Cloud Robotics

Cloud robotics is an emerging field which enables the web enabled robots to access the cloud services on the fly. Cloud Robotics was born by merging robotics with the cloud technologies. The robot intelligence is no more in the robot itself but remotely executed on the cloud. Robot acts as thin-client. There are several frameworks already in development and still growing. With the help of high speed networks using 4G/5G technologies, offloading of computation and storage in cloud is the further step in robotic evolution. This chapter deals the exploration of cloud robotics with its architecture, applications and existing frameworks. Also, existing research carried out is summarized in this chapter. The future challenges are discussed to foresee the opportunities in cloud robotics. It aims for the complete study on how robots leverages the cloud computing.

Advances in Cybernetics Provide a Foundation for the Future

Interest in cybernetics declined in North America from the mid 1970s to 2010, as measured by the number of journal articles by North American authors, but increased in Europe and Asia. Since 2010 the number of books on cybernetics in English has increased significantly. Whereas the social science disciplines create descriptions based on either ideas, groups, events or variables, cybernetics provides a multi-disciplinary theory of social change that uses all four types of descriptions. Cyberneticians use models with three structures – regulation, self-organization and reflexivity. These models can be used to describe any systemic problem. Furthermore, cybernetics adds a third approach to philosophy of science. In addition to a normative or a sociological approach to knowledge, cybernetics adds a biological approach. One implication of the biological approach is additional emphasis on ethics.

Our Cyber-Systemic Future

How can systems and cybernetics address the issues arising from an increasingly complex world, that often is beyond our traditional response capabilities? The author argues that to address such complexity we require imaginative propositions and innovative behaviours to see and address the inherently systemic nature of our world, which too often is fragmented by policies driven by non-systemic models. Socially, we live in a world experiencing systemic deficit; our policy responses are often fragmented, but even if they are not, socially designed responses fail to recognise environmental constraints and produce innovative allocations of requisite resources to make them happen. The author argues that conversational spaces, such as those offered by the World Organisation of Systems and Cybernetics [WOSC], and other cybersystemic associations, should help dealing with fragmentation and resources allocation; he sees these conversations as necessary contributions to redress our systemic deficit. Systemic thinking should help in visualising social situations as wholes, thus reducing the chances of dysfunctional fragmentation and cybernetics should help us understanding processes of dynamic stability in the interactions among and between people, institutions, and organizations. Systemic thinking should give us methodological tools; cybernetics should give us communication tools to manage the complexity of situations from the local to the global. The paper discusses complexity management strategies, emphasising the need to deal operationally with this complexity rather than cognitively; operational complexity is orders of magnitude larger than cognitive complexity. The paper ends up with an illustration of these complexity management strategies in higher education.

A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.

Delivering Value in Procurement With Robotic Cognitive Automation (RCA) Services

Organizations are applying digitalization to increasing amounts of different organizational processes. The procurement sector is also changing and actively seeking better ways to enhance performance such as the automation of workflow processes, for example, robotic process automation (RPA). To meet this clear demand, the automation of workflow processes in organizations has been a rising trend during the past few years. The author analyzes the potential of RPA along with the cognitive technologies robotic cognitive automation-based (RCA) value creation through knowledge work digitalization in the procurement sector.

Can We Induce a Cognitive Representation of a Prosthetic Arm by Means of Crossmodal Stimuli?

The ownership feeling of our body occurs mainly due to feedback responses in real-time from environment stimuli to our own body. These constant feedbacks induce a neuronal arrangement, generating a representative map and, consequently, an ownership and unity feeling, named as a body schema. Although there is a relative well knowing of the sensorial mapping about each part of our body, there are still several gaps about how the integration of all this representation is indeed accomplished. Many researchers have shown high rates of prosthesis non-acceptance due to different reasons. Here, the authors discuss an experimental protocol to induce optimally the ownership feeling associated with upper limb prosthesis, by means of a crossmodal vibro-tactile stimulation over the individual's body. The main hypothesis is that through this procedure the participant will extend their proprioception and achieve an ownership feeling of the prosthesis.

Fake Empathy and Human-Robot Interaction (HRI)

Empathy is a basic emotion trigger for human beings, especially while regulating social relationships and behaviour. The main challenge of this paper is study whether people's empathic reactions towards robots change depending on previous information given to human about the robot before the interaction. The use of false data about robot skills creates different levels of what we call ‘fake empathy'. This study performs an experiment in WOZ environment in which different subjects (n=17) interacting with the same robot while they believe that the robot is a different robot, up to three versions. Each robot scenario provides a different ‘humanoid' description, and out hypothesis is that the more human-like looks the robot, the more empathically can be the human responses. Results were obtained from questionnaires and multi- angle video recordings. Positive results reinforce the strength of our hypothesis, although we recommend a new and bigger and then more robust experiment.

A PhysX-Based Framework to Develop Rehabilitation Systems Using Haptics and Virtual Reality

The use of Virtual Reality (VR), in combination with haptic devices (i.e. robotic manipulators capable of generating forces that stimulate the tactile and/or proprioceptive system of the users) is becoming very popular in the field of rehabilitation. As matter of fact, different rehabilitation requirements, related to various pathologies, are usually addressed by developing specialized haptic devices, together with specific VR worlds and exercises to be performed within. This, in turn, usually brings a tremendous effort when new exercises must be designed and/or new haptic devices, with their mechanical model and hardware (HW) interfaces, must be embedded into an existing environment. To cope with the required flexibility and adaptability, while reducing the development cost, we propose in this chapter a software framework that aims at reducing the development time and cost of new VR+haptics systems, through the use of well-known software design patterns (Model/View/Controller, Strategy, Observer) and freely available technologies (XML, PhysX).

Autonomic Computing in a Biomimetic Algorithm for Robots Dedicated to Rehabilitation of Ankle

Human mobility is the key element of everyday life, its reduction or loss deeply affects daily activities. In assisted rehabilitation, robotic devices have focuses on the biomechanics of motor control. However, biomechanics does not study the neurological and physiological processes related to normal gait. Biomimetics combined with biomechanics, can generate a more efficient stimulation of the motor cortex and the locomotor system. The highest efficiency obtained through torque generation models, based on the physiological response of muscles and bones to reaction forces, together with control techniques based on autonomic computation. An autonomic control algorithm has a self-adjusting behaviour, ensuring patient safety and robot operation without the continuous monitoring of the physiotherapist. Thus, this work will identify the elements that characterize the physiological stimuli related to normal human gait, focusing on the ankle joint, aiming the development of biomimetic algorithms for robots for rehabilitation of the lower limbs.

Localization and Mapping for Indoor Navigation

Mapping and exploration for the purpose of navigation in unknown or partially unknown environments is a challenging problem, especially in indoor environments where GPS signals can't give the required accuracy. This chapter discusses the main aspects for designing a Simultaneous Localization and Mapping (SLAM) system architecture with the ability to function in situations where map information or current positions are initially unknown or partially unknown and where environment modifications are possible. Achieving this capability makes these systems significantly more autonomous and ideal for a large range of applications, especially indoor navigation for humans and for robotic missions. This chapter surveys the existing algorithms and technologies used for localization and mapping and highlights on using SLAM algorithms for indoor navigation. Also the proposed approach for the current research is presented.