Design and Modeling of 9 Degrees of Freedom Redundant Robotic Manipulator

In disaster areas, robot manipulators are used to rescue and clearance of sites. Because of the damaged area, they encounter disturbances like obstacles, and limited workspace to explore the area and to achieve the location of the victims. Increasing the degrees of freedom is required to boost the adaptability of manipulators to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. These robot manipulators offer a reliable way to handle the barrier challenges since they can search in places that humans can't reach. In this research paper, the 9-DOF robotic manipulator is designed, and an analytical model is developed to examine the system’s behavior in different scenarios. The kinematic and dynamic representation of the proposed model is analyzed to obtain the translation or rotation, and joint torques to achieve the expected position, velocity, and acceleration respectively. The number of degrees may be raised to avoid disturbances, and to obtain the fast desired position and precise movements of the end-effector. The simulation of developed models is performed to ensure the adaptable movement of the manipulators working in distinct configurations and controlling their motion thoroughly and effectively. In the proposed configuration the joints can easily be moved to achieve the desired position of the end-effector and the results are satisfactory. The simulation results show that the redundant manipulator achieves the victim location with various configurations of the manipulator. Results reveal the effectiveness and efficacy of the proposed system

Time domain System Identification of Longitudinal Dynamics of Single Rotor Model Helicopter using SIDPAC

This paper presents a time-domain approach for identification of longitudinal dynamics of single rotor model helicopter. A frequency sweep excitation input signal is applied for hover flying mode widely used for space state linearized model. A fully automated programmed flight test method provides high quality flight data for system identification using the computer controlled flight simulator X-plane©. The flight test data were recorded, analyzed and reduced using the SIDPAC (System Identification Programs for Air Craft) toolbox for MATLAB, resulting in an aerodynamic model of single rotor helicopter. Finally, the identified model of single rotor helicopter is validated on Raptor 30-class model helicopter at hover showing the reliability of proposed approac

Design, Implementation and Testing of Master Slave Robotic Surgical System

The autonomous manipulation of the medical robotics is needed to draw up a complete surgical plan in development. The autonomy of the robot comes from the fact that once the plan is drawn up off-line, it is the servo loops, and only these, that control the actions of the robot online, based on instantaneous control signals and measurements provided by the vision or force sensors. Using only these autonomous techniques in medical and surgical robotics remain relatively limited for two main reasons: Predicting complexity of the gestures, and human Safety. Therefore, Modern research in haptic force feedback in medical robotics is aimed to develop medical robots capable of performing remotely, what a surgeon does by himself. These medical robots are supposed to work exactly in the manner that a surgeon does in daily routine. In this paper the master slave tele-robotic system is designed and implemented with accuracy and stability by using 6DOF (Six Degree of Freedom) haptic force feedback devices. The master slave control strategy, haptic devices integration, application software designing using Visual C++ and experimental setup are considered. Finally, results are presented the stability, accuracy and repeatability of the syste

A Hybrid Flight Control for a Simulated Raptor-30 V2 Helicopter

This paper presents a hybrid flight control system for a single rotor simulated Raptor-30 V2 helicopter. Hybrid intelligent control system, combination of the conventional and intelligent control methodologies, is applied to small model helicopter. The proposed hybrid control used PID as a traditional control and fuzzy as an intelligent control so as to take the maximum advantage of advanced control theory. The helicopter?s model used; comes from X-Plane flight simulator and their hybrid flight control system was simulated using MATLAB/SIMULINK in a simulation platform. X-Plane is also used to visualize the performance of this proposed autopilot design. Through a series of numerous experiments, the operation of hybrid control system was investigated. Results verified that the proposed hybrid control has an excellent performance at hovering flight mode

Stable Hovering Flight for a Small Unmanned Helicopter Using Fuzzy Control

Stable hover flight control for small unmanned helicopter under light air turbulent environment is presented. Intelligent fuzzy logic is chosen because it is a nonlinear control technique based on expert knowledge and is capable of handling sensor created noise and contradictory inputs commonly encountered in flight control. The fuzzy nonlinear control utilizes these distinct qualities for attitude, height, and position control. These multiple controls are developed using two-loop control structure by first designing an inner-loop controller for attitude angles and height and then by establishing outer-loop controller for helicopter position. The nonlinear small unmanned helicopter model used comes from X-Plane simulator. A simulation platform consisting of MATLAB/Simulink and X-Plane© flight simulator was introduced to implement the proposed controls. The main objective of this research is to design computationally intelligent control laws for hovering and to test and analyze this autopilot for small unmanned helicopter model on X-Plane under ideal and mild turbulent condition. Proposed fuzzy flight controls are validated using an X-Plane helicopter model before being embedded on actual helicopter. To show the effectiveness of the proposed fuzzy control method and its ability to cope with the external uncertainties, results are compared with a classical PD controller. Simulated results show that two-loop fuzzy controllers have a good ability to establish stable hovering for a class of unmanned rotorcraft in the presence of light turbulent environment

Comparative Analysis of Feature Extraction Methods for Cotton Leaf Diseases Detection

Cotton leaf diseases must be accurately detected and classified to reduce plant diseases and output losses. Feature extraction strategies for automated cotton leaf disease diagnosis are compared in this study. The research uses HOG, SIFT, SURF, GLCM, and Gabor wavelets filter feature extractor to extract features. We gathered and preprocessed 2400 cotton leaf images of healthy and diseases, Angular Leaf Spot, Bacterial Blight, Cotton curl leaf disease (CLCuD), as well as Alternaria Disease. K-means clustering separates leaf areas and improves feature extraction in image segmentation. Discriminative features are extracted using the mentioned methods, and Support Vector Machine (SVM) classifier is employed for disease identification. The comparative analysis based on Accuracy, Precision, and Sensitivity reveals the Gabor Wavelet Filter Feature Extractor as the top performer, achieving 92% accuracy on the test dataset containing bacterial blight, curl virus, alternaria, and healthy leaves. While HOG, SIFT, SURF, and GLCM methods also perform well, they are outperformed by the Gabor Wavelet method. This study shows Gabor wavelet-based features can accurately identify and classify cotton leaf illnesses, helping farmers fight plant diseases. The results underscore the need of choosing proper feature extraction methods for autonomous plant disease diagnostic systems

3DoF Model Helicopter with Hybrid Control

Dynamics of miniature unmanned helicopter are considered nonlinear and mutually coupled; therefore designing of a stable control becomes a big challenge for researchers. This paper addresses this issue by proposing a hybrid control methodology using both traditional and intelligent control. A 3DoF model helicopter system is used as a controlled platform. This hybrid control used PID as a traditional and fuzzy as an intelligent control so as to take the full advantage of advanced control theory. Proposed hybrid control is evaluated against the fuzzy and PID control through intensive simulation. Results verified that the proposed control has an excellent performance in static as well as dynamic environment as compared to individual PID and fuzzy control. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.509

Identification of Nonlinear System Based on Fuzzy Model with Enhanced Gradient Search

Theidentification and modeling theory of nonlinear systems has always been challengingto researchers.  Fuzzy system due to its languagedescriptive way similar to human brain and deal with qualitative informationintelligently proves better choice for nonlinear system modeling over last fewdecades. The fuzzy system theory itself also has nonlinear characteristics thereforewhen establishing the fuzzy model of nonlinear system; it should be able towell describe the nonlinear characteristics. Takagi-Sugeno (TS) fuzzy systemsare not only suitable for modeling the nonlinear system due to combination ofthe good performance with the simple linear expressions, but also useful todesign the fuzzy controller. This paper proposed a new optimization algorithm namedas Enhanced Gradient Search (EGS) for identification of nonlinear system basedon TS fuzzy system. In proposed EGS, parameters of membership functions aretrained adaptively so as to calculate the gradient of cost function which isnecessary for minimizing the error. Using gradient information of costfunction, EGS applies in an innovative way such that it keeps and updates thebest search results at every training step during the optimization process. Theapplicability of EGS for TS fuzzy model shows splendid performance especially inmodeling of nonlinear system

Design and Implementation of Probe Driver Teleoperative Force Feedback System

The basic need of neurosurgery is to insert the probe into the key hole linearly for performing functional neurosurgery, trigeminal neuralgia surgery, biopsies, deep brain stimulation, and stereo-EEG. Recently, tele-robotic systems have been introduced to assist surgeon during invasive procedures to obtain desired results. In this paper, a linear probe driving tele-operative system with force feedback is proposed. The proposed system is highly accurate, stable, and safe and provides haptic transparency to the surgeon during its operation. The master slave architecture, control system and software application are designed to inject and eject probe driving trials. The experiments are performed on a piecewise linear Plasticine model. The accuracy, stability, repeatability of the system and haptic force feedback fidelity are discussed in the results.  DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.527