Self-calibration has the potential of: 1) removing the dependence on any external pose sensing information; 2) producing high accuracy measurement data over the entire workspace of the system with an extremely fast measurement rate; 3) being automated and completely noninvasive; 4) facilitating on-line accuracy compensation; and 5) being cost effective. A general framework is introduced in this paper for the self-calibration of parallel manipulators. The concept of creating forward and inverse measurement residuals by exploring conflicting information provided with redundant sensing is proposed. Some of these ideas have been widely used for robot calibration when robot end-effector poses are available. By this treatment, many existing kinematic parameter estimation techniques can be applied for the self-calibration of parallel mechanisms. It is illustrated through a case study, i.e. calibration of the Stewart platform, that with this framework the design of a suitable self-calibration system and the formulation of the relevant mathematical model become more systematic. A few principles important to the system self-calibration are also demonstrated through the case study. It is shown that by installing a number of redundant sensors on the Stewart platform, the system is able to perform self-calibration. The approach provides a tool for rapid and autonomous calibration of the parallel mechanism.

Self-calibration of parallel mechanisms with a case study on Stewart platforms

Presents a method for the autonomous calibration of six degrees-of-freedom parallel robots. The calibration makes use of the motorized prismatic joint positions corresponding to some sets of configurations where in each set either a passive universal joint or a passive spherical joint is fixed using a lock mechanism. Simulations give us an idea about the number of sets that must be used, the number of configurations by set and the effect of noise on the calibration accuracy. The main advantage of this method is that it can be executed rapidly without need to external sensors to measure the position or the orientation of the mobile platform.

Self calibration of Stewart-Gough parallel robots without extra sensors

https://hal-mines-nantes.archives-ouvertes.fr/hal-01201696/document

Identification of the manipulator stiffness model parameters in industrial environment

Presents a numerical method for the determination of the identifiable parameters of parallel robots. The special case of Stewart-Gough 6 degrees-of-freedom parallel robots is studied for classical and self calibration methods, but this method can be generalized to any kind of parallel robot. The method is based on QR decomposition of the observation matrix of the calibration system. Numerical relations between the parameters which are identified and those which are not identifiable can be obtained for each method.

/pdf/identifiable-parameters-for-parallel-robots-kinematic-4w1kfjz5tx.pdf

Identifiable parameters for parallel robots kinematic calibration

Parallel configurations are recently being applied to the machine tool with the hopes of greater rigidity, stability, and accuracy than conventional multi-axis structures allow. However, the many calibration methods presently available for serial machine tools are not applicable to hexapod type structures. A calibration method is presented that uses a ball–bar or other simple length measuring device to act as an ‘extra leg,’ allowing calibration of the hexapod's true kinematic parameters. This method utilizes a total least squares minimization, does not require any special hexapod configuration or difficult six degree of freedom pose measurements, and is effective with as few as one additional length sensor. Selection of calibration pose sets is briefly discussed, as well as the influence of measurement noise on calibration accuracy. Simulations show the potential for this algorithm to significantly reduce errors to the point where machining errors are within 5–10 times the measurement errors.

Calibration of a hexapod machine tool using a redundant leg

A general numerical method is introduced in this paper for the self-calibration of parallel manipulators. The concept of creating inverse measurement residuals by exploring conflicting information provided with redundant sensing is generalized. A numerical kinematic analysis method is adopted to systematically compute the inverse measurement residuals. By this treatment, the design of a suitable self-calibration system became more systematic, and existing kinematic parameter estimation techniques can be applied for the self-calibration of parallel mechanisms. It is shown that by installing 2 or more redundant sensors on the Stewart platform, the system is able to perform self-calibration. It is possible to calibrate part of the system using a reduced number of redundant sensors; the identification algorithm converges rapidly; its accuracy performance is satisfactory; and the extension of the method to other parallel manipulators is straightforward.

Self-calibration of a class of parallel manipulators

Hexapod machines are emerging as a new type of CNC machine tools, Among other things, stringent calibration is an important means to improve their accuracy, Traditionally, to perform system calibration, one needs to measure a number of machine poses using an external measuring device. However, this process is often labor-intensive and invasive, and difficult for on-line calibration. In this paper, a systematic way of self-calibrating a hexapod machine tool is introduced. By adding a small number of redundant internal sensors, errors of the hexapod machine tool can be measured. This approach has the potential of automatically producing high accuracy measurement data over the entire workspace of the system with an extremely fast measurement rate. Once the measurement data is available, a recursive filter is applied to estimate machine parameter errors from the predicted geometric errors, and to update the model residing in the machine controller. Thus, it is possible to dynamically calibrate and compensate for various types of machine errors including those induced by thermal and loading variations, without interrupting the normal operation of the machine tool. To verify the concept, preliminary experimental studies were conducted on a Stewart platform built at Florida Atlantic University.

Lixin Liu

Papers

Self-calibration of a class of parallel manipulators

Autonomous Calibration of Hexapod Machine Tools