Hakan Temeltas

Attitude control of a quadrotor

This study includes altitude stabilization, hovering control any desired position and attitude control of quadrotor. Classically PD controller derived and applied to this system. Inverse dynamic control, feedback linearization control and sliding mode control methods have used to derive as nonlinear controllers. Linear and nonlinear control techniques applied to attitude control of this vehicle. Derived control methods have been performed using computer simulations and compared the results according to this study objective.

A Comparative Study of Three Inverse Kinematic Methods of Serial Industrial Robot Manipulators in the Screw Theory Framework

In this paper, we compare three inverse kinematic formulation methods for the serial industrial robot manipulators. All formulation methods are based on screw theory. Screw theory is an effective way to establish a global description of rigid body and avoids singularities due to the use of the local coordinates. In these three formulation methods, the first one is based on quaternion algebra, the second one is based on dual-quaternions, and the last one that is called exponential mapping method is based on matrix algebra. Compared with the matrix algebra, quaternion algebra based solutions are more computationally efficient and they need less storage area. The method which is based on dual-quaternion gives the most compact and computationally efficient solution. Paden-Kahan sub-problems are used to derive inverse kinematic solutions. 6-DOF industrial robot manipulators forward and inverse kinematic equations are derived using these formulation methods. Simulation and experimental results are given.

Fuzzy-differential evolution algorithm for planning time-optimal trajectories of a unicycle mobile robot on a predefined path

An evolutionary technique with a Fuzzy Inference System (FIS) is offered for planning time-optimal trajectories on a predefined Visibility Graph Method Dijkstra (VGM-D) path of a Nomad 200 mobile robot (MR). First of all, the segmented trajectory is generated by the VGM-D algorithm. Line and curve segments are the components of the trajectory. The number of intersections of the segmented VGM-D path determines the curve segments number. It is assumed that, at each curve segment, translation velocity v t is taken as constant. The Differential Evolution (DE) algorithm finds v t values of all the curve segments, which minimize the trajectory tracking time. Line segments lengths are used to calculate the constraints of the problem according to the Nomad 200s limitations on the translation velocity and acceleration/deceleration. The structures of the curve segments are modeled by FIS to decrease the DEs execution time. Another FIS model is used to define the upper bound of the translation velocities on the curve segments for the same purpose. Both FIS models are trained by the adapted-network-based fuzzy inference system (ANFIS). Experiments are successfully implemented on the Nomad 200 MR.

A novel approach to smooth trajectory planning of a mobile robot

This paper represents a novel smooth trajectory planning algorithm which uses the natural behavior model of a mobile robot (MR). The shortest path in the free configuration space is obtained by using the visibility graph method. It is modified according to dynamic constraints which are implicitly included in natural behavior of the mobile robot. The modified path becomes a smooth, easily trackable near time and distance optimal trajectory. For every point of it, translating/steering velocities and accelerations and reaching times are known. It is applicable to the real time dynamic configuration spaces, because of simplicity and low computational time.

3D Multi-Layered Normal Distribution Transform for Fast and Long Range Scan Matching

Simultaneously Localization and Mapping (SLAM) problem requires a sophisticated scan matching algorithm, in which two consecutive point clouds belonging to highly correlated scene are registered by finding the rigid body transformation parameters when an initial relative pose estimate is available. A well-known scan matching method is the Iterative Closest Point (ICP) algorithm, and the basis of the algorithm is the minimization of an error function that takes point correspondences into account. Another 3D scan matching method called Normal Distribution Transform (NDT) has several advantages over ICP such as the surface representation capability, accuracy, and data storage. On the other hand, the performance of the NDT is directly related to the size of the cell, and there is no proved way of choosing an optimum cell size. In this paper, a novel method called Multi-Layered Normal Distribution Transform (ML-NDT) using various cell sizes in a structured manner is introduced. In this structure a number of layers are used, where each layer contains different but regular cell sizes. In the conventional NDT, the score function is chosen as Gaussian probability function which is minimized iteratively by Newton optimization method. However, the ML-NDT score function is described as the Mahalanobis distance function, and in addition to Newton optimization method, Levenberg–Marquardt algorithm is also adapted to the proposed method for this score function. The performance of the proposed method is compared to the original NDT, and the effects of the optimization methods are discussed. Moreover, an important issue in a scan matching algorithms is the subsampling strategy since the point cloud contains huge amount of data which has a non-uniform distribution. Therefore, the application of a sampling strategy is a must for fast and robust scan matching. In the performance analysis, two sampling strategies are investigated which are random sampling and grid based sampling. The method is successfully applied to experimentally obtained datasets, and the results show that ML-NDT with grid based sampling provides a fast and long range scan matching capability.

Solution of inverse kinematic problem for serial robot using dual quaterninons and plücker coordinates

In this paper we present a new formulation method to solve kinematic problem of serial robot manipulators. In this method our major aims are to formulize inverse kinematic problem in a compact closed form and to avoid singularity problem. This formulation is based on screw theory with dual - quaternion. Compared with other methods, screw theory methods just establish two coordinates, and its geometrical meaning is obvious. We used dual-quaternion in plücker coordinates as a screw operator for compactness. 6R-DOF industrial robot manipulators forward and inverse kinematic equations are derived using this new formulation and simulation results are given.

Behavioral task processing for cognitive robots using artificial emotions

This paper presents an artificial emotional-cognitive system-based autonomous robot control architecture for a four-wheel driven and four-wheel steered mobile robot. Discrete stochastic state-space mathematical model is considered for behavioral and emotional transition processes of the autonomous mobile robot in the dynamic realistic environment. The term of cognitive mechanism system which is composed from rule base and reinforcement self-learning algorithm explain all of the deliberative events such as learning, reasoning and memory (rule spaces) of the autonomous mobile robot. The artificial cognitive model of autonomous robot control architecture has a dynamic associative memory including behavioral transition rules which are able to be learned for achieving multi-objective robot tasks. Motivation module of architecture has been considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors for long-term action planning. Also reinforcement self-learning and reasoning ability of artificial cognitive model and motivational gain effects of proposed architecture can be observed on the executing behavioral sequences during simulation. The posture and speed of the robot and the configurations, speeds and torques of the wheels and all deliberative and cognitive events can be observed from the simulation plant and virtual reality viewer. This study constitutes basis for the multi-goal robot tasks and artificial emotions and cognitive mechanism-based behavior generation experiments on a real mobile robot.

Solution of inverse kinematic problem for serial robot using quaterninons

A new inverse kinematic solution for serial robot manipulators is represented in this paper. Major aims of this paper are to obtain singularity avoiding inverse kinematic solutions and formulize kinematic problems in a compact closed form. Our solution method is based on screw theory and it uses quaternions as a screw motion operator. Screw theory methods based on line transformation. All screw motions are represented as a rotation about a line together with a translation along the line with respect to base frame. Thus screw theory methods do not suffer from singularities. Two quaterninos are used to represent screw motion. First one is for orientation and second one is for translation. Thus we formulize kinematic problems in a compact closed form. 6R-DOF industrial robot manipulators forward and inverse kinematic equations are derived using this new formulation and also it compared with D-H convention that is the most common method in robot kinematic.

A fast and robust scan matching algorithm based on ML-NDT and feature extraction

In this paper, we introduce a fast and robust scan matching method that combines the Multi-Layered Normal Distributions Transform (ML-NDT) and a feature extraction algorithm into a single framework. This is achieved by first applying the conventional NDT generation process to the reference scan, and the plane segments are extracted with the help of Random Sample Consensus (RANSAC) algorithm for the input scan. Thus, the proposed method provides three significant advantages with respect to conventional methods. The first one is that the proposed method is more robust to outliers since it is based on the matching of certain geometric structures. The second one is that the registration step is much faster because the number of points to be matched is very less with respect to all scanned points. Therefore, this process can be considered as a special sampling strategy. Finally, it is showed that the extracted features can also be used in feature based probabilistic SLAM methods such as Kalman Filters, Information Filters, and Particle Filters after applying merging procedure. Since the plane segments are already registered, the data association problem can be easily solved even without any odometry measurement. This can be considered as the most powerful part of the algorithm because data association problem in three dimensions is quite difficult problem. As a result, on the one hand, it is obtained a robust and fast scan matching; on the other hand, it is possible to extend the method for feature extraction algorithm in SLAM problems with a little extra computation. The method is applied to real experimental data and the results are quite affirmative.

Maneuvering Strategies for Four-Wheel Drive, Four-Wheel Steer Mobile Robots Using Curvatures Based on Weingarten-Maps

Using the method known as Weingarten map, instantaneous center of rotation (ICR) of a four-wheel-drive & four-wheel-steer (4WD/4WS) mechanism is obtained for a predefined path. Kinematical model is obtained based on multiple manipulators with constraints on a common base approach