This article presents the design and validation of a regression model for the identification of dynamic parameters in manipulator robots. The model exhibits implementation advantages as it is based on the acquisition of position, speed and voltage data from the actuator in each joint rather than on the calculation of acceleration and torque. Actuators can be direct current and/or servomotor type. The regression model developed is simulated using MATLAB/Simulink software to identify the parameters of 2-DoF (Degrees of Freedom) and 5-DoF manipulator robots. Additionally, the model is experimentally validated on a real 5-DoF redundant manipulator robot. The identification model has great advantages in terms of implementation.

https://link.springer.com/content/pdf/10.1007/s00419-020-01865-2.pdf

Design and validation of a dynamic parameter identification model for industrial manipulator robots

This research delves into the development and evaluation of two distinct controllers for a 3-DoF robotic arm in the context of Industry 4.0. Two primary control strategies are presented in the study. The first is a Fuzzy Logic Controller that utilizes joint position error and its derivative as inputs, employing a set of 9 control knowledge rules. The second is an Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller, trained to learn the inverse dynamic model of the robot through a structured dataset. The research emphasizes the importance of accurate parameter tuning and data acquisition to achieve optimal control system performance. Extensive experimentation was conducted to evaluate the controllers’ performance in trajectory tracking and their response against external disturbances, such as load variations. The controllers exhibited remarkable precision and proficiency in tracking reference trajectories, with minimal deviations, overshoots, or oscillations. A quantitative analysis using performance indices such as root mean square error (RMSE) and the integral of the absolute value of the time-weighted error (ITAE) further confirmed the controllers’ effectiveness. Notably, the ANFIS Controller consistently outperformed the Fuzzy Logic Controller, demonstrating superior precision in trajectory tracking. The study underscored the importance of selecting the right control method and obtaining high-quality training data. Challenges in parameter tuning for Fuzzy Logic Controllers and potential time constraints in training ANFIS were discussed. The findings have significant implications for advancing robotic control systems, particularly in the era of Industry 4.0.

Fuzzy Control Strategies Development for a 3-DoF Robotic Manipulator in Trajectory Tracking

Study of a serial manipulator involves many non-linear functions and complex sets of equations. The complexity of the problem increases as mobility of the system increases and it becomes a very tedious task to analyse the robotic system especially the inverse kinematics and forward dynamics. This study is aimed to reduce the complexity of analysis by implementing adaptive neuro-fuzzy inference system-based inverse kinematic analysis and forward dynamic analysis. The CAD model of serial manipulators is prepared using SOLIDWORKS to get geometrical and inertial information. The manipulator is also mathematically modelled in MATLAB and its forward kinematics (FK), inverse kinematics (IK), and dynamic analyses are carried out. The ANFIS networks are trained using data generated by a mathematical model, and it is then tested for a new set of data. Finally, the results are validated by comparing with that of the mathematical model.

ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator

The manual disc cutter changing operation in tunnel boring machine (TBM) construction seriously restricts the safety and efficiency of tunnel engineering. To realize robot cutter changing in the narrow space inside TBM, a PPRP type serial robot is studied. The overall coverage rate of disc cutter replacement is 41.3%, and that of forward disc cutter replacement is 57.6%. Based on the trapezoidal velocity curve and quintic polynomial curve, a hybrid curve trajectory planning method for the disc cutter changing robot is proposed. Compared with the quintic polynomial curve, the motion time of the hybrid curve method is reduced by 16.1%, and the joint has no impact. Aiming at the problem of obtaining the compensation term of the control system model, the kinematics and dynamics equations of the robot are derived according to its body structure. A variable structure PID controller based on dynamic model compensation is designed. The simulation results show that the relative error of the robot end displacement in X, Y, and Z directions is less than 0.01%, and the maximum absolute error is only -0.0227 mm. The control performance is good.

Motion Control of Disc Cutter Changing Robot Body for Tunnel Boring Machine

This work deals with the modeling process of a new three dimensional human-like robot for an inverse dynamic analysis. This robot intends to be utilized by caregivers to assist persons with reduced mobility (such as the elderly). The model under analysis is composed by 24 rigid bodies: 3 to represent the robot’s base and locomotion, 4 for the lower limbs and torso, 7 for each arm, and 3 for the head. The resulting multibody system has 19 degrees-of-freedom driven by 4 linear actuators and 15 revolute motors. The proposed approach was implemented using an in-house computational code, and validated against a commercial software for a general spatial motion. The outcomes achieved show that the proposed formulation is computationally effective both in terms of efficiency and accuracy. The general findings of this study are promising and useful for the mechanical design and construction of a real human-like robot prototype. 

/pdf/dynamic-modeling-of-a-human-inspired-robot-based-on-a-newton-3jh9ubft.pdf

Dynamic Modeling of a Human-Inspired Robot Based on a Newton-Euler Approach

This paper presents the structure of the four-legged robot (Mini-Bot), dynamical equation of the multibody system, numerical results for the generation of the positions of each leg in the Cartesian coordinate system and angular velocities of each at different time and experimental results of locations for each links calculated in the Cartesian coordinate system. In this paper we used the Euler-Lagrange method to generate the dynamical equations of the Mini-Bot. The calculation of dynamic equations is performed using Mupad toolbox from MATLAB software. The experimental results and dynamical equations will be applied to the prototype of Mini-bot.

Analysis of Position and Angular Velocity of Four-Legged Robot (Mini-Bot) from Dynamic Model Using Euler-Lagrange Method

The inverse dynamics calculation of a robot manipulator is essential in a robot manipulator control system. The commonly used approaches to formulate dynamic models of robot manipulators are Newton-Euler and Lagrange-Euler methods. Since both methods are numerical recursive methods, they are computationally expensive and not suitable to be used directly in real time applications. In this paper, the adaptive-network-based fuzzy inference system (ANFIS) is used to construct the input-output mapping of inverse dynamics model of a robot manipulator. To create the training data sets for the ANFIS systems, the dynamic model of a 5 degree-of-freedom robot manipulator is computed using Newton-Euler dynamic formulation. The proposed method is tested in formulating the required torques of a point-to-point trajectory. The results show that the proposed method possesses shorter operational time and its performance is comparable to numerical method. The proposed method can be used for the rigid-body robot manipulators whose dynamical characteristics are known.

Efficient Method for Inverse Dynamics of Robot Manipulators by using Adaptive-network-based Fuzzy Inference System

The article proposes the development of a software module for modeling the kinematics and dynamics of a manipulator with five degrees of freedom. To solve the forward kinematics problem of the manipulator, the Denavit–Hartenberg method was used. To solve the inverse kinematics and dynamics problem of the manipulator, analytical methods (the Levenberg-Marquardt method, the Newton–Euler method) and a soft computing method (adaptive neurofuzzy inference system) were used. The software module for modeling the kinematics and dynamics of the manipulator was developed using the software package of the SolidWorks computer-aided design system and the MatLab program. The developed software module is able to simulate the kinematics and dynamics of the manipulator based on the described methods, visualize the simulation results, generate a trajectory for the target position and orientation of the end-effector of the manipulator, simulate the movement of the manipulator along a given trajectory.

Program complex for modelling a manipulating robot

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Papers

Analysis of Position and Angular Velocity of Four-Legged Robot (Mini-Bot) from Dynamic Model Using Euler-Lagrange Method

Efficient Method for Inverse Dynamics of Robot Manipulators by using Adaptive-network-based Fuzzy Inference System

Program complex for modelling a manipulating robot