International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 11, November – 2018, Pages: 28-33 www.ijeais.org/ijaer 28 An Improved Approach of Inverse Kinematics Solution for Robotics Arm with Five Degree of Freedom Using ANFIS W. W. Marzouk 1 , Adel A. Elbaset 2 , A.I.A. Galal 3, Amr Emad4 1 Production and Design Engineering Faculty of Engineering, Minia University, El-Minia, Egypt wagihw.marzouk@yahoo.com 2 Electrical Engineering Department, Faculty of Engineering ,Minia university, El-Minia, Egypt Adel.Soliman@mu.edu.eg 3 Electrical Engineering Department, Faculty of Engineering ,Minia university, El-Minia, Egypt galal_999@yahoo.com 4 Dept. of Mechanical Eng., El-Minia High Institute for Engineering and Technology, El-Minia, Egypt Engamremad77@yahoo.com Abstract-the FK (forward kinematics) and IK (inverse kinematics) of robotics is very difficult, as result to the occurrence of uncertain, nonlinear formulations and having multiple solutions. Many conventional methods are insufficient to find the solution. Therefor it is required to use easy and accurate way for the calculation of IK of robotics. This work shows ANFIS (Adaptive Neuro Fuzzy Inference System) architecture to optimize the IK solution. The designed (ANFIS) model has specified the correct coordinates in line with the certain angles of Cartesian coordinate. The object form the work is the employ of the (ANFIS) to discussion the advantage of the robot system instead of to give direct robotics arm system. This method causes a lowering in the difficulty and calculations faced when using the traditional methods in robotics arm. It shows a reasonably very good suitable for θ2 and other values. The average total error for the training data are found to be 2.8004* 10-5, 4.19*10-6, 3.31*10-5, 3.72*10-5, and 7.33*10-6 for the joint coordinates θ1, θ2, θ3, θ4, and θ5, respectively. Keywords- ANFIS; IK; Degrees of Freedom; robotics; D-H 1. INTRODUCTION The Robotics arm was Consisted of inflexible link joined by revolute joints. The position of joints generally close to a neighboring joints. Linking of progressive joints are qualified by 4x4 symmetrical matrix contain the robotics arm positions. The robotics arm D.O.F (Degree of Freedom) is set by the flexibility of transformation matrices reduplicate the matrices gives the mechanical robotics arm last position. Joint directions contain the control actions, though directions determine the robotics arm movements. That changing over the end of robotics arm to calculating the IK for joint angle in robotics arm to ca0n be controlled in the robotics arm [1-4]. Intelligent self-learning controlling in systems, fuzzy logic (FL), Artificial Neural Network (ANN) and ANFIS are the modern execution [5]. ANFIS approaches are suitable for real time adaptive manageable of robotics arm with a accepted error. It is competent with learning and building of complex functions, which are used in different applications like pattern recognition, approximation and fitting of data dynamic errors. Hariharan et al. [6] developed an immediate IK of odd number of D.O.F robotics arm with a mutual mathematical as well as methodical approach. The work prepare a novel, computationally competent process of executing IK for universal odd no. of D.O.F robotics arm with a spherical joint at the wrist. Kinematic and dynamic suspicion found the solution. Aggarwala et al. [7] suggested the ANN for the improvement of an IK problem with optical detection of spectacle zone. This method shows a non-conventional method to solve the IK problem using ANN. Fahmy et al. [8] improve NF (neural fuzzy) using IK control frame of robotic arm utilize for rehabilitation applications. It presented a new NF regulator for robot arm. The inductive information method is used to make the necessary IK rule from in/out data set recording. The manage frame offer good quality result match to the predictable methods. Alavandar at.al. [9] Suggested IK solution of two D.O.F and three D.O.F planar arm robotics using ANFIS. In this work, they adopted the structure of the fuzzy type Surgeon and the combination with the Neural Network (NN) model to deduction the IK of planar arm robots. In this paper improve an ANFIS controller for solve IK problem of a five D.O.F robotics arm, structure algorithm Depends on the update of the data by minimizing the error after each repetition process. 2. STRUCTURE ROBOTICS ARM OF 5 D.O.F AND ITS MODELING Figure. 1 A six arm Robot International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 11, November – 2018, Pages: 28-33 www.ijeais.org/ijaer 29 Figure. 2 structure for the robotics arm [10]. Figure 1. Shows how design a six arm robotics by solid works while fig.2 shows its Coordinate frames for the arm robotics and the relation between the joints and links. While defining the four important data by the D-H method [10]. Fig3. Shows the D-H general frame assignment. Where: • = space from measured along • = angle from measured along • = space from measured along • = angle from measured along Fig. 3. Denavit-Hartenberg general frame assignment [10]. Table 1, D-H data for different link of robotics arm Based on Table 1 between and can be write in equ. (1) As, ( ) ( ) ( ) ( ) ( ) The D-H data identical to this 6 links for robotics arm are listed in Table 1. The limit of all the angle were fixed also in the table and this limits were calculated. The D-H methodology is used to know its FK [10]. By replace (D-H) data in Table.1 into equ.(1), will be acquire and the common matrices from all the angle joint of the five D.O.F robotics arm will be derive by multiply all the matrix (0T6) [10]. 0T6= A1A2A3A4A5A6=* + ( ) Where ( ) are the positions and {( ) ( ) ( )+ are the all directions of the end robotics arm. The all directions of the robotics arm will be calculate in angles equations of (D-H table) to the robotics arm is seen in eqn.(2) [9.10]. Where: ( ) ( ) ( ) ( ) By balance the matrix in equ.(2) we can derive the equations following : ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) From equation (3) to (14), the position and directions of the five D.O.F robotics arm will be calculate the model can solve the FK by know all angles. The solution for is, ( , ) ( ) Therefore, there are several possible solutions for , which are as follows: * ( )+ ( ) Now consider the possible solutions for # d a α 1 d1=110 a1=35 -90o 2 0 a2=140 0 3 0 0 90o4 d4=130 0 90o 5 0 0 90o6 d6=140 0 0 International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 11, November – 2018, Pages: 28-33 www.ijeais.org/ijaer 30 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ( ) √ ) ( ) Now that are known, the solutions for will by find it's by know all FK equations. From the equation (11), can be known The solution for is [10] ( . / ) ( ) To solve form equation (8), can be known as: ( ) ( ) ( ) ( ) Now using this above derivation of and is derived as follows(9) * ( ) ( )+ ( ) Now it has been completed solution to IK of five D.O.F robotics arm. 3. ANFIS ARCHITECTURE The model structure of the ANFIS explain in fig.4. The end robotics arm positions (X, Y, Z) are the in/out are the joint angles (θ1, θ2, θ3, θ4, θ5). Between FIS models, the Surgeon FL is utilized because its rise performance. The studying algorithm accuracy the MF function utilize the train in/out parameters Show the output of , Layer1 : Every node in use a node function set by: ( ) Where will embrace any fuzzy (MF). Layer 2: All the node calculated from the firing strength ( ) Layer 3: Can calculate the by this equation [11]: Layer 4: All the node has function as following: ( ) is the output of layer3, and ( , , , ) Layer 5: By this equation can be calculate the single node ∑ ∑ The coordination and the all angle acquired from FK solved by the testing data to train ANFIS with (member function) MF. For solving the IK equation of five D.O.F , in this method, believes the ANFIS frame with first order Surgeon model containing rules. For the NF model used in this research , data points analytically acquired using FK . Of which are utilized for training and the remaining are utilized for testing. Training of ANFIS is usually completed by using ANFIS designer in Matlab [12]. 4. RESULTS AND DISCUSSION To take control the results which non-linear. should solve the problem of the IK to can be controlled on the robotics arm by working on confirm the direction and the positions of all joints angles could be desired when planning the trajectory for the robotics arm, a supervised feed forward ANN had been designed using FL designer on Matlab program. For example, for a FIS with three input, each with MF , the grid0 section leads to . GENFIS01 use a given training data set to generate an initial FIS that can be fine-tuned via the ANFIS command. International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 11, November – 2018, Pages: 28-33 www.ijeais.org/ijaer 31 Fig6.ANFIS model structure Fig .7 3D plot of for five D.O.F robotics arm Fig.8 3D plot of for five D.O.F robotics arm Fig.9 3D plot of for five D.O.F robotics arm Fig.10 3D plot of for five D.O.F robotics arm Fig.11 3D plot of for five D.O.F robotics arm Figures7 to 11 show 3D plot the ANFIS with angle joint of 5 D.O.F robotics arm. Fig.4 shows the 3D plot between for . It indicates that the values of move in a negative trend, with a very small increase followed by a lower in value. The in/out 3D plot of is indicated in Fig.5. The figure display value of high linear when move in the negative trend of and little of values of and then there is a sudden lower of value. No big move in the value of is take notice with move in values of coordinate. When change from negative value to positive value, there is a little high in the value of as well as there is no important, change with the value International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 11, November – 2018, Pages: 28-33 www.ijeais.org/ijaer 32 of , as clearly noticed from Fig 6. Similarly, the 3D plot for are shown in Fig.8. The in/out 3D plot of is shown in Fig.7. The Figure depicts that the value of decreases first followed by increase, for the increase in the value of . No big move in the value of is take notice with move in values of coordinate Fig.12 Plot of training data for θ1 Fig.13 Plot of training data for θ2 Fig.14 Plot of training data for θ3 Fig.15 Plot of training data for θ4 Fig.16 Plot of training data for θ5 The plots of training data for , , , , and of five D.O.F robotics arm are shown in Figures 12 to 16, respectively. Fig. 10 shows a showing a good fit for training data of . As little error lie close to the horizontal axis shown in Fig.13, it shows a moderately very good about for and other values. The average total error for the training data are found to be 2.804*10 -5 , 4.19*10 -6 , 3.31*10 -5 , 3.72*10 -5 , and 7.33*10 -6 for the joint coordinates , , , , and respectively Table5.Compison between this work and other work Study the all graph data for , , , , and of Five D.O.F robotics arm. It shows the model is good appropriate for the research Figure 13, 14 and 15. Table 5 presents a comparison between the results obtained in this paper and others published previously (14,15) 5. CONCLUSIONS This paper, can solve IK problem by applying ANFIS in a five D.O.F robotics arm different in angles joint prediction with ANFIS structure for a five D.O.F robotics arm obviously indicates the suggested model predict angle for all joints together with moderately suitable errors. ANFIS structure predict angle for all joints together with little number of recurrence. As a consequence, the training ANFIS structure will be use to solution interrupted IK robotics arm and by this method, working ANFIS and stand by approach to accord with IK. The explanatory IK model obtained permanently supply correct angles joint for move the robotics arm to any position. The method used for now the IK model for the arm could be used to other types of robotic arms progressing by the five D.O.F robotics arm The average total error for the training data are found to be 2.8004* 10 -5 , 4.19*10 -6 , 3.31*10 -5 , 3.72*10 -5 , and 7.33*10 -6 the angles for , , , , and , respectively. It will be conclude that, the advanced solution prove and the advantages of robotics arm s in application with surprising path motion in obscure environment. REFERENCE present work Ref. 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