Decision tree learning for intelligent mobile robot navigation

The replication of human intelligence, learning and reasoning by means of computer algorithms is termed Artificial Intelligence (Al) and the interaction of such algorithms with the physical world can be achieved using robotics. The work described in this thesis investigates the applications of concept learning (an approach which takes its inspiration from biological motivations and from survival instincts in particular) to robot control and path planning. The methodology of concept learning has been applied using learning decision trees (DTs) which induce domain knowledge from a finite set of training vectors which in turn describe systematically a physical entity and are used to train a robot to learn new concepts and to adapt its behaviour. To achieve behaviour learning, this work introduces the novel approach of hierarchical learning and knowledge decomposition to the frame of the reactive robot architecture. Following the analogy with survival instincts, the robot is first taught how to survive in very simple and homogeneous environments, namely a world without any disturbances or any kind of "hostility". Once this simple behaviour, named a primitive, has been established, the robot is trained to adapt new knowledge to cope with increasingly complex environments by adding further worlds to its existing knowledge. The repertoire of the robot behaviours in the form of symbolic knowledge is retained in a hierarchy of clustered decision trees (DTs) accommodating a number of primitives. To classify robot perceptions, control rules are synthesised using symbolic knowledge derived from searching the hierarchy of DTs. A second novel concept is introduced, namely that of multi-dimensional fuzzy associative memories (MDFAMs). These are clustered fuzzy decision trees (FDTs) which are trained locally and accommodate specific perceptual knowledge. Fuzzy logic is incorporated to deal with inherent noise in sensory data and to merge conflicting behaviours of the DTs. In this thesis, the feasibility of the developed techniques is illustrated in the robot applications, their benefits and drawbacks are discussed

Imprecise knowledge based design and development of titanium alloys for prosthetic applications

Imprecise knowledge on the composition–processing–microstructure–property correlation of titanium alloys combined with experimental data are used for developing rule based models for predicting the strength and elastic modulus of titanium alloys. The developed models are used for designing alloys suitable for orthopedic and dental applications. Reduced Space Searching Algorithm is employed for the multi-objective optimization to find composition, processing and microstructure of titanium alloys suitable for orthopedic applications. The conflicting requirements attributes of the alloys for this particular purpose are high strength with low elastic modulus, along with adequate biocompatibility and low costs. The ‘Pareto’ solutions developed through multi-objective optimization show that the preferred compositions for the fulfilling the above objectives lead to β or near β-alloys. The concept of decision making employed on the solutions leads to some compositions, which should provide better combination of the required attributes. The experimental development of some of the alloys has been carried out as guided by the model-based design methodology presented in this research. Primary characterizations of the alloys show encouraging results in terms of the mechanical properties

AI Methods in Algorithmic Composition: A Comprehensive Survey

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC- 5123) from the Consejería de Innovación y Ciencia de Andalucía

Research on key techniques of flexible workflow based approach to supporting dynamic engineering design process

Error on title page - correct year of award is 2015 not 2013.Engineering design process (EDP) is a highly dynamic and creative process, and the capability in managing an EDP is considered as a major differentiating factor between competing enterprises. The most important prerequisite to establish an engineering design process excellence is a proper management of all the design process activities and the associated information. The most important impact in recent years on the EDP and on the activities of designers has come from computer-based data processing. Workflow, the automation of a business processes in whole or part, is a useful tool for modelling and managing a business process which can be reprensented by a workflow model (computerized process definition). By considering the dynamic characteristics of EDP, an EDP management system must be flexible enough to support the creative and dynamic EDP. After the introduction of engineering design process and its new trend, as well as flexible workflow technology, reviews of both engineering design process and its supporting flexible workflow technology shows that there is a need for a holistic framework to automate and coordinate design activities in the creative and dynamic EDP, and the flexible workflow technology should also be improved comprehensively in flexibility and intelligence in order to support better engineering design management. By introducing the relations between the EDP and flexible workflow, a virtual workflow and an autonomic flexible workflow built upon autonomic computing is investigated, and an innovative engineering design process management framework based on multi-autonomic objects flexible workflow is proposed. For the flexible workflow modelling in the framework, a dynamic instance-based flexible workflow modelling method is proposed for multi-autonomic objects flexible workflow. In order to improve the intelligence of flexible workflow, after examining the principle of flexible workflow intelligence in flexible workflow, a new flexible workflow autonomic object intelligence algorithm based on both extended Mamdani fuzzy reasoning and neural network is proposed, weighted fuzzy reasoning algorithm, as well as precise and fuzzy hybrid knowledge reasoning algorithm is designed; a bionic flexible workflow adaptation algorithm is proposed to improve the intelligence of autonomic object flexible workflow further. According to the characteristic of EDP, such as cross-enterprises and geographical distribution, and in order to realize the flexible execution of distributed flexible workflow engine, a distributed flexible workflow engine architecture based on web service is proposed and a flexible workflow model description method based on extended WSDL (Web Service Description Language) and BPEL4WS (Business Process Execution Language for Web Services) is proposed. A flexible workflow prototype system supporting engineering design process is implemented according to the proposed EDP management framework in Microsoft VS.Net 2005 environment. The framework is demonstrated by the application in an EDP of a MTO company, and it shows that the proposed framework can support the creative and dynamic process in an efficient way. Finally, the strengths and weakness of the framework as well as the prototype system is discussed based on the results of the evaluation, and the proposed areas of future work are given.Engineering design process (EDP) is a highly dynamic and creative process, and the capability in managing an EDP is considered as a major differentiating factor between competing enterprises. The most important prerequisite to establish an engineering design process excellence is a proper management of all the design process activities and the associated information. The most important impact in recent years on the EDP and on the activities of designers has come from computer-based data processing. Workflow, the automation of a business processes in whole or part, is a useful tool for modelling and managing a business process which can be reprensented by a workflow model (computerized process definition). By considering the dynamic characteristics of EDP, an EDP management system must be flexible enough to support the creative and dynamic EDP. After the introduction of engineering design process and its new trend, as well as flexible workflow technology, reviews of both engineering design process and its supporting flexible workflow technology shows that there is a need for a holistic framework to automate and coordinate design activities in the creative and dynamic EDP, and the flexible workflow technology should also be improved comprehensively in flexibility and intelligence in order to support better engineering design management. By introducing the relations between the EDP and flexible workflow, a virtual workflow and an autonomic flexible workflow built upon autonomic computing is investigated, and an innovative engineering design process management framework based on multi-autonomic objects flexible workflow is proposed. For the flexible workflow modelling in the framework, a dynamic instance-based flexible workflow modelling method is proposed for multi-autonomic objects flexible workflow. In order to improve the intelligence of flexible workflow, after examining the principle of flexible workflow intelligence in flexible workflow, a new flexible workflow autonomic object intelligence algorithm based on both extended Mamdani fuzzy reasoning and neural network is proposed, weighted fuzzy reasoning algorithm, as well as precise and fuzzy hybrid knowledge reasoning algorithm is designed; a bionic flexible workflow adaptation algorithm is proposed to improve the intelligence of autonomic object flexible workflow further. According to the characteristic of EDP, such as cross-enterprises and geographical distribution, and in order to realize the flexible execution of distributed flexible workflow engine, a distributed flexible workflow engine architecture based on web service is proposed and a flexible workflow model description method based on extended WSDL (Web Service Description Language) and BPEL4WS (Business Process Execution Language for Web Services) is proposed. A flexible workflow prototype system supporting engineering design process is implemented according to the proposed EDP management framework in Microsoft VS.Net 2005 environment. The framework is demonstrated by the application in an EDP of a MTO company, and it shows that the proposed framework can support the creative and dynamic process in an efficient way. Finally, the strengths and weakness of the framework as well as the prototype system is discussed based on the results of the evaluation, and the proposed areas of future work are given

Computational composition strategies in audiovisual laptop performance

We live in a cultural environment in which computer based musical performances have become ubiquitous. Particularly the use of laptops as instruments is a thriving practice in many genres and subcultures. The opportunity to command the most intricate level of control on the smallest of time scales in music composition and computer graphics introduces a number of complexities and dilemmas for the performer working with algorithms. Writing computer code to create audiovisuals offers abundant opportunities for discovering new ways of expression in live performance while simultaneously introducing challenges and presenting the user with difficult choices. There are a host of computational strategies that can be employed in live situations to assist the performer, including artificially intelligent performance agents who operate according to predefined algorithmic rules. This thesis describes four software systems for real time multimodal improvisation and composition in which a number of computational strategies for audiovisual laptop performances is explored and which were used in creation of a portfolio of accompanying audiovisual compositions

Measurements, Models, Systems and Design

531 s.

Adaptive and learning-based formation control of swarm robots

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation