Hyungsuck Cho

A sensor-based navigation for a mobile robot using fuzzy logic and reinforcement learning

The proposed navigator consists of an avoidance behavior and goal-seeking behavior. Two behaviors are independently designed at the design stage and then combined them by a behavior selector at the running stage. A behavior selector using a bistable switching function chooses a behavior at each action step so that the mobile robot can go for the goal position without colliding with obstacles. Fuzzy logic maps the input fuzzy sets representing the mobile robots state space determined by sensor readings to the output fuzzy sets representing the mobile robots action space. Fuzzy rule bases are built through the reinforcement learning which requires simple evaluation data rather than thousands of input-output training data. Since the fuzzy rules for each behavior are learned through a reinforcement learning method, the fuzzy rule bases can be easily constructed for more complex environments. In order to find the mobile robots present state, ultrasonic sensors mounted at the mobile robot are used. The effectiveness of the proposed method is verified by a series of simulations. >

Orthogonal distance fitting of implicit curves and surfaces

Dimensional model fitting finds its applications in various fields of science and engineering and is a relevant subject in computer/machine vision and coordinate metrology. In this paper, we present two new fitting algorithms, distance-based and coordinate-based algorithm, for implicit surfaces and plane curves, which minimize the square sum of the orthogonal error distances between the model feature and the given data points. Each of the two algorithms has its own advantages and is to be purposefully applied to a specific fitting task, considering the implementation and memory space cost, and possibilities of observation weighting. By the new algorithms, the model feature parameters are grouped and simultaneously estimated in terms of form, position, and rotation parameters. The form parameters determine the shape of the model feature and the position/rotation parameters describe the rigid body motion of the model feature. The proposed algorithms are applicable to any kind of implicit surface and plane curve. In this paper, we also describe algorithm implementation and show various examples of orthogonal distance fit.

A Smooth Path Tracking Algorithm for Wheeled Mobile Robots with Dynamic Constraints

In order to avoid wheel slippage or mechanical damage during the mobile robot navigation, it is necessary tosmoothly change driving velocity or direction of the mobile robot. This means that dynamic constraints of the mobile robotshould be considered in the design of path tracking algorithm. In the study, a path tracking problem is formulated asfollowing a virtual target vehicle which is assumed to move exactly along the path with specified velocity. The drivingvelocity control law is designed basing on bang-bang control considering the acceleration bounds of driving wheels. Thesteering control law is designed by combining the bang-bang control with an intermediate path called the landing curve whichguides the robot to smoothly land on the virtual targets tangential line. The curvature and convergence analyses providesufficient stability conditions for the proposed path tracking controller. A series of path tracking simulations and experimentsconducted for a two-wheel driven mobile robot show the validity of the proposed algorithm.

Robotic assembly: a synthesizing overview

Robotic assembly systems offer tremendous promise for the flexible assembly automation but present a variety of complex research issues due to the positioning inaccuracy of the manipulator, dimensional variation of mating parts and their physical interactions. This paper provides an up-to-date survey of researches in robotic assembly with emphasis on parts mating technology. Depending upon the mating strategy, presently available methods of performing precision assembly operations are classified and their advantages and limitations are discussed from the view points of the system complexity, adaptability and reliability. The performance variables such as the mating speed, positioning error absorbing capability and applicability are compared in some details for various assembly methods.

A robust method for vision-based seam tracking in robotic arc welding

This paper presents a robotic seam tracking system which is aimed at achieving robustness against some welding noises such as arc glares, welding spatters, fumes etc. In particularly, a syntactic analysis is used to improve the extraction reliability of the joint features. The joint features thus obtained are used to extract the 3-dimensional information of the weld joint and then achieve the robot path correction. To show the performance of the developed system, a series of experiments on joint feature detection and robotic seam tracking are conducted for different types of weld joints. The results exhibit that the system is very robust to various welding noises as well as variations in appearance of weld joint and workpiece.

Microsurgical telerobot system

A microsurgical telerobot system has been developed according to the results of the microsurgery task analysis. Several fields of the microsurgery have been investigated and the surgery tasks and tool motions are analyzed to acquire guidelines for specifications of a microsurgical telerobot system. A slave robot system consists of a 6-DOF parallel micromanipulator, that is our own modified Stewart platform type, and a 6-DOF macro-motion industrial robot that mounts the parallel micromanipulator at the end. A 6-DOF force-reflecting master device has also been developed using five-bar parallel mechanisms driven by harmonic DC servomotors. A bilateral control algorithm has been proposed based on the force-position loop, and the local position controller for the master has been developed to minimize the effect of gravity, friction, and inertia.

Solder joints inspection using a neural network and fuzzy rule-based classification method

In this paper we described an approach to automation of visual inspection of solder joint defects of SMC(Surface Mounted Components) on PCBs(Printed Circuit Board) by using neural network and fuzzy rule-based classification method. Inherently the surface of the solder joints is curved tiny and specular reflective it induces difficulty of taking good image of the solder joints. And the shape of the solder joints tends to greatly vary with the soldering condition and the shapes are not identical to each other even though the solder joints belong to a set of the same soldering quality. This problem makes it difficult to classify the solder joints according to their qualities. Neural network and fuzzy rule-based classification method is proposed to effi-ciently make human-like classification criteria of the solder joint shapes. The performance of the proposed approach is tested on numerous samples of commercial computer PCB boards and compared with the results of the human inspector performance and the conventional Kohonen network.

Haptic control of the master hand controller for a microsurgical telerobot system

A microsurgical telerobot system has been developed based on the results of the operation task analysis. The telerobot system is composed of a 6-DOF parallel micromanipulator attached to the macro-motion industrial robot and a 6-DOF force-reflecting haptic master device. The master device uses five-bar parallel mechanisms driven by harmonic DC servomotors. The proposed 6-DOF master hand controller has nonlinear coupled dynamics and friction. Since the disturbance force due to friction, gravity and coupled inertia can distort the operators perception, a disturbance observer is introduced in the operational space and implemented in the microsurgery master hand controller.

A Robust Visual Seam Tracking System for Robotic arc Welding

Abstract A robotic seam tracking system is developed to achieve robustness against optical noises such as arc glares, welding spatters, fume, and other unexpected brightness sources. The profile data of a weld joint to be welded are reliably extracted using two separate vision processing algorithms: the first is for joint modeling before welding starts, while the second is for joint feature detection during welding. Each procedure is divided into several consecutive steps. In particular, the syntactic approach is refined to improve the reliability of the joint features extracted. To achieve more careful syntactic analysis, several junction primitives and production rules are newly defined. From the joint features thus obtained, the three-dimensional information of the weld joint is extracted to achieve the robot path correction. To investigate the performance of the developed visual system, a series of experiments on joint feature detection and robotic seam tracking are conducted for four different types of weld joints: butt, lap, fillet and vee. The results show that the system is very robust in the presence of various welding noises as well as variations in appearance of weld joint and workpiece.

A Sensor-based Obstacle Avoidance Controller For A Mobile Robot Using Fuzzy Logic And Neural Network

Abslmct-This paper proposes a sensor-based path planning method which utilizcs fuzzy logic and neural network for obstacle avoidancc of a mobile robot in uncertain environments. In order to acquire the information about the environment around the mobile robot, the ultrasonic sensors mounted on the front of mobile robot are used. The neural network, whose inputs arc preprocessed by ultrasonic sensor readings, informs the mobile robot of the situation of environment in which mobile robot is at the present instant. Then, according to the situatiou class, the fuzzy rules are fired to make a decision on the mobilc robot action. This structure has a merit that the fuzzy rules €or obstacle avoidance can be easily constructed for more cornplcx environments. In addition, this method can be implcrncoted real time sincc the number of fuzzy rules used to avoid the obstacles is small. The fuzzy rules are constructed based on the human reasoning and are tuned by iterative simulations. The cffectivcness of the proposed avoidance method is vcrilicd by a series of simulations. Path planning is one of tlie most vital task in navigation of autonomous niobiic robot. Path planning for mobile robot may be tlivitletl illto two categories: One is the global path planning based on a priori complete inforniation about the environment antl the other is the local path pliinning based on sensory information i n uncertain environnient where the size, shape and loc,atioii of ol)stacles are UllIi1lo\v11. nietliotl incliitlcs configuration space Voronoi diiigraiii[2] and potential field out i n oft-line iii:aiinc:r. 1-Iowever, this metliod is not suitable for ntivigiition i n coiiiples and dynamically changing environment where uiiliiiown obstacles niiiy be located on a priori planned path. Thus, this inc~thotl niust be followed by sensor-based local path planning, so ciilletl obstacle avoidance, carried out in on-line nianncr. Local pittli plxnning utilizes tlie information provided by sensor suc,li as ultrasonic sensor, vision, laser range finder, proximity sensor and binnper switch R.A.Brooks[4] applied tlie for(;c-fielti concept to obstacle avoidance problem for mobile robot equipped with ultrasonic, sensors whose readings are used to compute the I-esultant repulsive force. Borenstein and I<oren[5] proposed the vector field liistograin method for fast running iiioliile robot equipped with ultrasonic sensors. However, tlie Jiove inetliotls liave the shortcoming that it is difficult to find the force coefficients influencing on the velocity and direction of iiioliile robot in cluttered environment which c ~ n not be tlcsc r …