Dedicated Dynamic Parameter Identification for Delta-Like Robots

Radiotherapy (RT) enables a selective destruction of tumor cells, although the treatment area is limited to the irradiated volume. Any RT technique comes along with multiple sources of error, which can lead to a deviation of the dose that is applied to the patient. Phantoms—structures that replicate a human and include measurement technology to assess the applied dosage—are used to make such errors observable. Past RT-technologies assumed static tumors. Correspondingly, most existing phantoms comprise only static components. Nowadays, RT is at a transition stage toward techniques which explicitly account for physiological motion. These techniques require phantoms generating such motion. Consequentially, a demand for new kinds of manipulators, which operate with a RT-phantom, has come up and will further increase in the future. Key demands of such manipulators are among others, the generation of full rigid body motion, high acceleration, high stiffness, compactness, little weight, and easy portability. Another indispensable feature is the spatial separation of mechatronic components and phantom structure to ensure human equivalency of the latter. In this work, a new kind of parallel kinematic manipulator (PKM), which is tailored to the requirements of RT-phantom technology, is presented. The PKM consists of low cost standardized mechanical components and sets the target structures, which are located inside a human-equivalent area, into translational and rotational motion in three degrees-of-freedom (DOFs). Only a part of the end-effector is located within the human-equivalent area. All the remaining parts of the PKM are located outside that area. Two versions of the manipulator are presented in detail: their kinematics are derived and their kinetostatic properties are compared. This includes a workspace analysis and the analysis of the transmission behavior in general, meaning the influence of the most important design parameters on the performance. It can be shown that practical differences of both kinematics are negligible, while the modified version provides significant mechanical advantages. In conclusion, a first special purpose manipulator for application in the evolving field of RT-phantom technology is presented. The PKM, which employs a novel kinematic structure, provides higher suitability for its purpose than any other robotic system employed so far for the same purpose.

Offline robot dynamic identification methods are based on the use of the inverse dynamic identification model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal (the input reference of the motor current loop) with the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of the linear least squares technique to calculate the parameters (IDIM-LS technique). However, as actuation-redundant parallel robots are overactuated, their IDIM has an infinity of solution for the force/torque prediction, depending on the value of the desired overconstraint that is a priori unknown in the identification process. As a result, the IDIM cannot be used as it is for such a class of parallel robots. This paper proposes a procedure for the dynamic parameter identification of actuation-redundant parallel robots. The procedure takes advantage of two possible modified formulations for the IDIM of actuation-redundant robots that can be used for identification purpose. The modified IDIM formulations project some or all input torques/forces onto the robot bodies, thus leading to a unique solution of the model that can then be used in the identification process. A systematic and straightforward way to compute these modified IDIM is presented. The identification of the inertial parameters of a planar parallel robot with actuation redundancy, the DualV, is then carried out using these modified IDIM. Experimental results show the validity of the methods.

Identification of dynamic parameters of a 3-DOF RPS parallel manipulator

Aiming at the shortcomings of the current dynamic parameter identification methods in fitting nonlinear friction characteristics, the satisfaction of physically-consistent constraints, and the efficiency of dynamic calculation of the minimum inertial set, a physical consistent dynamic full parameter identification method based on the nonlinear friction model is proposed. Firstly, according to the characteristics of each component of the robot's dynamic equation, the joint trajectory that can cancel the non-friction moment term during the forward and reverse rotation of the joint is designed, and the friction moment is separated from the measured moment; Secondly, the nonlinear friction model is used to model the friction torque, and the friction parameters are obtained by solving the nonlinear least square problem; Finally, the regularized weighted least squares problem with physically-consistent constraints is solved by convex optimization method, and the full parameter set of robot dynamics including friction parameters and inertia parameters is obtained. The experimental results show that the RMS error of the proposed dynamic parameter identification method is the smallest compared with the CAD numerical calculation method and the penalty optimization identification method.

This article is concerned with the identification of industrial robot dynamics parameters, and an identification method based on a nonlinear friction model and a least squares (LS) with symbiotic organisms search (SOS) algorithm is proposed. First, according to the friction characteristics of robot joints, for the nonlinear Tustin friction model, two parameters are introduced to describe the Stribeck characteristics of Coulomb friction and static friction. Then, the joint velocity trajectory that can offset the nonfriction torque during the forward and reverse rotation is designed, and friction parameters are estimated by using LS. Based on the optimal criterion constructed by Hadamard’s inequality, the excitation trajectory represented by the Fourier series is designed, and the combined inertial parameter set is estimated by using LS. Second, select the minimum inertial parameters and friction parameters (minimum dynamic parameters) as the center points to search the upper and lower bounds; design the fitness function with adjustable weights of each joint and use the SOS algorithm to estimate the minimum dynamic parameter set as a whole. Finally, a variety of parameter identification algorithms are applied to the Staubli TX-90 robot under the same excitation trajectory. The experiment results show that the root-mean-square (rms) error of the joint torque estimated by the proposed method is the smallest. By executing the verification trajectory, the experiment results show that the rms error of the joint torque is small and the correlation coefficient is close to 1, thereby verifying the effectiveness of the estimated model for different motion trajectories.

We present a new parameterization of quintessence potentials for dark energy based directly upon the dynamical properties of the equations of motion. Such parameterization arises naturally once the equations of motion are written as a dynamical system in terms of properly defined polar variables. We have identified two different classes of parameters, and we dubbed them as dynamical and passive parameters. The dynamical parameters appear explicitly in the equations of motion, but the passive parameters play just a secondary role in their solutions. The new approach is applied to the so-called thawing potentials and it is argued that only three dynamical parameters are sufficient to capture the evolution of the quintessence fields at late times. This work reconfirms the arbitrariness of the quintessence potentials as the recent observational data fail to constrain the dynamical parameters.

The dynamic and friction parameters of a redundantly actuated parallel manipulator are identified by using the weighted least square (WLS) method. The dynamic model with nonlinear friction is formulated in the joint space for the parallel manipulator, and it is expressed in its linear matrix form with respect to the dynamic and friction parameters. In the WLS method, the difference algorithm of joint angles, filter of actuated torques, and the well-excited trajectory of the end-effector are designed to get satisfying estimated results. Another type of the end-effector trajectory is adopted to verify the estimated parameters. In order to compare the identified model with the nominal model, the torques of the active joints is calculated by the estimated parameters and the nominal parameters, respectively.

This paper presents optimizations of a parallel kinematic manipulator used for a machine tool in terms of its workspace and stiffness. The system stiffness and workspace of the parallel manipulator are conducted in the paper. In order to locate the maximum system stiffness and workspace, single and multi-objective optimizations are performed in terms of rotation angles in x and y axes and translation displacement in z axis with genetic algorithms. By optimizing the design variables including geometric dimensions of the manipulator, the system stiffness and workspace of the proposed parallel kinematic manipulator has been greatly improved.

This article examines Genetic Algorithms to solve the forward kinematics problem applied to planar parallel manipulators. Most of these manipulators can be modeled by the tripod 3-RPR. The conversion of an equation system solving problem into an optimization one is investigated. Parallel manipulator kinematics are formulated using the explicit Inverse Kinematics Model (IKM). From the displacement based equation systems, the objective function is formulated specifically for the FKP using one squared error performance criteria. The proposed approach implements an elitist selection process where a new mutation operator for Real-Coded GA is analyzed. Experiments on a typical manipulator example shows the fast convergence of the proposed method.

Reconfiguration of a parallel kinematic manipulator with 2T2R motions for avoiding singularities through minimizing actuator forces

A common issue of the parallel robot is that has a large number of dynamic parameters, which requires a lot of processing time, whether in dynamic modeling, identification or control. The optimization and estimation of inertial parameters of a large DoF number of robotic system is crucial to tune the model-based control law in order to improve the robot accuracy. In this paper, we present an optimized number of dynamic parameters, called base inertial parameters. As a result, only 90 base inertial parameters affect the evr@ simulator instead of 210 standard one. Torque signals evaluation from experimental parallel platform and the developed analytical form show the effectiveness of the obtained results.

The hexapod is a parallel kinematic manipulator that is the minimum arrangement for independent control of six degrees of freedom. Advancing needs for hexapod performance, capacity and configurations have driven development of highly capable new actuator designs. This paper describes new compact hexapod design proposals for high load capacity, and corresponding hexapod actuator only mechanisms suitable for integration as structural motion elements in next-generation telescope designs. These actuators provide up to 90 000N load capability while preserving sub-micrometer positional capability and in-position stability. The design is optimized for low power dissipation and incorporates novel encoders direct manufactured with the nut flange to achieve more than 100000 increments per revolution. In the hexapod design we choose cardan joints for the actuator that have axis offsets to provide optimized stiffness. The additional computational requirements for offset axes are readily solved by advanced kinematic algorithms and modern hardware. The paper also describes the hexapod controller concept with individual actuator designs, which allows the integration of hexapod actuators into the main telescope structure to reduce mass and provide the telescope designer more design freedom in the incorporation of these types of motion systems. An adaptive software package was developed including collision control feature for real-time safety during hexapod movements.

This paper presents the design and analysis of a novel five degrees-of- freedom (DOF) parallel kinematic manipulator (PKM) for part-handling, sorting, general positioning, and robotic machining applications. The 2- R(Pa-IQ)RR, R(Pa-IQ)R manipulator has two rotational DOFs, one parasitic rotation, and three translational DOFs. In comparison with other 5- and 6- DOF PKMs, this PKM possesses three pairs of coplanar legs that contain nested kinematic chains, and it makes exclusive use of revolute and prismatic joints. The inverse kinematic analysis is a novel extension of the geometric (vector) method with the analysis of inner and outer kinematic chains. The forward kinematic analysis was solved using the Newton Raphson (NR) method. The results of the forward and inverse kinematic analyses were validated with SolidWorks ® and MATLAB ® simulations.

This paper presents a new hybrid method, which integrates the structured laser light, decoupled dynamic models, and evolutionary optimization strategy, to identify dynamic parameters of autonomous underwater vehicles. This is the first research that investigates the utilization of laser scanned images for the system identification of underwater vehicles. The AUV’s equations of motions and the dynamic parameter identification using the AUV’s decoupled motions will be illustrated. The working principles to calculate the AUV’s positons using the structured laser light will be explained with respect to the surge and pitch motions. The evolutionary optimization strategy used to generate the AUV’s dynamic parameters will be presented.

Off-line robot dynamic identification methods are generally based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal - the input reference of the motor current loop - by the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). However, as actuation redundant parallel robot are overconstrained, their IDIM has infinity of solutions for the force/torque prediction, depending of the value of the desired overconstraint that is a priori unknown in the identification process. As a result, the IDIM cannot be used for the identification procedure. On the contrary the Power Identification Model (PIM) of any types of robot manipulator has a unique formulation and contains the same dynamic parameters as the IDIM. This paper proposes to use the PIM of actuation redundant robots for identification purpose. The identification of the inertial parameters of a planar parallel robot with actuation redundancy, the DualV, is then carried out using its PIM. Experimental results show the validity of the method.