A Comparison of Type-1 and Type-2 Fuzzy Logic Controllers in Robotics: A review

Most real world applications face high levels of uncertainties that can affect the operations of such applications. Hence, there is a need to develop different approaches that can handle the available uncertainties and reduce their effects on the given application. To date, Type-1 Fuzzy Logic Controllers (FLCs) have been applied with great success to many different real world applications. The traditional type-1 FLC which uses crisp type-1 fuzzy sets cannot handle high levels of uncertainties appropriately. Nevertheless it has been shown that a type-2 FLC using type-2 fuzzy sets can handle such uncertainties better and thus produce a better performance. As such, type-2 FLCs are considered to have the potential to overcome the limitations of type-1 FLCs and produce a new generation of fuzzy controllers with improved performance for many applications which require handling high levels of uncertainty. This paper will briefly introduce the interval type-2 FLC and its benefits. We will also present briefly some of the type-2 FLC real world applications

Development of Cognitive Capabilities in Humanoid Robots

Merged with duplicate record 10026.1/645 on 03.04.2017 by CS (TIS)Building intelligent systems with human level of competence is the ultimate grand challenge for science and technology in general, and especially for the computational intelligence community. Recent theories in autonomous cognitive systems have focused on the close integration (grounding) of communication with perception, categorisation and action. Cognitive systems are essential for integrated multi-platform systems that are capable of sensing and communicating. This thesis presents a cognitive system for a humanoid robot that integrates abilities such as object detection and recognition, which are merged with natural language understanding and refined motor controls. The work includes three studies; (1) the use of generic manipulation of objects using the NMFT algorithm, by successfully testing the extension of the NMFT to control robot behaviour; (2) a study of the development of a robotic simulator; (3) robotic simulation experiments showing that a humanoid robot is able to acquire complex behavioural, cognitive, and linguistic skills through individual and social learning. The robot is able to learn to handle and manipulate objects autonomously, to cooperate with human users, and to adapt its abilities to changes in internal and environmental conditions. The model and the experimental results reported in this thesis, emphasise the importance of embodied cognition, i.e. the humanoid robot's physical interaction between its body and the environment

Applying reinforcement learning in playing Robosoccer using the AIBO

"Robosoccer is a popular test bed for AI programs around the world in which AIBO entertainments robots take part in the middle sized soccer event. These robots need a variety of skills to perform in a semi-real environment like this. The three key challenges are manoeuvrability, image recognition and decision making skills. This research is focussed on the decision making skills ... The work focuses on whether reinforcement learning as a form of semi supervised learning can effectively contribute to the goal keeper's decision making when a shot is taken." -Master of Computing (by research

HYBRID FUZZY CONTROL AND ANT COLONY OPTIMIZATION BASED PATH PLANNING FOR WHEEL MOBILE ROBOT NAVIGATION

Wheeled Mobile Robot (WMR) is extremely important for active target tracking control and reactive obstacle avoidance in an unstructured environment. A WMR needs the best control performance an automatic path planning to maintain a very high level of accuracy. Therefore, the development of control strategies and path planning is very significant. Hence, research was carried out to investigate the control and path planning issues of WMR in dynamic environment. Several controllers such as conventional controller Proportional (P), Integral (I), Derivative (D) and Fuzzy Logic controller were investigated. A Hybrid Controller for differential WMR was proposed. Various aspects of the research on WMR such as kinematics model, conventional controller, fuzzy controller and hybrid controller were discussed. Overall it was found that on average the Hybrid Controller gives the best performance with 5.5s, 5.4s and 11s for target of 10x 10y, 30x10y and 60x20y respectively

Evolutionary, developmental neural networks for robust robotic control

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 136-143).The use of artificial evolution to synthesize controllers for physical robots is still in its infancy. Most applications are on very simple robots in artificial environments, and even these examples struggle to span the "reality gap," a name given to the difference between the performance of a simulated robot and the performance of a.real robot using the same evolved controller. This dissertation describes three methods for improving the use of artificial evolution as a tool for generating controllers for physical robots. First, the evolutionary process must incorporate testing on the physical robot. Second, repeated structure on the robot should be exploited. Finally, prior knowledge about the robot and task should be meaningfully incorporated. The impact of these three methods, both in simulation and on physical robots, is demonstrated, quantified, and compared to hand-designed controllers.by Bryan Adams.Ph.D

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

HYBRID FUZZY CONTROL AND ANT COLONY OPTIMIZATION BASED PATH PLANNING FOR WHEEL MOBILE ROBOT NAVIGATION

Wheeled Mobile Robot (WMR) is extremely important for active target tracking control and reactive obstacle avoidance in an unstructured environment. A WMR needs the best control performance an automatic path planning to maintain a very high level of accuracy. Therefore, the development of control strategies and path planning is very significant. Hence, research was carried out to investigate the control and path planning issues of WMR in dynamic environment. Several controllers such as conventional controller Proportional (P), Integral (I), Derivative (D) and Fuzzy Logic controller were investigated. A Hybrid Controller for differential WMR was proposed. Various aspects of the research on WMR such as kinematics model, conventional controller, fuzzy controller and hybrid controller were discussed. Overall it was found that on average the Hybrid Controller gives the best performance with 5.5s, 5.4s and 11s for target of 10x 10y, 30x10y and 60x20y respectively

Evolving robot sub-behaviour modules using Gene Expression Programming

Many approaches to AI in robotics use a multi-layered approach to determine levels of behaviour from basic operations to goal-directed behaviour, the most well-known of which is the subsumption architecture. In this paper, the performances of the unigenic gene expression programming (ugGEP) and multigenic GEP (mgGEP) in evolving robot controllers for a wall following robot is analysed. Additionally, the paper introduces Regulatory Multigenic Gene Expression Programming (RMGEP), a new evolutionary technique that can be utilised to automatically evolve modularity in robot behaviour. The proposed technique extends the mgGEP algorithm, by incorporating a regulatory gene as part of the GEP chromosome. The regulatory gene, just as in systems biology, determines which of the genes in the chromosome to express and therefore how the controller solves the problem. In the initial experiments, the proposed algorithm is implemented for a robot wall following problem and the results compared to that of ugGEP and mgGEP. In addition to the wall following behaviour, a robot foraging behaviour is implemented with the aim of investigating whether the position of a speci c module (sub-expression tree (ET)) in the overall ET is of importance when coding for a problem.http://link.springer.com/journal/107102016-05-30hb201

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion