The paper proposes a Δ-Y transformations technique for stiffness modelling of over-constrained manipulators with internal cross-linkages. It allows representing complex structures as a serial-parallel equivalent one that can be easily handled by the VJM-based method. To derive desired analytical expressions for the equivalent serial-parallel structure, the MSA-based stiffness modelling approach is employed first, which allows describing the stiffness response for both the Δ and Y structures operating with VJM-type stiffness matrices. Further, the desired relations between equivalent Δ-Y and Y-Δ stiffness matrices are obtained. The example of stiffness modelling of a non-rigid Gough-Stewart platform with multiple cross-linkages demonstrates the benefits of the proposed technique.

The paper deals with stiffness matrix identification of complex-shape robotic links. It proposes an enhancement that simplifies the identification procedure by splitting the link into simple segments for which the identification procedure is trivial. Further, the segments’ stiffness matrices are aggregated into the desired link stiffness matrix. The proposed enhancement allows users to avoid ambiguity with reference points for link connections with multiple surfaces. The developed technique is applied to real-world problem dealing with tool stiffness matrix identifications from the CAD-based virtual experiments.

The work focuses on the development of an adaptive technique for the physical interaction handling between a human and a robot, as well as its experimental validation. The proposed technique is based on the deep residual neural network and dedicated finite state machine, where the states are the robot behavior modes and transitions are the switchings between the states that depend on the interaction parameters and characteristics. It ensures the human operator safety and improves the human–robot collaboration performance by implementing various scenarios. In the scope of this technique, the parameters of human–robot interaction are used to select an appropriate robot reaction strategy using data from internal robot sensors only, i.e. proprioceptive sensors. These parameters define the interaction force vector and its application point on the robot surface, which allow to classify the interaction within the set of predefined categories. This classification distinguishes interactions applied at the tool or intermediate link (Tool/Link), having soft or hard nature (Soft/Hard), as well as having different intention (Intl/Accd) or duration (Short/Long). Based on identified category and the current robot state, the algorithm chooses an appropriate robot reaction. To confirm the efficiency the developed technique, an experimental study was conducted, which involved the collaboration between the real industrial manipulator KUKA LBR iiwa and the human operator.

International audience

The goal of this work is to propose a way of dealing with physical interactions for collaborative robots that will ensure the safety of a human operator and improve the performance of a common task by implementing multiple robot behavior scenarios. In this scope, all collisions of a robotic arm are detected and analyzed to chooses an appropriate reaction strategy. The points of contact on the robot’s surface for each collision are estimated, the external forces are identified and collisions are classified by the set of predefined categories. Based on these categories and the current robot state, the algorithm chose an appropriate behavior scenario.All presented algorithms are based only on proprioceptive sensors information and were tested in a simulated environment and on the real collaborative robots KUKA iiwa and Universal Robots UR10e. The result for contact localization showed 4 cm mean accuracy, the classification algorithm was able to identify collisions with hard and soft objects with 98% accuracy for KUKA iiwa 14.

International audience

International audience

The paper deals with comparison study of serial and quasi-serial industrial robots used for machining operations. It proposes a new methodology for robot ranking, which is based on estimation of the end-effector resistance to cutting forces for several machining tasks, which are optimally located within the robot workspace. To cover wide range of applications, a set of isotropic, quasi-isotropic and extended benchmark tasks are considered. It is shown that regardless of the benchmark problem, seral manipulators are preferable for small and medium tasks while quasi-serial ones' better suit large-dimensional tasks. The proposed technique was applied for the comparison analysis of 10 industrial robots of both serial and quasi-serial architectures with similar working radius and payload of about 200 kg.

The paper addresses a problem of robotic manipulator calibration. The main contributions are in the area of the elastostatic parameters identification. In contrast to other works, the considered approach takes into account elastic properties of both links and joint. Particular attention is paid to generation of the complete and irreducible stiffness model that is suitable for the identification. To solve the problem, physical and algebraic model reduction methods are proposed. They are based on taking into account the physical properties of the manipulator elements and structure of the corresponding observation matrix. The advantages of the developed approach are illustrated by an application example that deals with elastostatic calibration of an industrial robot.

The paper focuses on the stiffness modeling of heavy industrial robots with gravity compensators. The main attention is paid to the identification of geometrical and elastostatic parameters and calibration accuracy. To reduce impact of the measurement errors, the set of manipulator configurations for calibration experiments is optimized with respect to the proposed performance measure related to the end-effector position accuracy. Experimental results are presented that illustrate the advantages of the developed technique.

The paper focuses on the stiffness modeling of parallel manipulators composed of non-perfect serial chains, whose geometrical parameters differ from the nominal ones. In these manipulators, there usually exist essential internal forces/torques that considerably affect the stiffness properties and also change the end-effector location. These internal loadings are caused by elastic deformations of the manipulator elements during assembling, while the geometrical errors in the chains are compensated for by applying appropriate forces. For this type of manipulators, a non-linear stiffness modeling technique is proposed that allows us to take into account inaccuracy in the chains and to aggregate their stiffness models for the case of both small and large deflections. Advantages of the developed technique and its ability to compute and compensate for the compliance errors caused by different factors are illustrated by an example that deals with parallel manipulators of the Orthoglide family.

This paper focuses on stiffness matrix computation for manipulators with passive joints, compliant actuators, and flexible links. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in the general case and allow us to obtain the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and nonsingular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.

The paper focuses on stiffness matrix computation for manipulators with passive joints. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in general case and allow obtaining the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and non-singular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.

In this paper, a new methodology for the optimal design of parallel kinematic machine tools is proposed. This approach is based on the concept of the maximal inscribed parallelepiped and uses technology-oriented constraints that are motivated by particular applications. This methodology is applied on two translational parallel robots with three degrees-of-freedom (DOF): the Y-STAR and the UraneSX. An analysis of the size of their workspace as a function of the design constraints is made. It is shown that, for identical workspaces with similar properties, the size of the legs of the UraneSX are greater than for the Y-STAR, thus leading to larger deformations. However, the footprint surface needed in order to install the Y-STAR is about two times bigger than for the UraneSX. Therefore, it may be interested to use the UraneSX in order to save some place on ground in manufacturing centres.

The paper presents a new stiffness modelling method for overconstrained parallel manipulators, which is applied to 3-d.o.f. translational mechanisms. It is based on a multidimensional lumped-parameter model that replaces the link flexibility by localized 6-d.o.f. virtual springs. In contrast to other works, the method includes a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations, which allows computing the stiffness matrix for the overconstrained architectures and for the singular manipulator postures. The advantages of the developed technique are confirmed by application examples, which deal with comparative stiffness analysis of two translational parallel manipulators.

The Orthoglide is a Delta-type PKM dedicated to 3-axis rapid machining applications that was originally developed at IRCCyN in 2000-2001 to meet the advantages of both serial 3-axis machines (regular workspace and homogeneous performances) and parallel kinematic architectures (good dynamic performances and stiffness). This machine has three fixed parallel linear joints that are mounted orthogonally. The geometric parameters of the Orthoglide were defined as function of the size of a prescribed cubic Cartesian workspace that is free of singularities and internal collision. The interesting features of the Orthoglide are a regular Cartesian workspace shape, uniform performances in all directions and good compactness. In this paper, a new method is proposed to analyze the stiffness of overconstrained Delta-type manipulators, such as the Orthoglide. The Orthoglide is then benchmarked according to geometric, kinematic and stiffness criteria: workspace to footprint ratio, velocity and force transmission factors, sensitivity to geometric errors, torsional stiffness and translational stiffness.

ShareCam is a robotic pan, tilt, and zoom Web-based camera controlled by simultaneous frame requests from online users. Part I describes the system. This paper, part II, focuses on algorithms. The ShareCam problem is to find a camera frame that optimizes a measure of total user satisfaction. We present a grid-based approximation algorithm: given camera frame requests from n users, and approximation bound /spl epsi/, we analyze the trade of between solution quality and processing speed and prove that the algorithm runs in O(n//spl epsi//sup 3/) time. The algorithm can be distributed to run in O(1//spl epsi//sup 3/) time at each client and in O(n + 1//spl epsi//sup 3/) time at the server. Experiments suggest that performance of the distributed algorithm degrades gracefully as clients fail to complete their part of the computation.

The paper focuses on the enhancement of automatic robot programming techniques for laser cutting application. Its particular contribution lies in the area of multiobjective optimisation of robot motions via graph representation of the search space and dynamic programming procedures. It have been developed algorithms that allow to generate smooth manipulator trajectories within acceptable time, simultaneously considering kinematic, collision and singularities constraints of the robotic system, as well as the limitations of the robot control units. The presented results are implemented in a commercial software package and verified for real-life applications in automotive industry.