A review on robot motion planning approaches

The ability of a robot to plan its own motion seems pivotal to its autonomy, and that is why the motion planning has become part and parcel of modern intelligent robotics. In this paper, about 100 research are reviewed and briefly described to identify and classify the amount of the existing work for each motion planning approach. Meanwhile, around 200 research were used to determine the percentage of the application of each approach. The paper includes comparative tables and charts showing the application frequency of each approach in the last 30 years. Finally, some open areas and challenging topics are presented based on the reviewed papers

Optimization approaches for robot trajectory planning

[EN] The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof), the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.Llopis-Albert, C.; Rubio, F.; Valero, F. (2018). Optimization approaches for robot trajectory planning. Multidisciplinary Journal for Education, Social and Technological Sciences. 5(1):1-16. doi:10.4995/muse.2018.9867SWORD1165

Complex Adaptive Systems & Urban Morphogenesis:

This thesis looks at how cities operate as Complex Adaptive Systems (CAS). It focuses on how certain characteristics of urban form can support an urban environment's capacity to self-organize, enabling emergent features to appear that, while unplanned, remain highly functional. The research is predicated on the notion that CAS processes operate across diverse domains: that they are ‘generalized' or ‘universal'. The goal of the dissertation is then to determine how such generalized principles might ‘play out' within the urban fabric. The main thrust of the work is to unpack how elements of the urban fabric might be considered as elements of a complex system and then identify how one might design these elements in a more deliberate manner, such that they hold a greater embedded capacity to respond to changing urban forces. The research is further predicated on the notion that, while such responses are both imbricated with, and stewarded by human actors, the specificities of the material characteristics themselves matter. Some forms of material environments hold greater intrinsic physical capacities (or affordances) to enact the kinds of dynamic processes observed in complex systems than others (and can, therefore, be designed with these affordances in mind). The primary research question is thus:   What physical and morphological conditions need to be in place within an urban environment in order for Complex Adaptive Systems dynamics arise - such that the physical components (or ‘building blocks') of the urban environment have an enhanced capacity to discover functional configurations in space and time as a response to unfolding contextual conditions?   To answer this question, the dissertation unfolds in a series of parts. It begins by attempting to distill the fundamental dynamics of a Complex Adaptive System. It does so by means of an extensive literature review that examines a variety of highly cited ‘defining principles' or ‘key attributes' of CAS. These are cross-referenced so as to extract common features and distilled down into six major principles that are considered as the generalized features of any complex system, regardless of domain. In addition, this section considers previous urban research that engages complexity principles in order to better position the distinctive perspective of this thesis. This rests primarily on the dissertation's focus on complex urban processes that occur by means of materially enabled in situ processes. Such processes have, it is argued, remained largely under-theorized. The opening section presents introductory examples of what might be meant by a ‘materially enabling' environment.   The core section of the research then undertakes a more detailed unpacking of how complex processes can be understood as having a morphological dimension. This section begins by discussing, in broad terms, the potential ‘phase space' of a physical environment and how this can be expanded or limited according to a variety of factors. Drawing insights from related inquiries in the field of Evolutionary Economic Geography, the research argues that, while emergent capacity is often explored in social, economic, or political terms, it is under-theorized in terms of the concrete physical sub-strata that can also act to ‘carry' or ‘moor' CAS dynamics. This theme is advanced in the next article, where a general framework for speaking about CAS within urban environments is introduced. This framework borrows from the terms for ‘imageability' that were popularized by Kevin Lynch: paths, edges, districts, landmarks, and nodes. These terms are typically associated with physical or ‘object-like features' of the urban environment – that is to say, their image. The terminology is then co-opted such that it makes reference not simply to physical attributes, but rather to the complex processes these attributes enable. To advance this argument, the article contrasts the static and ‘imageable' qualities of New Urbanism projects with the ‘unfolding' and dynamic qualities of complex systems - critiquing NU proponents as failing to appreciate the underlying forces that generate the environments they wish to emulate. Following this, the efficacy of the re-purposed ‘Lynchian' framework is tested using the case study of Istanbul's Grand Bazaar. Here, specific elements of the Bazaar's urban fabric are positioned as holding material agency that enables particular emergent spatial phenomena to manifest. In addition, comparisons are drawn between physical dynamics unfolding within the Bazaar's morphological setting (leading to emergent merchant districts) and parallel dynamics explored within Evolutionary Economic Geography).   The last section of the research extends this research to consider digitally augmented urban elements that hold an enhanced ability to receive and convey information. A series of speculative thought-experiments highlight how augmented urban entities could employ CAS dynamics to ‘solve for' different kinds of urban optimization scenarios, leading these material entities to self-organize (with their users) and discover fit regimes. The final paper flips the perspective, considering how, not only material agency, but also human agency is being augmented by new information processing technologies (smartphones), and how this can lead to new dances of agency that in turn generate novel emergent outcomes.   The dissertation is based on a compilation of articles that have, for the most part, been published in academic journals and all the research has been presented at peer-reviewed academic conferences. An introduction, conclusion, and explanatory transitions between sections are provided in order to clarify the narrative thread between the sections and the articles. Finally, a brief ‘coda' on the spatial dynamics afforded by Turkish Tea Gardens is offered

Design of an UAV swarm

This master thesis tries to give an overview on the general aspects involved in the design of an UAV swarm. UAV swarms are continuoulsy gaining popularity amongst researchers and UAV manufacturers, since they allow greater success rates in task accomplishing with reduced times. Appart from this, multiple UAVs cooperating between them opens a new field of missions that can only be carried in this way. All the topics explained within this master thesis will explain all the agents involved in the design of an UAV swarm, from the communication protocols between them, navigation and trajectory analysis and task allocation

Synthesis of autonomous controllers in mobile robotics through bio-inspired computing

Orientador: Fernando Jose Von ZubenAcompanha CD-ROMTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: Novas técnicas de navegação autônoma de robôs móveis visam suprir a crescente demanda pelo emprego de robôs em diversos setores da sociedade e junto a uma ampla gama de tarefas. Os desafios envolvidos no desenvolvimento do sistema que controla o robô permitem afirmar que a inteligência embarcada em robôs atuais ainda encontra-se em um nível incipiente e limitado. Neste trabalho, cinco frentes de pesquisa complementares são propostas visando estudar, teórica e praticamente, aspectos fundamentais de projeto e implementação de controladores autônomos inteligentes para robótica móvel. Metodologias de computação bio-inspirada e de robótica evolutiva provêem os conceitos e ferramentas que fundamentam as cinco propostas, as quais são validadas com base em sistemas de navegação concebidos e aplicados a problemas relevantes da área. Uma série de simulações computacionais em ambientes virtuais e experimentos com robôs reais é realizada, permitindo medir o alcance das contribuições e apontar as principais frentes de atuação que se abrem como perspectivas futuras da pesquisa.Abstract: Novel techniques for autonomous robot navigation aim at fulfilling the growing demand for mobile robots in multiple segments of society and in a plethora of tasks. The challenges involved in developing the system which controls the robot allow to say that the intelligence embedded in the current robots is found to be still incipient and limited. In this work, five complementary research fronts are proposed intending to study, theoretical and practically, aspects which are fundamental to the design and implementation of intelligent autonomous controllers for mobile robotics. Bio-inspired computing and evolutionary robotics methodologies provide the concepts and tools underlying the five proposals, which are validated through navigation systems devised and applied to important problems. Numerous real robot experiments as well as computational simulations taking place in virtual environments are carried out, allowing for the evaluation of contributions and also the discussion of future possibilities.DoutoradoEngenharia de ComputaçãoDoutor em Engenharia Elétric

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Intuition: The Experience of Formal Research

A new concept of Intuition, the Deep Unconscious is considered on the basis of the Paradigm of limiting generalizations. The book describes a high-level sketch. The results of the study can be used in education, economics, medicine, artificial intelligence, and the management of complex systems of various natures