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This paper aims to address the issue of model discontinuity typically encountered in traditional Denavit-Hartenberg (DH) models. To achieve this, we propose the use of a local Product of Exponentials (POE) approach. Additionally, a modified calibration model is presented which takes into account both kinematic errors and high-order joint-dependent kinematic errors. Both kinematic errors and high-order joint-dependent kinematic errors are analyzed to modify the model.

Robot positioning accuracy is critically important in high-speed and heavy-load manufacturing applications. One essential problem encountered in calibration of series robot is that the traditional methods only consider fitting kinematic errors, while ignoring joint-dependent kinematic errors.

Laguerre polynomials are chosen to fitting kinematic errors and high-order joint-dependent kinematic errors which can avoid the Runge phenomenon of curve fitting to a great extent. Levenberg–Marquard algorithm, which is insensitive to overparameterization and can effectively deal with redundant parameters, is used to quickly calibrate the modified model. Experiments on an EFFORT ER50 robot are implemented to validate the efficiency of the proposed method; compared with the Chebyshev polynomial calibration methods, the positioning accuracy is improved from 0.2301 to 0.2224 mm.

The results demonstrate the substantial improvement in the absolute positioning accuracy achieved by the proposed calibration methods on an industrial serial robot.

The purpose of this paper is to propose a screw axis identification (SAI) method based on the product of exponentials (POE) model, which is concerned with calibrating a serial robot with m joints equipped with a stereo‐camera vision system.

Different from conventional approaches, like the circle point analysis (CPA) or the system theoretic method which must collect a great deal of data, the identification of the joint parameters for the proposed method only needs to measure m+1 times for n (n≥3) target points mounted on the manipulator end‐effector.

In this approach, the joint parameter, called a screw or twist, together with the actual value of joint angle can be obtained by linearly solving a closed‐form expression. Further, this method avoids calibrating the hand‐eye relationship and the exterior parameter of the robot.

Finally, the stability and accuracy of the SAI method are evaluated by simulation experiments, and it is also verified well in practical experiments.

This paper aims to propose a calibration model for kinematic parameters identification of serial robot to improve its positioning accuracy, which only requires position measurement of the end-effector.

The proposed model is established based on local frame representation of the product of exponentials (local POE) formula, which integrates all kinematic errors into the twist coordinates errors; then they are identified with the tool frame’ position deviations simultaneously by an iterative least squares algorithm.

To verify the effectiveness of the proposed method, extensive simulations and calibration experiments have been conducted on a 4DOF SCARA robot and a 5DOF drilling machine, respectively. The results indicate that the proposed model outperforms the existing model in convergence, accuracy, robustness and efficiency; fewer measurements are needed to gain an acceptable identification result.

This calibration method has been applied to a variable-radius circumferential drilling machine. The machine’s positioning accuracy can be significantly improved from 11.153 initially to 0.301 mm, which is well in the tolerance (±0.5 mm) for fastener hole drilling in aircraft assembly.

An accurate and efficient kinematic calibration model has been proposed, which satisfies the completeness, continuity and minimality requirements. Due to generality, this model can be widely used for serial robot kinematic calibration with any combination of revolute and prismatic joints.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

Calibrating kinematic parameters is one of the efficient ways to improve the robot's positioning accuracy. A method based on the product-of-exponential (POE) formula to calibrate the kinematic parameters of serial industrial robots is proposed. The paper aims to discuss these issues.

The forward kinematics is established, and the general positioning error model is deduced in an explicit expression. A simplified model of robot's positioning error is established as both the error of reference configuration and the error of rigid displacement of the base coordinating system with respect to the measuring coordinating system are equivalently transferred to the zero position errors of the robot's joints. A practical calibration model is forwarded only requiring 3D measuring based on least-squares algorithm. The calibration system and strategy for calibrating kinematic parameters are designed.

By the two geometrical constrains between the twist coordinates, each joint twist only has four independent coordinates. Due to the equivalent error model, the zero position error of each joint can cover the error of reference configuration and rigid displacement of the robot base coordinating system with respect to the measuring coordinating system. The appropriate number of independent kinematic parameters of each joint to be calibrated is five.

It is proved by a group of calibration experiments that the calibration method is well conditioned and can be used to promote the level of absolute error of end effector of industrial robot to 2.2 mm.

This paper aims to propose a novel robot kinematic calibration method based on the common perpendicular line (CPL) model to improve the absolute accuracy of industrial robots.

The deviation between the nominal and actual twists is considered the CPL transformation, which includes the rotation about the CPL and the translation along the CPL. By using the invariance of the reciprocal product of the two spatial lines, the previous deviation was analyzed in the neighbor space of the base frame origin. In this space, the line vector of the CPL contained only four independent parameters: two orientation elements and two moment elements. Thus, the CPL model has four independent parameters for the revolute joint and two parameters for the prismatic joint.

By simulations and experiment conducted on a SCARA robot and a 6-DOF PUMA robot, the effectiveness of the novel method for calibration of industrial robot is validated.

The CPL model avoided the normalization and orthogonalization in the iterative identification procedure. Therefore, identifying the CPL model was not only simpler but also more accurate than that of the traditional model. In addition, the results of the CPL transformation strictly conformed to the constraints of the twist.

Developing general closed-form solutions for six-degrees-of-freedom (DOF) serial robots is a significant challenge. This paper thus aims to present a general solution for six-DOF robots based on the product of exponentials model, which adapts to a class of robots satisfying the Pieper criterion with two parallel or intersecting axes among its first three axes.

The proposed solution can be represented as uniform expressions by using geometrical properties and a modified Paden–Kahan sub-problem, which mainly adopts the screw theory.

A simulation and experiments validated the correctness and effectiveness of the proposed method (general resolution for six-DOF robots based on the product of exponentials model).

The Rodrigues rotation formula is additionally used to turn the complex problem into a solvable trigonometric function and uniformly express six solutions using two formulas.

Effective use of post-occupancy evaluation (POE) data – quantitative physical measurements and qualitative occupants’ perceptions are limited due to practical challenges and research gaps. Although building information modelling (BIM) has enabled a paradigm shift in the architecture, engineering and construction (AEC) industries, its use in facility management (FM) is still infancy. Limited research has used building performance data to enable changes to BIM models for the benefit of FM. This paper aims to propose the innovative process to collect and contextualize two fragmented types of POE data sets by filling methodological gap in POE research. Moreover, it presents innovative modelling techniques to facilitate BIM as a more effective platform to visualize such currently fragmented data sets in real-time while enabling a decision-making model to benefit facility managers.

The paper presents a process of capturing cloud-based POE data, both wireless sensor network-based physical measurement data and mobile app-based occupant perception data. Real-time capture and visualization of such building performance data was demonstrated through a pilot data collection. Subsequently, the innovative visualization of the cloud connected data is supported by a prototype game engine-based BIM model.

Cloud-based POE data, both quantitative physical measurements and qualitative occupants’ reported perceptions, can be effectively used in FM practice with the use of innovative data capture and visualization techniques in a beneficial manner for facility operation and management decisions. This paper also demonstrates the ability of BIM to serve as a “single source of truth” to support post-construction building performance data.

While addressing a number of research gaps, the paper provides a holistic approach to BIM-based performance monitoring for smart FM to achieve the ultimate vision of BIM enabled FM. The innovative system is expected to provide a powerful and practical tool for data collection, analysis and visualization for intelligent facility management decision making. This paper contributes to fill an important research and practice gap in the area of next generation smart building management practices.

The purpose of this paper is to propose an error model for serial robot kinematic calibration based on dual quaternions.

The dual quaternions are the combination of dual-number theory and quaternion algebra, which means that they can represent spatial transformation. The dual quaternions can represent the screw displacement in a compact and efficient way, so that they are used for the kinematic analysis of serial robot. The error model proposed in this paper is derived from the forward kinematic equations via using dual quaternion algebra. The full pose measurements are considered to apply the error model to the serial robot by using Leica Geosystems Absolute Tracker (AT960) and tracker machine control (T-MAC) probe.

Two kinematic-parameter identification algorithms are derived from the proposed error model based on dual quaternions, and they can be used for serial robot calibration. The error model uses Denavit–Hartenberg (DH) notation in the kinematic analysis, so that it gives the intuitive geometrical meaning of the kinematic parameters. The absolute tracker system can measure the position and orientation of the end-effector (EE) simultaneously via using T-MAC.

The error model formulated by dual quaternion algebra contains all the basic geometrical parameters of serial robot during the kinematic calibration process. The vector of dual quaternion error can be used as an indicator to represent the trend of error change of robot’s EE between the nominal value and the actual value. The accuracy of the EE is improved after nearly 20 measurements in the experiment conduct on robot SDA5F. The simulation and experiment verify the effectiveness of the error model and the calibration algorithms.

This paper aims to propose an optimization method to automatically adjust the spatial route of multibend pipes to meet the assembly demands in constrained space.

The compact geometric parameters that uniquely determine the pipe route are analyzed. Besides, the relationship between these parameters and the end pose is revealed based on the exponential product formula. Mathematical representations for the engineering constraints, including the end pose restriction, collision interference, manufacture ability and geometric limitations, are further established. On this basis, the adjustment of the spatial route is formulated as a multiconstraint optimization problem. A modified particle swarm optimization method based on the combination of gradient projection and swarm intelligence is designed to find the near-optimal pipe that meets the required assembly demands.

The experimental results show that the proposed method can effectively find the feasible pipe route that satisfies the engineering constraints and the end pose requirement is highly guaranteed.

The proposed method can automate the geometric adjustment of multi-bend pipes to meet the actual assembly demands, which significantly reduces manual efforts and guarantees high accuracy. The results demonstrate the possibility of further applications in the pipe assembly or design process, especially in ships, aerospace products or pressure vessels.