DYNAMICS BASED CONTROL OF A SKID STEERING MOBILE ROBOT

In this paper, development of a reduced order, augmented dynamics-drive model that combines both the dynamics and drive subsystems of the skid steering mobile robot (SSMR) is presented. A Linear Quadratic Regulator (LQR) control algorithm with feed-forward compensation of the disturbances part included in the reduced order augmented dynamics-drive model is designed. The proposed controller has many advantages such as its simplicity in terms of design and implementation in comparison with complex nonlinear control schemes that are usually designed for this system. Moreover, the good performance is also provided by the controller for the SSMR comparable with a nonlinear controller based on the inverse dynamics which depends on the availability of an accurate model describing the system. Simulation results illustrate the effectiveness and enhancement provided by the proposed controller

False Data Injection of a Robotic Navigation System: Concepts and Simulations

Today, robotic vehicles (RV) play an essential role in both modern industry and the military. More and more RVs become autonomously operated and are prone to cyber-attacks of their embedded control systems. These attacks can be detected and prevented with the appropriate tools but can also be almost undetectable if executed correctly. In this work, a type of cyber-attack, namely false data injection is performed to spoof an Extended Kalman Filter (EKF) and a conventional fault detection mechanism is used to attempt to identify the attack. A two-wheeled differentially steered robotic vehicle based on the TurtleBot 3 ‘Burger’ is simulated in MATLAB. The navigation system is attacked by injecting false data into the measurement device - a LiDAR sensor. The false data injection alters the range and bearing measurements and aims to change the measured heading angle of the robot and alter its trajectory. The attack is then tuned to make it undetectable by the implemented counter measures. In this thesis, it is demonstrated that false data injection can be executed in such a way that it is almost impossible for the fault detection mechanism to perceive an attack. The simulations have shown that the key to stealth is to inject the false data in a slow and steady manner to deceive the EKF by steering its output. The deviation introduced is mostly unnoticeable as long as it is in the same order of magnitude of the noise, which is part of the robot’s navigation system. In contrast, sudden and severe changes of measurement data are detected easily by the EKF and the fault detection mechanism.Universitaet der Bundeswehr Muenchen Fakultaet fuer Luft- und Raumfahrttechnik Institute for Space Technology and Applications Werner-Heisenberg-Weg 39 85579 Neubiberg, GermanyGerman Armed ForcesApproved for public release; distribution is unlimited

Wheelchair lifter

Basically, a wheelchair stair lift is a motorized, meaning by carrying a person seated in a wheelchair up and down stairs. A wheelchair lift, also known as a platform lift, or vertical platform lift is a fully powered device designed to raise a wheelchair and its occupant in order to overcome a step or similar vertical barrier (Figure 8.1). Wheelchair lifts can be installed in homes or businesses and are often added to both private and public vehicles in order to meet accessibility requirements laid out by the Americans with Disabilities Act of 1990 (ADA). These mobility devices are often installed in homes as an alternative to a stair lift, which only transport a passenger and not his/her wheelchair or mobility scooter. It is installed over the stairs in such a way that the stairs can still be used in the usual fashion. There is no need of breaking down or reconstructing the existing building

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

Adaptive Steering and Trajectory Control of Wheeled Mobile Robots for Autonomous Navigation

This chapter presents a new reactive navigation algorithm for a wheeled mobile robot (WMR) with a differential drive mechanism moving in unknown environments [1]. The mobile robot is controlled to travel to a predefined goal position safely and efficiently without any prior map of the environment. The navigation is achieved by modulating the steering angle and turning radius. To avoid obstacles while seeking the goal position, the dimensions and shape of the robot are incorporated to determine the set of all possible collision-free steering angles. The algorithm then selects the optimum steering angle candidate to contour the obstacle. Simulation and experimental results on a WMR prototype are used to validate the proposed algorithms