86 research outputs found

    Compliance error compensation in robotic-based milling

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    The paper deals with the problem of compliance errors compensation in robotic-based milling. Contrary to previous works that assume that the forces/torques generated by the manufacturing process are constant, the interaction between the milling tool and the workpiece is modeled in details. It takes into account the tool geometry, the number of teeth, the feed rate, the spindle rotation speed and the properties of the material to be processed. Due to high level of the disturbing forces/torques, the developed compensation technique is based on the non-linear stiffness model that allows us to modify the target trajectory taking into account nonlinearities and to avoid the chattering effect. Illustrative example is presented that deals with robotic-based milling of aluminum alloy

    Elasto-geometrical modeling and calibration of robot manipulators: Application to machining and forming applications

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    International audienceThis paper proposes an original elasto-geometrical calibration method to improve the static pose accuracy of industrial robots involved in machining, forming or assembly applications. Two approaches are presented respectively based on an analytical parametric modeling and a Takagi-Sugeno fuzzy inference system. These are described and then discussed. This allows to list the main drawbacks and advantages of each of them with respect to the task and the user requirements. The Fuzzy Logic model is used in a model-based compensation scheme to increase significantly the robot static pose accuracy in a context of incremental forming application. Experimental results show the efficiency of the Fuzzy Logic model while minimizing development and computational resources

    Compensation of Tool Deflection in Robotic-Based Milling

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    International audienceThe paper presents the compliance errors compensation technique for industrial robots, which are used in milling manufacturing cells. under external loading, which is based on the non-linear stiffness model. In contrast to previous works, it takes into account the interaction between the milling tool and the workpiece that depends on the end-effector position, process parameters and cutting conditions (spindle rotation, feed rate, geometry of the tool, etc.). Within the developed technique, the compensation errors caused by external loading is based on the non-linear stiffness model and reduces to a proper adjusting of a target trajectory that is modified in the off-line mode. The advantages and practical significance of the proposed technique are illustrated by an example that deals with milling with Kuka robot

    ModĂšle des interactions dynamiques

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    In robotic-based machining, an interaction between the workpiece and technological tool causes essential deflections that significantly decrease the manufacturing accuracy. Relevant compliance errors highly depend on the manipulator configuration and essentially differ throughout the workspace. Their influence is especially important for heavy serial robots. To overcome this difficulty this report presents a new technique for compensation of the compliance errors caused by technological process. In contrast to previous works, this technique is based on the non-linear stiffness model and the reduced elasto-dynamic model of the robotic based milling process. The advantages and practical significance of the proposed approach are illustrated by milling with of KUKA KR270. It is shown that after error compensation technique significantly increase the accuracy of milling.ANR COROUSS

    Compliance error compensation in robotic-based milling

    Get PDF
    The paper deals with the problem of compliance errors compensation in robotic-based milling. Contrary to previous works that assume that the forces/torques generated by the manufacturing process are constant, the interaction between the milling tool and the workpiece is modeled in details. It takes into account the tool geometry, the number of teeth, the feed rate, the spindle rotation speed and the properties of the material to be processed. Due to high level of the disturbing forces/torques, the developed compensation technique is based on the non-linear stiffness model that allows us to modify the target trajectory taking into account nonlinearities and to avoid the chattering effect. Illustrative example is presented that deals with robotic-based milling of aluminum alloy

    ModĂšle des interactions dynamiques

    Get PDF
    In robotic-based machining, an interaction between the workpiece and technological tool causes essential deflections that significantly decrease the manufacturing accuracy. Relevant compliance errors highly depend on the manipulator configuration and essentially differ throughout the workspace. Their influence is especially important for heavy serial robots. To overcome this difficulty this report presents a new technique for compensation of the compliance errors caused by technological process. In contrast to previous works, this technique is based on the non-linear stiffness model and the reduced elasto-dynamic model of the robotic based milling process. The advantages and practical significance of the proposed approach are illustrated by milling with of KUKA KR270. It is shown that after error compensation technique significantly increase the accuracy of milling.ANR COROUSS

    Kinematic analysis and optimization of robotic milling

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    Robotic milling is proposed to be one of the alternatives to respond the demand for flexible and cost-effective manufacturing systems. Serial arm robots offering 6 degrees of freedom (DOF) motion capability which are utilized for robotic 5-axis milling purposes, exhibits several issues such as low accuracy, low structural rigidity and kinematic singularities etc. In 5-axis milling, the tool axis selection and workpiece positioning are still a challenge, where only geometrical issues are considered at the computer-aided-manufacturing (CAM) packages. The inverse kinematic solution of the robot i.e. positions and motion of the axes, strictly depends on the workpiece location with respect to the robot base. Therefore, workpiece placement is crucial for improved robotic milling applications. In this thesis, an approach is proposed to select the tool axis for robotic milling along an already generated 5-axis milling tool path, where the robot kinematics are considered to eliminate or decrease excessive axis rotations. The proposed approach is demonstrated through simulations and benefits are discussed. Also, the effect of workpiece positioning in robotic milling is investigated considering the robot kinematics. The investigation criterion is selected as the movement of the robot axes. It is aimed to minimize the total movement of either all axes or selected the axis responsible of the most accuracy errors. Kinematic simulations are performed on a representative milling tool path and results are discusse

    Robot Learning for Manipulation of Deformable Linear Objects

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    Deformable Object Manipulation (DOM) is a challenging problem in robotics. Until recently there has been limited research on the subject, with most robotic manipulation methods being developed for rigid objects. Part of the challenge in DOM is that non-rigid objects require solutions capable of generalizing to changes in shape and mechanical properties. Recently, Machine Learning (ML) has been proven successful in other fields where generalization is important such as computer vision, thus encouraging the application of ML to robotics as well. Notably, Reinforcement Learning (RL) has shown promise in finding control policies for manipulation of rigid objects. However, RL requires large amounts of data that are better satisfied in simulation while deformable objects are inherently more difficult to model and simulate. This thesis presents ReForm, a simulation sandbox for robotic manipulation of Deformable Linear Objects (DLOs) such as cables, ropes, and wires. DLO manipulation is an interesting problem for a variety of applications throughout manufacturing, agriculture, and medicine. Currently, this sandbox includes six shape control tasks, which are classified as explicit when a precise shape is to be achieved, or implicit when the deformation is just a consequence of a more abstract goal, e.g. wrapping a DLO around another object. The proposed simulation environments aim to facilitate comparison and reproducibility of robot learning research. To that end, an RL algorithm is tested on each simulated task providing initial benchmarking results. ReForm is one of three concurrent frameworks to first support DOM problems. This thesis also addresses the problem of DLO state representation for an explicit shape control problem. Moreover, the effects of elastoplastic properties on the RL reward definition are investigated. From a control perspective, DLOs with these properties are particularly challenging to manipulate due to their nonlinear behavior, acting elastic up to a yield point after which they become permanently deformed. A low-dimensional representation from discrete differential geometry is proposed, offering more descriptive shape information than a simple point-cloud while avoiding the need for curve fitting. Empirical results show that this representation leads to a better goal description in the presence of elastoplasticity, preventing the RL algorithm from converging to local minima which correspond to incorrect shapes of the DLO

    Kinematics and Robot Design II (KaRD2019) and III (KaRD2020)

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    This volume collects papers published in two Special Issues “Kinematics and Robot Design II, KaRD2019” (https://www.mdpi.com/journal/robotics/special_issues/KRD2019) and “Kinematics and Robot Design III, KaRD2020” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2020), which are the second and third issues of the KaRD Special Issue series hosted by the open access journal robotics.The KaRD series is an open environment where researchers present their works and discuss all topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. It aims at being an established reference for researchers in the field as other serial international conferences/publications are. Even though the KaRD series publishes one Special Issue per year, all the received papers are peer-reviewed as soon as they are submitted and, if accepted, they are immediately published in MDPI Robotics. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”.KaRD2019 together with KaRD2020 received 22 papers and, after the peer-review process, accepted only 17 papers. The accepted papers cover problems related to theoretical/computational kinematics, to biomedical engineering and to other design/applicative aspects
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