Serial Robot Research Articles

Influence of dynamic complexity on serial robots with joint clearance based on a nonlinearity measure

Conditional monitoring and diagnosis of serial robots depend not only on the method used but also on the dynamic complexity of the robotic system itself. Previously, researchers have focused mainly on the analysis of dynamic behaviors with different parameters of a mechanical system with clearance. Although the indicators such as Root Mean Square (RMS), spectrum kurtosis (SK), Entropy have the potentiality to express the specific trend by different parameters, it can be noticed that they mainly depend on the values of the dynamic responses and neglect the information of the nonlinear characteristics in the responses of mechanical systems. In this paper, a nonlinearity measure-based method is proposed to analyze the impact of dynamic complexity on serial robots with joint clearance. The kinetic equations of a serial robot with joint clearance are established by considering the contact forces in the joint. The dynamic model of the robotic system is validated by experiments. A quantization method for dynamic complexity analysis is established based on the nonlinearity measure, and the influences of parameters on the dynamic complexity are analyzed via numerical computations for the validated dynamical models of the robotic system. A relationship is developed among the clearance radius, friction coefficient, and dynamic complexity. This shows that a larger clearance radius will lead to a more complex system and that friction coefficients within a certain range can reduce the dynamic complexity of the system. These results can guide methodological choices for condition monitoring and diagnosis of serial robotic systems.

Parallel–Serial Robotic Manipulators: A Review of Architectures, Applications, and Methods of Design and Analysis

Parallel–serial (hybrid) manipulators represent robotic systems composed of kinematic chains with parallel and serial structures. These manipulators combine the benefits of both parallel and serial mechanisms, such as increased stiffness, high positioning accuracy, and a large workspace. This study discusses the existing architectures and applications of parallel–serial robots and the methods of their design and analysis. The paper reviews around 500 articles and presents over 150 architectures of manipulators used in machining, medicine, and pick-and-place tasks, humanoids and legged systems, haptic devices, simulators, and other applications, covering both lower mobility and kinematically redundant robots. After that, the paper considers how researchers have developed and analyzed these manipulators. In particular, it examines methods of type synthesis, mobility, kinematic, and dynamic analysis, workspace and singularity determination, performance evaluation, optimal design, control, and calibration. The review concludes with a discussion of current trends in the field of parallel–serial manipulators and potential directions for future studies.

Inertial analyses based on the generalized inertia matrix for parallel robots

Analyzing the inertial properties is meaningful for parallel robots, especially those interacting with the environment. This paper provides tools for the analysis of the inertial properties of parallel robots based on the generalized inertia matrix (GIM). Since most interactions between the environment and robots happen through the mobile platform, the inertia of the whole robot reflected at the platform is considered. In this framework, the GIM is expressed in Cartesian space to yield inertial characteristics with a clear physical meaning. Then, the inertia of the whole robot is thereby reduced to an equivalent mass/inertia at the platform. Unlike for serial robots, obtaining the GIM of parallel robots in Cartesian space is complex due to the inherent closed-loop structures and the possibility of including two different types of redundancy. Two methods are proposed to solve the mentioned problems, which can simplify the derivations of the required GIMs for parallel robots. Detailed analysis and usages of the proposed methods are given based on different examples, and the results demonstrate the effectiveness of the proposed approaches.

Research on the influence of cutter overhang length on robotic milling chatter stability

Serial industrial robots are widely in demand in the field of large-scale component processing and manufacturing. However, the structure characteristic of serial robots makes it easy to generate chatter during milling and the overhang length of milling cutter has an important influence on the stability of robotic milling. Milling cutter overhang length refers to the length from the tip of the cutter to the protrusion of the spindle, to study the influence of milling cutter overhang length on the stability behavior of robotic milling, the modal parameters of milling cutter under different overhang length were obtained by hammer experiment, and its dynamic characteristics were analyzed. The stability behavior for robotic milling under different cutter overhang lengths was analyzed by using the stability lobe diagrams, and the stability lobe diagrams were verified by robotic milling experiments. The results show that the rigidity and natural frequency of milling cutter decrease with the increase of overhang length. There is a big gap between the stability lobe diagrams and the actual machining state when the cutter overhang length is short, and the low frequency vibration is easy to occur in the robotic milling process when the spindle speed is low, which is most probably because that the absorbed vibration energy by the cutter has been transferred to the robot body before the milling cutter vibrates. When the cutter overhang is increased and the feed direction is along the y-axis of the robot global coordinate system, the stability lobe diagrams by considering the multi-mode coupling effect is more consistent with the actual milling state.

Lie-theory-based dynamic model identification of serial robots considering nonlinear friction and optimal excitation trajectory

Abstract Accurate dynamic model is essential for the model-based control of robotic systems. However, on the one hand, the nonlinearity of the friction is seldom treated in robot dynamics. On the other hand, few of the previous studies reasonably balance the calculation time-consuming and the quality for the excitation trajectory optimization. To address these challenges, this article gives a Lie-theory-based dynamic modeling scheme of multi-degree-of-freedom (DoF) serial robots involving nonlinear friction and excitation trajectory optimization. First, we introduce two coefficients to describe the Stribeck characteristics of Coulomb and static friction and consider the dependency of friction on load torque, so as to propose an improved Stribeck friction model. Whereafter, the improved friction model is simplified in a no-load scenario, a novel nonlinear dynamic model is linearized to capture the features of viscous friction across the entire velocity range. Additionally, a new optimization algorithm of excitation trajectories is presented considering the benefits of three different optimization criteria to design the optimal excitation trajectory. On the basis of the above, we retrieve a feasible dynamic parameter set of serial robots through the hybrid least square algorithm. Finally, our research is supported by simulation and experimental analyses of different combinations on the seven-DoF Franka Emika robot. The results show that the proposed friction has better accuracy performance, and the modified optimization algorithm can reduce the overall time required for the optimization process while maintaining the quality of the identification results.

Motion Planning for Minimally Actuated Serial Robots

Motion Planning for Minimally Actuated Serial Robots

Error analysis of a coaxis five-bar parallel mechanism

Abstract With societal advancement, robots are increasingly being deployed in production processes. Currently, high-precision robots predominantly found in the market are delta parallel robots. Common parallel robots, including delta robots, generally suffer from the drawback of having a smaller workspace compared to serial robots. Contrasted with other types of parallel robots, coaxis parallel robots feature a larger workspace, thereby offering greater potential for application. This paper focuses on a coaxis five-bar parallel mechanism as the subject of investigation. Firstly, by employing the perturbation method to model the errors in the parallel mechanism, a mapping relationship between error sources and the errors of the mechanism’s end-effector was derived. Then a sensitivity analysis of each error source was performed statistically, yielding sensitivity metrics. Last, under conditions where the magnitudes of errors are identical, the end-effector error of a coaxis parallel mechanism is notably larger compared to that of a common parallel mechanism. This makes it more essential to conduct precision design on coaxis parallel robots in the future study.

A New Method for Displacement Modelling of Serial Robots Using Finite Screw

Kinematics is a hot topic in robotic research, serving as a foundational step in the synthesis and analysis of robots. Forward kinematics and inverse kinematics are the prerequisite and foundation for motion control, trajectory planning, dynamic simulation, and precision guarantee of robotic manipulators. Both of them depend on the displacement models. Compared with the previous work, finite screw is proven to be the simplest and nonredundant mathematical tool for displacement description. Thus, it is used for displacement modelling of serial robots in this paper. Firstly, a finite-screw-based method for formulating displacement model is proposed, which is applicable for any serial robot. Secondly, the procedures for forward and inverse kinematics by solving the formulated displacement equation are discussed. Then, two typical serial robots with three translations and two rotations are taken as examples to illustrate the proposed method. Finally, through Matlab simulation, the obtained analytical expressions of kinematics are verified. The main contribution of the proposed method is that finite-screw-based displacement model is highly related with instantaneous-screw-based kinematic and dynamic models, providing an integrated modelling and analysis methodology for robotic mechanisms.

Design, Experiments, and Path Planning for a Lightweight 3D Minimally Actuated Serial Robot with a Mobile Actuator

This paper presents a novel three-dimensional (3D) minimally actuated serial robot (MASR) and its unique kinematic analysis. Unlike traditional robots, the 3D MASR features a passive arm devoid of wires or motors, comprising passive rotational and prismatic joints. A single mobile actuator (MA) traverses the arm, engages designated joints for operation, and locks them in place with a worm gear setup. A gripper is attached to the MA, enabling object transportation along the arm, reducing joint actuation, and optimizing task completion time. Our key contributions include the mechanical design, and in particular the robot’s passive joints with their automated actuation mechanism, and a novel optimization algorithm leveraging neural networks (NNs) to minimize task completion time through advanced kinematic analysis. Experiments with a physical prototype of the 3D MASR demonstrate its major advantages: it is remarkably lightweight (2.3 kg for a 1 m long arm and a 1 kg payload) compared to similar robots; it is highly modular (five joints R and P actuated by a single MA); and part replacement is effortless due to the absence of wiring along the arm. These features are visually depicted in the accompanying video.

An online error compensation strategy for hybrid robot based on grating feedback

Purpose This paper aims to enhance the machining accuracy of hybrid robots by treating the moving platform as the first joint of a serial robot for direct position measurement and integrating external grating sensors with motor encoders for real-time error compensation. Design/methodology/approach Initially, a spherical coordinate system is established using one linear and two circular grating sensors. This system enables direct acquisition of the moving platform’s position in the hybrid robot. Subsequently, during the coarse interpolation stage, the motor command for the next interpolation point is dynamically updated using error data from external grating sensors and motor encoders. Finally, fuzzy proportional integral derivative (PID) control is applied to maintain robot stability post-compensation. Findings Experiments were conducted on the TriMule-600 hybrid robot. The results indicate that the following errors of the five grating sensors are reduced by 94%, 93%, 80%, 75% and 88% respectively, after compensation. Using the fourth drive joint as an example, it was verified that fuzzy adaptive PID control performs better than traditional PID control. Practical implications The proposed online error compensation strategy significantly enhances the positional accuracy of the robot end, thereby improving the actual processing quality of the workpiece. Social implications This method presents a technique for achieving online error compensation in hybrid robots, which promotes the advancement of the manufacturing industry. Originality/value This paper proposes a cost-effective and practical method for online error compensation in hybrid robots using grating sensors, which contributes to the advancement of hybrid robot technology.

Soft Robots: Computational Design, Fabrication, and Position Control of a Novel 3-DOF Soft Robot

This paper presents the computational design, fabrication, and control of a novel 3-degrees-of-freedom (DOF) soft parallel robot. The design is inspired by a delta robot structure. It is engineered to overcome the limitations of traditional soft serial robot arms, which are typically low in structural stiffness and blocking force. Soft robotic systems are becoming increasingly popular due to their inherent compliance match to that of human body, making them an efficient solution for applications requiring direct contact with humans. The proposed soft robot consists of three soft closed-loop kinematic chains, each of which includes a soft actuator and a compliant four-bar arm. The complex nonlinear dynamics of the soft robot are numerically modeled, and the model is validated experimentally using a 6-DOF electromagnetic position sensor. This research contributes to the growing body of literature in the field of soft robotics, providing insights into the computational design, fabrication, and control of soft parallel robots for use in a variety of complex applications.

A closed-loop calibration method for serial robots based on position constraints and local area measurement

This paper presents a cost-effective and efficient closed-loop calibration method to enhance the absolute positioning accuracy of industrial robots. The method utilizes an economical and highly accurate set of simple measurement devices, including a device mounted on the robot's end effector and a spherical constraint device positioned within the robot's workspace. A novel local area measurement method is employed for the spherical constraint device, effectively converting position errors into the errors in the sphere center position of the constraint device. Furthermore, the error model considers both kinematic parameter deviations of the robot itself as well as those of the measurement device, along with non-kinematic errors caused by link self-weight. The closed-loop calibration model relies on position constraints, enabling identification and compensation of all error parameters using Levenberg Marquardt method after substituting measured data. The effectiveness of this proposed method is demonstrated through simulation and experimentation. In simulations, average position error reduces from 8.249 mm to 0.8384 mm, while absolute mean difference in sphere center positions obtained using our measurement equipment decreases from 1.206 mm to 0.1027 mm. Significant reductions in both position error and difference in sphere center position are indicated after calibration. This proves that the absolute mean value of the sphere center position difference can be used as the basis for judging the size of the robot's end position error. Experimental results show that absolute mean difference in sphere center position decreases from 0.4319 mm to 0.02869 mm, leading to substantial improvement in overall positioning accuracy.

QCASBC: An algorithm for hardware-in-the-loop simulation of 3-link RRR robotic manipulator

In this paper, a quick convergence adaptive structure is proposed for trajectory tracking of an articulated type robotic manipulator using the Hardware in the Loop (HIL) simulation technique. A novel Nonlinear Quick Convergence Adaptive Sliding Backstepping Control (QCASBC) algorithm is implemented on a C2000 real-time controller board. The performance of the proposed control algorithm is inspected concerning the sliding mode PID (SM-PID) control technique to estimate its correlation with the proposed algorithm. The experimental part of the HIL simulation tests has been carried out on a simulated model of a three-link serial robot manipulator. A dynamic model of the robotic manipulator has been developed using Matlab Simulink software and its performance is analyzed using the HIL technique via a C2000 real-time controller for tracking the desired trajectory. Results show that the speed of convergence while tracking the desired trajectory of the manipulator is better in the proposed algorithm. It is also estimated that the positional error of the QCASBC algorithm is superior to the SM-PID control algorithm. The observed average angle error is improved by 14% and the average response time error is improved by 11% by using the proposed QCASBC algorithm compared to the SM-PID approach.

Development and Optimization of a Noncircular Pulley for Motion Decoupling in Cable-Driven Serial Robots

Abstract Cable-driven serial robots have emerged with high potential for wide applications due to their compact size and low inertia properties. However, developing this type of robot encounters a motion coupling issue that the movement of one joint leads to the motion of other joints, resulting in complex control. In this paper, we proposed a novel approach for motion decoupling based on a noncircular pulley. The length change of the driving cable caused by the motion coupling problem is resolved by using the noncircular pulley. The calculation process of the profile for the noncircular pulley is illustrated in detail. An optimization process based on the brute force method is presented to identify the optimal parameters to minimize the compensation error. A cable-driven serial robot based on the decoupling method is prototyped for assessments. Experiments are conducted to evaluate the performance of the proposed motion decoupling method. The results reveal that the proposed method can effectively resolve the motion coupling issue by maintaining almost constant cable length with a maximum accumulative error only as 0.086 mm, demonstrating the effectiveness of the method.

Model free sliding mode control for serial robot manipulator: rigid and elastic joint robot

Model free sliding mode control for serial robot manipulator: rigid and elastic joint robot

Accurate kinematic calibration of a six-DoF serial robot by using hybrid models with reduced dimension and minimized linearization errors

PurposeIn typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.Design/methodology/approachThe negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.FindingsThe proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.Originality/valueThis new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.

Simultaneous identification of geometric parameters and structural stiffness of serial robots composing flexible links

It has been a formidable challenge to accurately predict the pose of serial robots composing flexible links due to the difficulties in simultaneously considering geometric errors and link flexibility. This paper presents an approach for simultaneously identifying kinematics and stiffness parameters in the flexible serial robot. A compliance equivalent method is employed to model the flexibility in the joints and links nonlinearly. Based on this, the kinetostatics model of those serial robots can be established analytically. By approximating the force-deflection characteristics of the flexible links, a unified error model containing both geometric and compliance parameters is derived. Moreover, an adaptive total-least-square method is proposed for the identification considering constraints on the compliance coefficient. To verify the effectiveness of the proposed method, simulations on a single flexible link, a serial robot, and experiments on a 3-DOF planar serial manipulator are carried out. The results show that the residual errors of the manipulator can be significantly reduced by identifying the kinematics and stiffness parameters using the proposed approach.

Optimized Ray-Based Method for Workspace Determination of Kinematic Redundant Manipulators

Abstract Determining the workspace of a robotic manipulator is highly significant for knowing its abilities and planning the robot application. Several techniques exist for robot workspace determination. However, these methods are usually affected by computational redundancy, like in the Monte Carlo based method case, and their implementation can be complex. The workspace analysis of kinematic redundant manipulators is even more complex. This paper proposes a kinematically optimized ray-based workspace determination algorithm based on a simple idea and not affected by computational redundancy. The proposed method can be applied to any serial robot but is tested only on spatial kinematic redundant robots. The results show how the approach can correctly determine the robot workspace boundaries in a short time. Then, the correctness and computational time of the proposed optimized ray-based method are compared to pseudo-inverse Jacobian ray-based and Monte Carlo methods. The comparison demonstrates that the proposed method has better results in a shorter time. Finally, some limitations of the proposed algorithm are discussed.

A general energy modeling network for serial industrial robots integrating physical mechanism priors

Industrial robots (IRs), as the core equipment of intelligent manufacturing, play increasingly important roles in various industrial scenarios such as assembly, welding, handling, and spraying, significantly improving production efficiency and product quality. The massive popularization and application of IRs have brought about a sharp increase in energy consumption (EC), and the modeling and optimization of EC is becoming imperative. In this paper, a general energy modeling network DM-PLM for serial IRs based on Dynamic Model (DM) and Power Loss Model (PLM) is proposed by integrating the prior knowledge of IR power composition and dynamic mechanism, enabling efficient and accurate modeling of dynamics, power, and EC under multi-load conditions. Considering the force transmission characteristics of serial robots, this paper proposes an improved bidirectional recurrent neural network (BiRNN) to model the joint dynamics. Additionally, a power loss model based on the ResNet convolutional neural network is employed. Experiments are carried out with a KUKA KR210 heavy-duty robot and a UR5 collaborative robot. The results show that the DM-PLM model incorporating the physical mechanism priors achieves 97 %, 98 %, and 99 % modeling accuracy in joint torques, total power, and EC for both robots under multi-load conditions. In addition, the proposed DM-PLM model is applied to the EC optimization of KUKA KR210 through trajectory planning, which achieves over 30 % EC reduction with the genetic algorithm, providing an effective approach to improving the energy efficiency of serial IRs.

A novel stiffness-controllable joint using antagonistic actuation principles

The inherent safety of collaborative robots is essential for enhancing human–robot interaction. The primary challenge in creating soft components for these robots is achieving sufficient force and stiffness. This paper presents a joint design for collaborative robots that addresses this challenge by incorporating an antagonistic actuation principle, allowing for adjustable stiffness. The novelty of our variable-stiffness joint lies in achieving a wide range of stiffness variation at any bending angle through antagonistic actuation. This bio-inspired principle results from the activation of two opposing actuation chambers. Compared to existing joints, our proposed joint is compact and utilises a high percentage of soft materials, enabling safer human–robot interaction. The paper outlines the joint’s design and fabrication process, highlighting the feasibility of our innovative concept. Kinematic and stiffness models are introduced to analyse the bending and stiffness characteristics, which are further validated through experimental testing. The stiffness experiments demonstrate significant stiffness changes achievable through the antagonistic actuation principle. Additionally, force experiments reveal our joint can generate 20 N force at a 1.5×105 Pa pressure. A constant force output experiment confirms the joint’s advantages in providing consistent force compared to motors. Finally, a case study showcases how our proposed joint can be embedded in serial robots with variable stiffness capabilities under loading and safe human–robot interaction.