Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Improving robotic machining accuracy through experimental error investigation and modular compensation

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis

Control Strategies for Machining with Industrial Robots

This thesis presents methods for improving machining with industrial robots using control, with focus on increasing positioning accuracy and controlling feed rate. The strong process forces arising during high-speed machining operations, combined with the limited stiffness of industrial robots, have hampered the usage of industrial robots in high-end machining tasks. However, since such manipulators may offer flexible and cost-effective machining solutions compared to conventional machine tools, it is of interest to increase the achievable accuracy using industrial robots. In this thesis, several different methods to increase the machining accuracy are presented. Modeling and control of a piezo-actuated high-dynamic compensation mechanism for usage together with an industrial robot during a machining operation, such as milling in aluminium, is considered. Position control results from experiments are provided, as well as an experimental verification of the benefit of utilizing the online compensation scheme. It is shown that the milling surface accuracy achieved with the proposed compensation mechanism is increased by up to three times compared to the uncompensated case. Because of the limited workspace and the higher bandwidth of the compensator compared to the robot, a mid-ranging approach for control of the relative position between the robot and the compensator is proposed. An adaptive, model-based solution is presented, which is verified through simulations as well as experiments, where a close correspondence with the simulations was achieved. Comparing the IAE from experiments using the proposed controller to previously established methods, a performance increase of up to 56 % is obtained. Additionally, two different approaches to increasing the accuracy of the machining task are also presented in this thesis. The first method is based on identifying a stiffness model of the robot, and using online force measurements in order to modify the position of the robot to compensate for position deflections. The second approach uses online measurements from an optical tracking system to suppress position deviations. In milling experiments performed in aluminium, the absolute accuracy was increased by up to a factor of approximately 6 and 9, for the two approaches, respectively. Robotic machining is often performed using position feedback with a conservative feed rate, to avoid excessive process forces. By controlling the applied force, realized by adjusting the feed rate of the workpiece, precise control over the material removal can be exercised. This will in turn lead to maximization of the time-efficiency of the machining task, since the maximum amount of material can be removed per time unit. This thesis presents an adaptive force controller, based on a derived model of the machining process and an identified model of the Cartesian dynamics of the robot. The controller is evaluated in both simulation and an experimental setup

Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis

The study describes the design and development of a single degree-of-freedom haptic robot, Haptic Theradrive, for post-stroke arm rehabilitation for in-home and clinical use. The robot overcomes many of the weaknesses of its predecessor, the TheraDrive system, that used a Logitech steering wheel as the haptic interface for rehabilitation. Although the original TheraDrive system showed success in a pilot study, its wheel was not able to withstand the rigors of use. A new haptic robot was developed that functions as a drop-in replacement for the Logitech wheel. The new robot can apply larger forces in interacting with the patient, thereby extending the functionality of the system to accommodate low-functioning patients. A new software suite offers appreciably more options for tailored and tuned rehabilitation therapies. In addition to describing the design of the hardware and software, the paper presents the results of simulation and experimental case studies examining the system\u27s performance and usability

A spatial impedance controller for robotic manipulation

Mechanical impedance is the dynamic generalization of stiffness, and determines interactive behavior by definition. Although the argument for explicitly controlling impedance is strong, impedance control has had only a modest impact on robotic manipulator control practice. This is due in part to the fact that it is difficult to select suitable impedances given tasks. A spatial impedance controller is presented that simplifies impedance selection. Impedance is characterized using ¿spatially affine¿ families of compliance and damping, which are characterized by nonspatial and spatial parameters. Nonspatial parameters are selected independently of configuration of the object with which the robot must interact. Spatial parameters depend on object configurations, but transform in an intuitive, well-defined way. Control laws corresponding to these compliance and damping families are derived assuming a commonly used robot model. While the compliance control law was implemented in simulation and on a real robot, this paper emphasizes the underlying theor

A Framework of Hybrid Force/Motion Skills Learning for Robots

Human factors and human-centred design philosophy are highly desired in today’s robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more likeable but also improve their performance. In particular, skill transfer by imitation learning can increase usability and acceptability of robots by the users without computer programming skills. In fact, besides positional information, muscle stiffness of the human arm, contact force with the environment also play important roles in understanding and generating human-like manipulation behaviours for robots, e.g., in physical HRI and tele-operation. To this end, we present a novel robot learning framework based on Dynamic Movement Primitives (DMPs), taking into consideration both the positional and the contact force profiles for human-robot skills transferring. Distinguished from the conventional method involving only the motion information, the proposed framework combines two sets of DMPs, which are built to model the motion trajectory and the force variation of the robot manipulator, respectively. Thus, a hybrid force/motion control approach is taken to ensure the accurate tracking and reproduction of the desired positional and force motor skills. Meanwhile, in order to simplify the control system, a momentum-based force observer is applied to estimate the contact force instead of employing force sensors. To deploy the learned motion-force robot manipulation skills to a broader variety of tasks, the generalization of these DMP models in actual situations is also considered. Comparative experiments have been conducted using a Baxter Robot to verify the effectiveness of the proposed learning framework on real-world scenarios like cleaning a table

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 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

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

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