos. Com desavantatge afegida als robots col·laboratius es troba la major flexibilitat que aquests tenen en les seves articulacions, a causa de que inclouen reductors del tipus Harmonic drive. L'ús d'un control de força en processos de mecanitzat amb braços robots permet controlar, i corregir, en temps real les desviacions generades per la flexibilitat en les articulacions del robot. Utilitzar aquest mètode de control és beneficiós en qualsevol braç robot, però, el control intern que inclouen els robots col·laboratius presenta avantatges que permeten que el control de força es puga aplicar d'una manera més eficient. En el present treball es desenvolupa una proposta real per a la inclusió del control d'esforços en el braç robot, així com s'avalua i quantifica la capacitat dels robots industrials i col·laboratius en tasques de mecanitzat. La proposta planteja com millorar la utilització d'un control de força per bucle interior/exterior aplicat en un braç col·laboratiu, quan es desconeixen els parells reals dels motors del robot, així com altres paràmetres interns que els fabricants no donen a conèixer. Aquest bucle de control interior/exterior ha estat utilitzat en aplicacions de polit sobre diferents materials. Els resultats indiquen que el robot col·laboratiu és factible de realitzar aquestes operacions de mecanitzat. Els seus millors resultats s'obtenen quan s'utilitza un bucle de control intern per velocitat i un bucle de control extern de força amb els algoritmes Proporcional-Integral-Derivatiu o Proporcional més Pre-alimentació de la Força.[EN] Machining with robot arms has been studied approximately since the 90s; during this time, important advances and discoveries have been made in its field of application. In general, manipulative robots have many benefits and advantages when they are used in machining operations, such as flexibility, large work area, and ease of programming, among others, compared to Numerical Control Machine Tools (NCMT) that need a great investment to work very large pieces or increase their degrees of freedom. As for disadvantages, compared to NCMT, robotic arms have lower rigidity, which, combined with the high forces produced in machining processes, causes precision errors, path deviations, vibrations, and, consequently, poor quality in the manufactured parts. Among robot arms, collaborative arms are on the rise due to their intuitive programming and safety measures, which allow them to work in the same space without risk for the operators. An added disadvantage of collaborative robots is their flexibility in their joints because they include Harmonic drive type reducers. The use of force control in machining processes with robot arms makes possible to control and correct, in real-time, the deviations generated by the flexibility in the robot's joints. The use of this control method is beneficial for any robot arm. However, the internal control included in collaborative robots has advantages that allow the force control to be applied more efficiently. In this work, a real proposal is developed to include effort control in the robot arm. The capacity of industrial and collaborative robots in machining tasks is evaluated and quantified. The proposal recommends how to improve the use of an inner/outer force control loop applied in a collaborative arm, when the real torques of the robot's motors are unknown and other internal parameters that manufacturers do not disclose. This inner/outer control loop has been used in polishing and sanding applications on different materials. The results indicate that the collaborative robot is feasible to perform such machining operations. Best results are obtained using an internal velocity control loop and external force control loop with Proportional-Integral-Derivative or Proportional plus Feed Forward.The authors are grateful for the financial support of the Spanish Ministry of Economy and European Union, grant DPI2016-81002-R (AEI/FEDER, UE). This work was funded by the CONICYT PFCHA/DOCTORADO BECAS CHILE/2017 – 72180157.Pérez Ubeda, RA. (2022). Propuesta de inclusión de esfuerzos en el control de un brazo robot para asegurar el cumplimiento de la rugosidad superficial durante operaciones de lijado en diferentes materiales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/182000TESISCompendi

    Force Control Improvement in Collaborative Robots through Theory Analysis and Experimental Endorsement

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    [EN] Due to the elasticity of their joints, collaborative robots are seldom used in applications with force control. Besides, the industrial robot controllers are closed and do not allow the user to access the motor torques and other parameters, hindering the possibility of carrying out a customized control. A good alternative to achieve a custom force control is sending the output of the force regulator to the robot controller through motion commands (inner/outer loop control). There are different types of motion commands (e.g., position or velocity). They may be implemented in different ways (Jacobian inverse vs. Jacobian transpose), but this information is usually not available for the user. This article is dedicated to the analysis of the effect of different inner loops and their combination with several external controllers. Two of the most determinant factors found are the type of the inner loop and the stiffness matrix. The theoretical deductions have been experimentally verified on a collaborative robot UR3, allowing us to choose the best behaviour in a polishing operation according to pre-established criteria.The authors are grateful for the financial support of the Spanish Ministry of Economy and European Union, grant DPI2016-81002-R (AEI/FEDER, UE), to the research work here published. Rodrigo Perez-Ubeda is grateful to the Ph.D. Grant CONICYT PFCHA/DOCTORADO BECAS CHILE/2017-72180157.Pérez-Ubeda, R.; Zotovic Stanisic, R.; Gutiérrez, SC. (2020). Force Control Improvement in Collaborative Robots through Theory Analysis and Experimental Endorsement. Applied Sciences. 10(12):1-24. https://doi.org/10.3390/app10124329S1241012Top Trends Robotics 2020—International Federation of Robotics https://ifr.org/ifr-press-releases/news/top-trends-robotics-2020Gaz, C., Magrini, E., & De Luca, A. (2018). A model-based residual approach for human-robot collaboration during manual polishing operations. Mechatronics, 55, 234-247. doi:10.1016/j.mechatronics.2018.02.014Iglesias, I., Sebastián, M. A., & Ares, J. E. (2015). Overview of the State of Robotic Machining: Current Situation and Future Potential. Procedia Engineering, 132, 911-917. doi:10.1016/j.proeng.2015.12.577Perez-Ubeda, R., Gutierrez, S. C., Zotovic, R., & Lluch-Cerezo, J. (2019). Study of the application of a collaborative robot for machining tasks. Procedia Manufacturing, 41, 867-874. doi:10.1016/j.promfg.2019.10.009Spong, M. W. (1989). On the force control problem for flexible joint manipulators. IEEE Transactions on Automatic Control, 34(1), 107-111. doi:10.1109/9.8661Ren, T., Dong, Y., Wu, D., & Chen, K. (2019). Impedance control of collaborative robots based on joint torque servo with active disturbance rejection. Industrial Robot: the international journal of robotics research and application, 46(4), 518-528. doi:10.1108/ir-06-2018-0130Ajoudani, A., Tsagarakis, N. G., & Bicchi, A. (2017). Choosing Poses for Force and Stiffness Control. IEEE Transactions on Robotics, 33(6), 1483-1490. doi:10.1109/tro.2017.2708087Magrini, E., & De Luca, A. (2016). Hybrid force/velocity control for physical human-robot collaboration tasks. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). doi:10.1109/iros.2016.7759151Ahmad, S. (1993). Constrained motion (force/position) control of flexible joint robots. IEEE Transactions on Systems, Man, and Cybernetics, 23(2), 374-381. doi:10.1109/21.229451Calanca, A., & Fiorini, P. (2018). Understanding Environment-Adaptive Force Control of Series Elastic Actuators. IEEE/ASME Transactions on Mechatronics, 23(1), 413-423. doi:10.1109/tmech.2018.2790350Oh, S., & Kong, K. (2017). High-Precision Robust Force Control of a Series Elastic Actuator. IEEE/ASME Transactions on Mechatronics, 22(1), 71-80. doi:10.1109/tmech.2016.2614503Yin, H., Li, S., & Wang, H. (2016). Sliding mode position/force control for motion synchronization of a flexible-joint manipulator system with time delay. 2016 35th Chinese Control Conference (CCC). doi:10.1109/chicc.2016.7554329Ma, Z., Hong, G.-S., Ang, M. H., Poo, A.-N., & Lin, W. (2018). A Force Control Method with Positive Feedback for Industrial Finishing Applications. 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). doi:10.1109/aim.2018.8452689Huang, L., Ge, S. S., & Lee, T. H. (2006). Position/force control of uncertain constrained flexible joint robots. Mechatronics, 16(2), 111-120. doi:10.1016/j.mechatronics.2005.10.002Chiaverini, S., Siciliano, B., & Villani, L. (1999). A survey of robot interaction control schemes with experimental comparison. IEEE/ASME Transactions on Mechatronics, 4(3), 273-285. doi:10.1109/3516.789685Winkler, A., & Suchy, J. (2016). Explicit and implicit force control of an industrial manipulator — An experimental summary. 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR). doi:10.1109/mmar.2016.7575081Neranon, P., & Bicker, R. (2016). Force/position control of a robot manipulator for human-robot interaction. Thermal Science, 20(suppl. 2), 537-548. doi:10.2298/tsci151005036nChen, S., Zhang, T., & Zou, Y. (2017). Fuzzy-Sliding Mode Force Control Research on Robotic Machining. Journal of Robotics, 2017, 1-8. doi:10.1155/2017/8128479Lin, H.-I., & Dubey, V. (2018). Design of an Adaptive Force Controlled Robotic Polishing System Using Adaptive Fuzzy-PID. Advances in Intelligent Systems and Computing, 825-836. doi:10.1007/978-3-030-01370-7_64Perez-Vidal, C., Gracia, L., Sanchez-Caballero, S., Solanes, J. E., Saccon, A., & Tornero, J. (2019). Design of a polishing tool for collaborative robotics using minimum viable product approach. International Journal of Computer Integrated Manufacturing, 32(9), 848-857. doi:10.1080/0951192x.2019.1637026Chen, F., Zhao, H., Li, D., Chen, L., Tan, C., & Ding, H. (2019). Contact force control and vibration suppression in robotic polishing with a smart end effector. Robotics and Computer-Integrated Manufacturing, 57, 391-403. doi:10.1016/j.rcim.2018.12.019Mohammad, A. E. K., Hong, J., & Wang, D. (2018). Design of a force-controlled end-effector with low-inertia effect for robotic polishing using macro-mini robot approach. Robotics and Computer-Integrated Manufacturing, 49, 54-65. doi:10.1016/j.rcim.2017.05.011Xiao, C., Wang, Q., Zhou, X., Xu, Z., Lao, X., & Chen, Y. (2019). Hybrid Force/Position Control Strategy for Electromagnetic based Robotic Polishing Systems. 2019 Chinese Control Conference (CCC). doi:10.23919/chicc.2019.8865183Li, J., Zhang, T., Liu, X., Guan, Y., & Wang, D. (2018). A Survey of Robotic Polishing. 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO). doi:10.1109/robio.2018.8664890Zollo, L., Siciliano, B., De Luca, A., Guglielmelli, E., & Dario, P. (2004). Compliance Control for an Anthropomorphic Robot with Elastic Joints: Theory and Experiments. Journal of Dynamic Systems, Measurement, and Control, 127(3), 321-328. doi:10.1115/1.1978911Han, D., Duan, X., Li, M., Cui, T., Ma, A., & Ma, X. (2017). Interaction Control for Manipulator with compliant end-effector based on hybrid position-force control. 2017 IEEE International Conference on Mechatronics and Automation (ICMA). doi:10.1109/icma.2017.8015929Schindlbeck, C., & Haddadin, S. (2015). Unified passivity-based Cartesian force/impedance control for rigid and flexible joint robots via task-energy tanks. 2015 IEEE International Conference on Robotics and Automation (ICRA). doi:10.1109/icra.2015.7139036Zotovic Stanisic, R., & Valera Fernández, Á. (2009). Simultaneous velocity, impact and force control. Robotica, 27(7), 1039-1048. doi:10.1017/s0263574709005451Volpe, R., & Khosla, P. (1993). A theoretical and experimental investigation of explicit force control strategies for manipulators. IEEE Transactions on Automatic Control, 38(11), 1634-1650. doi:10.1109/9.262033Zeng, G., & Hemami, A. (1997). An overview of robot force control. Robotica, 15(5), 473-482. doi:10.1017/s026357479700057xSalisbury, J. (1980). Active stiffness control of a manipulator in cartesian coordinates. 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes. doi:10.1109/cdc.1980.272026Chen, S.-F., & Kao, I. (2000). Conservative Congruence Transformation for Joint and Cartesian Stiffness Matrices of Robotic Hands and Fingers. The International Journal of Robotics Research, 19(9), 835-847. doi:10.1177/02783640022067201Institute of Robotics and Mechatronics DLR Light Weight Robot III https://www.dlr.de/rm/en/desktopdefault.aspx/tabid-12464/#gallery/2916

    Control System Development for small UAV Gimbal

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    The design process of unmanned ISR systems has typically driven in the direction of increasing system mass to increase stabilization performance and imagery quality. However, through the use of new sensor and processor technology high performance stabilization feedback is being made available for control on new small and low mass stabilized platforms that can be placed on small UAVs. This project develops and implements a LOS stabilization controller design, typically seen on larger gimbals, onto a new small stabilized gimbal, the Tigereye, and demonstrates the application on several small UAV aircraft. The Tigereye gimbal is a new 2lb, 2-axis, gimbal intended to provided high performance closed loop LOS stabilization through the utilization of inertial rate gyro, electronic video stabilization, and host platform state information. Ground and flight tests results of the LOS stabilization controller on the Tigereye gimbal have shown stabilization performance improvements over legacy systems. However, system characteristics identified in testing still limit stabilization performance, these include: host system vibration, gimbal joint friction and backlash, joint actuation compliance, payload CG asymmetry, and gyro noise and drift. The control system design has been highly modularized in anticipation of future algorithm and hardware upgrades to address the remaining issues and extend the system\u27s capabilities

    Predictive Context-Based Adaptive Compliance for Interaction Control of Robot Manipulators

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    In classical industrial robotics, robots are concealed within structured and well-known environments performing highly-repetitive tasks. In contrast, current robotic applications require more direct interaction with humans, cooperating with them to achieve a common task and entering home scenarios. Above all, robots are leaving the world of certainty to work in dynamically-changing and unstructured environments that might be partially or completely unknown to them. In such environments, controlling the interaction forces that appear when a robot contacts a certain environment (be the environment an object or a person) is of utmost importance. Common sense suggests the need to leave the stiff industrial robots and move towards compliant and adaptive robot manipulators that resemble the properties of their biological counterpart, the human arm. This thesis focuses on creating a higher level of intelligence for active compliance control methods applied to robot manipulators. This work thus proposes an architecture for compliance regulation named Predictive Context-Based Adaptive Compliance (PCAC) which is composed of three main components operating around a 'classical' impedance controller. Inspired by biological systems, the highest-level component is a Bayesian-based context predictor that allows the robot to pre-regulate the arm compliance based on predictions about the context the robot is placed in. The robot can use the information obtained while contacting the environment to update its context predictions and, in case it is necessary, to correct in real time for wrongly predicted contexts. Thus, the predictions are used both for anticipating actions to be taken 'before' proceeding with a task as well as for applying real-time corrective measures 'during' the execution of a in order to ensure a successful performance. Additionally, this thesis investigates a second component to identify the current environment among a set of known environments. This in turn allows the robot to select the proper compliance controller. The third component of the architecture presents the use of neuroevolutionary techniques for selecting the optimal parameters of the interaction controller once a certain environment has been identified

    A homography-based dynamic control approach of Autonomous Underwater Vehicles observing a (near) vertical target without linear velocity measurements

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    The paper addresses the challenging problem of image-based dynamic control of Autonomous Underwater Vehicles observing a (near) vertical planar target, without measuring the linear velocity. The proposed control approach exploits a minimum sensor suite consisting of a camera looking forward to provide images from which the homography matrix is extracted and an IMU providing angular velocity and gravity direction measurements. The dynamics of the AUV are exploited in a hierarchical control scheme with inner-outer control loop architecture. Rigourous stability analysis is established. The performance of the proposed approach is illustrated via simulation results conducted on a realistic AUV model

    Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

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    The rise of collaborative robots urges the consideration of them for different industrial tasks such as sanding. In this context, the purpose of this article is to demonstrate the feasibility of using collaborative robots in processing operations, such as orbital sanding. For the demonstration, the tools and working conditions have been adjusted to the capacity of the robot. Materials with different characteristics have been selected, such as aluminium, steel, brass, wood, and plastic. An inner/outer control loop strategy has been used, complementing the robot’s motion control with an outer force control loop. After carrying out an explanatory design of experiments, it was observed that it is possible to perform the operation in all materials, without destabilising the control, with a mean force error of 0.32%. Compared with industrial robots, collaborative ones can perform the same sanding task with similar results. An important outcome is that unlike what might be thought, an increase in the applied force does not guarantee a better finish. In fact, an increase in the feed rate does not produce significant variation in the finish—less than 0.02 µm; therefore, the process is in a “saturation state” and it is possible to increase the feed rate to increase productivity

    A Path-Following Controller for Marine Vehicles Using a Two-Scale Inner-Outer Loop Approach

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    This article addresses the problem of path following of marine vehicles along straight lines in the presence of currents by resorting to an inner-outer control loop strategy, with due account for the presence of currents. The inner-outer loop control structures exhibit a fast-slow temporal scale separation that yields simple “rules of thumb” for controller tuning. Stated intuitively, the inner-loop dynamics should be much faster than those of the outer loop. Conceptually, the procedure described has three key advantages: (i) it decouples the design of the inner and outer control loops, (ii) the structure of the outer-loop controller does not require exact knowledge of the vehicle dynamics, and (iii) it provides practitioners a very convenient method to effectively implement path-following controllers on a wide range of vehicles. The path-following controller discussed in this article is designed at the kinematic outer loop that commands the inner loop with the desired heading angles while the vehicle moves at an approximately constant speed. The key underlying idea is to provide a seamless implementation of path-following control algorithms on heterogeneous vehicles, which are often equipped with heading autopilots. To this end, we assume that the heading control system is characterized in terms of an IOS-like relationship without detailed knowledge of vehicle dynamics parameters. This paper quantitatively evaluates the combined inner-outer loop to obtain a relationship for assessing the combined system’s stability. The methods used are based on nonlinear control theory, wherein the cascade and feedback systems of interest are characterized in terms of their IOS properties. We use the IOS small-gain theorem to obtain quantitative relationships for controller tuning that are applicable to a broad range of marine vehicles. Tests with AUVs and one ASV in real-life conditions have shown the efficacy of the path-following control structure developed
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