Achmad Jazidie

A Robust Obstacle Avoidance for Service Robot Using Bayesian Approach

The objective of this paper is to propose a robust obstacle avoidance method for service robot in indoor environment. The method for obstacles avoidance uses information about static obstacles on the landmark using edge detection. Speed and direction of people that walks as moving obstacle obtained by single camera using tracking and recognition system and distance measurement using 3 ultrasonic sensors. A new geometrical model and maneuvering method for moving obstacle avoidance introduced and combined with Bayesian approach for state estimation. The obstacle avoidance problem is formulated using decision theory, prior and posterior distribution and loss function to determine an optimal response based on inaccurate sensor data. Algorithms for moving obstacles avoidance method proposed and experiment results implemented to service robot also presented. Various experiments show that our proposed method very fast, robust and successfully implemented to service robot called Srikandi II that equipped with 4 DOF arm robot developed in our laboratory.

Indoor Navigation Using Adaptive Neuro Fuzzy Controller for Servant Robot

We present our ongoing work on the development of Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for humanoid servant robot designed for navigation based on vision. In this method, black line on the landmark used as a track for robot’s navigation using webcam as line sensor. We proposed architecture of ANFIS controller for servant robot based on mapping method, 3 input and 3 output applied to the controller. Only 45 training data used for navigation and best error starting at epoch 62. Each of the components are described in the paper and experimental results are presented. Humanoid servant robot also equipped with 4DOF arm robot, face recognition and text to speech processor. In order to demonstrate and measure the usefulness of such technologies for human-robot interaction, all components have been integrated and have been used for a servant robot named Srikandi I. Based on experiments, ANFIS controller successfully implemented as controller for robot’s navigation.

Hybrid fuzzy control for swinging up and stabilizing of the pendulum-cart system

This paper presents the design and implementation of a hybrid fuzzy control for the swinging up and stabilizing of the pendulum-cart system. The fuzzy swing-up controller is employed to swing the pendulum up from its pendant position to the stabilization zone in the upright position using as few rules as possible. After the pendulum reaches the zone, the fuzzy stabilizing controller is then switched to stabilize the inverted pendulum at the upright position. The controller is designed based on a robust performance state feedback controller using Linear Matrix Inequalities (LMI) approach for Takagi-Sugeno fuzzy systems. Numerical simulation and real-time experiment are presented to show the effectiveness of the method.

Fuzzy tracking control design using observer-based stabilizing compensator for nonlinear systems

This paper presents fuzzy tracking control design for nonlinear systems. The design methodology is a synthesis of the tracking control theory of linear multivariable control and the Takagi-Sugeno fuzzy model. The observer-based stabilizing compensator type from multivariable tracking control theory is used, because not all states of the nonlinear system are fully available or measured while Takagi-Sugeno (T-S) fuzzy model is used to represent the dynamic of nonlinear system. The concept of parallel distributed compensation is employed to design fuzzy tracker and fuzzy observer from the T-S fuzzy model. The stability analysis of the designed system is derived via the Lyapunov function. Numerical simulation and real-time experiment are provided to illustrate the tracking control design procedure and performance of the proposed methods for practical application.

An Improved Face Recognition System for Service Robot Using Stereo Vision

Service robot is an emerging technology in robot vision, and demand from household and industry will be increased significantly in the future. General vision-based service robot should recognizes people and obstacles in dynamic environment and accomplishes a specific task given by a user. The ability to face recognition and natural interaction with a user are the important factors for developing service robots. Since tracking of a human face and face recognition are an essential function for a service robot, many researcher have developed face-tracking mechanism for the robot (Yang M., 2002) and face recognition system for service robot( Budiharto, W., 2010). The objective of this chapter is to propose an improved face recognition system using PCA(Principal Component Analysis) and implemented to a service robot in dynamic environment using stereo vision. The variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals (Adini et al., 1997). Recognizing face reliably across changes in pose and illumination using PCA has proved to be a much harder problem because eigenfaces method comparing the intensity of the pixel. To solve this problem, we have improved the training images by generate random value for varying the intensity of the face images. We proposed an architecture of service robot and database for face recognition system. A navigation system for this service robot and depth estimation using stereo vision for measuring distance of moving obstacles are introduced. The obstacle avoidance problem is formulated using decision theory, prior and posterior distribution and loss function to determine an optimal response based on inaccurate sensor data. Based on experiments, by using 3 images per person with 3 poses (frontal, left and right) and giving training images with varying illumination, it improves the success rate for recognition. Our proposed method very fast and successfully implemented to service robot called Srikandi III in our laboratory. This chapter is organized as follows. Improved method and a framework for face recognition system is introduced in section 2. In section 3, the system for face detection and depth estimation for distance measurement of moving obstacles are introduced. Section 4, a detailed implementation of improved face recognition for service robot using stereo vision is presented. Finally, discussions and future work are drawn in section 5.

Reconfigurable Controller Based on Fuzzy Descriptor Observer for Nonlinear Systems with Sensor Faults

In this paper, the FTC system for multiple operating condition nonlinear systems subjected to sensor faults is developed by applying reconfigurable control scheme. The scheme generates any modified control signal using appropriate additive reference signal to the nominal control system. The proposed observer is developed based on descriptor approach in the fuzzy Takagi-Sugeno model configuration in order to accommodate some operating conditions of a nonlinear system. The simulation result shows that the proposed method has capability to compensate more than one sensor fault occurred in a three-tank benchmark system even there is a change in condition operation as well as in reference signal.

A method for path planning strategy and navigation of service robot

This paper presents our work on the development of Path Planning Strategy and Navigation by using ANFIS(Adaptive Neuro-Fuzzy Inference System)controller for a vision-based service robot. The robot will deliver a cup to a recognized customer and a black line as the guiding track for navigating a robot with a single camera. The contribution of this research includes a proposed architecture of ANFIS controller for vision-based service robot integrated with improved face recognition system using PCA, and the algorithm for moving obstacle avoidance. We also propose a path planning algorithm based on Dijkstra’s algorithm to obtain the shortest path for robot to move from the starting point to the destination. In order to avoid moving obstacles, we have proposed an algorithm using binaural ultrasonic sensors. The service robot called Srikandi is also equipped with 4 DOF arm and a framework of face recognition system. The proposed path planning strategy and navigation was tested empirically and proved effective.

A Novel Static and Moving Obstacles Avoidance Method Using Bayesian Filtering for Service Robot

This paper presents a novel static and moving obstacles avoidance method in indoor environment for service robot. This method uses combination of information about static obstacles on the landmark, speed and direction of people that walks as moving obstacle obtained by single camera, then calculated the probability of collision using Bayesian Filtering. In this research, 2 stopping point in landmark used for efficiency in detecting and processing obstacles. By increasing/lowering the speed of robot based on the state estimation calculated before, robot able to avoid the moving obstacles. Algorithms for static and moving obstacles avoidance proposed and simulation result implemented to service robot presented. This method very robust and successfully implemented to service robot called Srikandi II that equipped with 4 DOF arm robot in our laboratory.

Temperature distribution pattern in normal and cancer tissues: the effect of electromagnetic wave

Abstract : Temperature distribution pattern on normal and cancer tissues caused by the Electromagnetic wave effect is presented in this paper. First, the pattern is modelled by using Bio Heat Transfer Equation and then the Galerkin Finite Element method is used to solve the equation via computer simulation. From the simulation results it can be shown that the temperature change on the cancer tissues is relatively constant and 0.4 degrees Celsius higher than the change on the normal tissues. From this phenomenon it can be understood that the damage of the cell of the cancer tissues is greater than the damage of the cell of the normal tissues. Therefore it is possible to use the Hyperthermia technique with electromagnetic wave for cancer therapy. The simulation results can be also used to decide the control strategy for giving the dose energy of electromagnetic wave which is flowed out to the cancer tissues.

Design of actuator fault compensation with MRC in 2 DOF manipulator based on PID CTC

All mechanical and electronic systems can run into performance degradation including robot Manipulators. One cause of such performance degradation is due to the occurrence of fault on the actuator. The occurrence of actuator fault on Robot Manipulator 2 DOF (Degree of Freedom) will make tracking of the robot shifted from its reference, cause signal deviation and enlarge overshoot. Estimation and compensation techniques can be a solution to this problem, but these techniques can only be done if the designed system is capable of generating residual signals. This signal is a comparison of the response signal between the actual system and the MRC response signal. This paper explains the design of an AFTC (Active Fault Tolerant Control) algorithm based MRC. When an actuator fault happened, it was estimated and compensated with Model Reference Control (MRC) using Proportional Integral Derivative (PID) based on Computed Torque Control (CTC) law. Simulation result shows that the designed system can compensate actuator fault with small error tracking error about 0.0068 rad and has time response less than 1s. It also reach minimum overshoot through 0.041 rad.