Modeling and Simulation Longitudinal Mobile Robotic with Rough Terrain and Ascent Angle Disturbance

Model mobile robot that used to this simulation is type car like vehicle steering. Mobile robot type car like vehicle steering is mobile robot that move using force of rear wheel and front rear of mobile robot functions as steering to control direction of mobile robot. The dynamic nonlinear model mobile robot is implemented to view influence disturbance of mobile robot to longitudinal direction mobile robot that used to planetary exploration in rough terrain. The model that used to simulation is nonlinear multivariable MIMO with 5 input and 7 output. The simulation has done by using Simulink of Matlab. The simulations were carried out by giving 4 conditions, namely without disturbance, with an incline angle of 30 (0.5236 rad), with a rough terrain angle of 28.6479 (+0.5 rad), and a combination of 30 incline angle and 28.6479 rough terrain angle. The simulation results with 3 mobile robots show accurate results

Formation control of nonholonomic mobile robots: the virtual structure approach

PhDIn recent years, there has been a considerable growth in applications of multi-robot systems as opposed to single-robot systems. This thesis presents our proposed solutions to a formation control problem in which mobile robots are required to create a desired formation shape and track a desired trajectory as a whole. In the first instance, we study the formation control problem for unicycle mobile robots. We propose two control algorithms based on a cascaded approach: one based on a kinematic model of a robot and the other based on a dynamic model. We also propose a saturated controller in which actuator limitations are explicitly accounted for. To demonstrate how the control algorithms work, we present an extensive simulation and experimental study. Thereafter we move on to formation control algorithms in which the coordination error is explicitly defined. Thus, we are able to give conditions for robots keeping their desired formation shape without necessarily tracking the desired trajectory. We also introduce a controller in which both trajectory tracking and formation shape maintenance are achieved as well as a saturated algorithm. We validate the applicability of the introduced controllers in simulations and experiments. Lastly, we study the formation control problem for car-like robots. In this case we develop a controller using the backstepping technique. We give conditions for robots keeping their desired formation shape while failing to track their desired trajectories and present simulation results to demonstrate the applicability of the proposed controlle

Development of autonomous features and indoor localization techniques for car-like mobile robots

Intelligente autonome Navigation ist ein wesentliches Problem in der mobilen Robotik. Für einen modellbasierten Fahrzeug-ähnlichen mobilen Roboter ist das Steuerungskonzept ähnlich wie beim Auto. Autonome Feature erlauben Robotern eigene Bewegungen zu kontrollieren ohne menschliche Interaktion. Drei autonome Feature werden in diese Arbeit behandelt: Hindernisvermeidung, 180° Drehung in einem schmalen Flur und Pfadverfolgung. Weil die Hindernispositionen unbekannt sind, erfordert die Strategie nicht nur Hindernisvermeidung, sondern auch Bahnplanung und Roboterlokalisierung. Die Roboterlokalisierung kann in relative und absolute Lokalisierungen unterteilt werden. In dieser Arbeit soll die Entwicklung der modellbasierten relativen Lokalisierungstechnik und der absoluten Lokalisierung durch Landmarken untersucht werden. Die Entwicklung der modellbasierten relativen Lokalisierung wird durch ein nichtlineares dynamisches Automodell mit nachfolgendem Kalman Filter erreicht. Die Integration der Sensordaten des Entfernungsmessers, Trägheitsgyroskop-Sensors und der Kompass-Sensoren durch den Kalman Filter ermöglicht die Analyse der Leistung der drei Positionierungsmethoden; durch differentiellen Antrieb, Gyroskops- und Kompass-Abschätzung. Die absolute Lokalisierung wird durch den Einsatz einer 3D-Kamera und 3D-Landmarken erreicht und wird im Folgen der Positionskalibrierung genant. Drei Teile der Positionskalibrierung werden entwickelt: Das Design der Landmarken, die Erkennung der Landmarken sowie die Voraussage und die Aktualisierung der Roboterposition. Schließlich wird die Verbesserung der Auflösung der Positionskalibrierungstechnik durch 2D und 3D Bilder untersucht.Intelligent autonomous navigation in a large-scale and unknown indoor environment is an important problem in mobile robotics. For a car-like mobile robot with a racing car platform, the movement control concept is similar to that of a car. The autonomous features enable robots to control own motion without human interference. Three autonomous features are addressed in this thesis; obstacle avoidance, doing 180° turns in a narrow corridor, and path following control. Since the obstacle positions are not known beforehand, the strategy requires not only the obstacle avoidance but also trajectory generation and robot localization. The robot localization can be broken down into relative and absolute localization. This thesis addresses the development of the model-based relative localization technique and the landmark-based absolute localization technique. The model-based relative localization is applied by the non-linear dynamic car model to the Kalman filter. The study of integrating sensor data from odometer, gyroscope and compass for the position and heading estimators provides a discussion of the performance of three localization methods; differential drive, gyroscope estimator, and compass estimator. The landmark-based absolute localization is applied by using the 3D camera and the 3D artificial landmark and is called the position calibration. Three parts of the position calibration are developed: The design of landmarks, the landmark recognition, and the robot position prediction and update. Lastly, the improvement for the resolution of the position calibration by using 2D and 3D images is studied

A layered fuzzy logic controller for nonholonomic car-like robot

A system for real time navigation of a nonholonomic car-like robot in a dynamic environment consists of two layers is described: a Sugeno-type fuzzy motion planner; and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including right and left views to identify the next step to the goal. A Sugeno-type fuzzy motion planner of four inputs one output is introduced to give a clear direction to the robot controller. The second stage is a modified proportional navigation based fuzzy controller based on the proportional navigation guidance law and able to optimize the robot's behavior in real time, i.e. to avoid stationary and moving obstacles in its local environment obeying kinematics constraints. The system has an intelligent combination of two behaviors to cope with obstacle avoidance as well as approaching a target using a proportional navigation path. The system was simulated and tested on different environments with various obstacle distributions. The simulation reveals that the system gives good results for various simple environments

Uncalibrated Dynamic Mechanical System Controller

An apparatus and method for enabling an uncalibrated, model independent controller for a mechanical system using a dynamic quasi-Newton algorithm which incorporates velocity components of any moving system parameter(s) is provided. In the preferred embodiment, tracking of a moving target by a robot having multiple degrees of freedom is achieved using an uncalibrated model independent visual servo control. Model independent visual servo control is defined as using visual feedback to control a robot's servomotors without a precisely calibrated kinematic robot model or camera model. A processor updates a Jacobian and a controller provides control signals such that the robot's end effector is directed to a desired location relative to a target on a workpiece.Georgia Tech Research Corporatio