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.

Perception Effects in Ground Robotic Tele-Operation

The focus of this article is perception affects and enhancement during ground robotic tele-operation. Three independent factors were studied, namely scale perception, distance perception, and orientation awareness. Enhancements for each factor was proposed, implemented, and evaluated. The results show that under remote perception conditions, where the operator was separated from the environment where the navigation took place, both distance perception and scale perception were significantly impaired as compared with that obtained under direct perception conditions. In addition, for each of the proposed enhancements designed for each critical factor, the corresponding factor was significantly improved. The broader impacts of this work can be applied to various human-robot collaborated applications, such as urban search and rescue. Applying the proposed enhancements will allow the operators to have fewer failures through hallways, doorways, or maneuvering around obstacles, as well as allowing a more accurate understanding of the area's layout when a map is not available.

On the Uncertainty Control in the Complex Multiphysics Systems in the Task of Multi-Scale Stochastic GHG and Carbon Balance Modeling

The problem of uncertainty analysis in complex multi-component systems is considered. The problem of decision making with uncertainty in tasks modeling carbon balance and the analysis of greenhouse gas (GHG) emissions using satellite tools was considered. Approaches to decision making under uncertainty are described in terms of interval, fuzzy, and stochastic assessments. Different approaches and algorithms to calculate carbon and GHG emissions are described. For every algorithm, errors and uncertainties are analyzed and estimated. Algorithms for uncertainty analysis based on integrated interlinked models of the system are presented. Algorithms for the analysis of components of vegetation productivity assessment using satellite data are proposed. Uncertainty component analysis allows the understanding of important properties of the system studied, and its feedback as to its anthropogenic load and impact on the climate. It was demonstrated that the comprehensive analysis of uncertainties allows not only the reduction of errors, but new knowledge about the studied systems.

Human Detection by Surveillance Camera

Security problems and decreasing costs, leads to the rapid development of video surveillance systems. It is necessary to implement analytical tools capable of identifying objects that may appear in the video sequence. The work presented in this article consists of designing a video surveillance system for the automatic detection of humans in a video sequence acquired by a fixed camera. The principle of this work is based on the modeling and subtraction of the background. In order to determine the nature of the objects, the authors make the detection of the contours of the foreground image, then by matching this contour with the images of a base, silhouette images of people in different positions. The acquisition of the frames is carried out in real time, the matching of the images takes a considerable time and this time becomes increasingly longer based on the size of the base. To solve this problem, the authors have used the parallelism.

Formal Modeling and Analysis of Collaborative Humanoid Robotics

A humanoid robot is inherently complex due to the heterogeneity of accessory devices and to the interactions of various interfaces, which will be exponentially increased in multiple robotics collaboration. Therefore, the design and implementation of multiple humanoid robotics (MHRs) remains a very challenging issue. It is known that formal methods provide a rigorous analysis of the complexity in both design of control and implementation of systems. This article presents an agent-based framework of formal modeling on the design of communication and control strategies of a team of autonomous robotics, to attain the specified tasks in a coordinated manner. To ensure a successful collaboration of multiple robotics, this formal agent-based framework captures behaviors in Petri Net models and specifies collaboration operations in four defined operations. To validate the framework, a non-trivial soccer bot set was implemented and simulation results were discussed.

Emotional State Recognition Using Facial Expression, Voice, and Physiological Signal

Emotion recognition is an important aspect of affective computing, one of whose aims is the study and development of behavioral and emotional interaction between human and machine. In this context, another important point concerns acquisition devices and signal processing tools which lead to an estimation of the emotional state of the user. This article presents a survey about concepts around emotion, multimodality in recognition, physiological activities and emotional induction, methods and tools for acquisition and signal processing with a focus on processing algorithm and their degree of reliability.

Integrating Linear Physical Programming and Fuzzy Logic for Robot Selection

An increasing number of companies are using robots to perform a variety of repetitive and hazourdous tasks. Existence of many different robot alternatives force companies to consider several conflicting criteria before determining the most suitable robot alternative. Researchers have developed various multi-criteria decision making based methodologies in order to assist the decision makers in robot selection process. However, those methodologies require decision makers to assign physically meaningless weights to evaluation criteria. This article eliminates this weight assignment process by proposing a robot selection methodology based on linear physical programming. In addition, fuzzy logic was integrated into the proposed approach in order to determine the preference values of subjective robot evaluation criteria. A numerical example is also provided in order to present the applicability of the proposed methodology.

Autonomous Intelligent Robotic Navigation System Architecture With Mobility Service for IoT

This article presents the platform for autonomous vehicle architecture, navigation optimization and mobility services. The basic approach is to develop an intelligent agent to create a safety journey and redefine the world of transportation. The goal is to eliminate human driving errors and save human life from accidents. AI robots are a concept of future transportation with full automation and self-learning. Velodyne laser sensors are used for obstacle detection and autonomous navigation of ground vehicles and to create 3D images of the surround so that navigation and controls are optimized. In this article, existing system accessibility will be optimized by multiple features. The agent accessibility is improved, and users can access the vehicles through different ways like mobile apps, speech recognition and gestures. This article concentrates on the mobility services of autonomous vehicles.

Kinova Modular Robot Arms for Service Robotics Applications

This article presents Kinova's modular robotic systems, including the robots JACO2 and MICO2, actuators and grippers. Kinova designs and manufactures robotics platforms and components that are simple, sexy and safe under two business units: Assistive Robotics empowers people living with disabilities to push beyond their current boundaries and limitations while Service Robotics empowers people in industry to interact with their environment more efficiently and safely. Kinova is based in Boisbriand, Québec, Canada. Its technologies are exploited in over 25 countries and are used in many applications, including as service robotics, physical assistance, medical applications, mobile manipulation, rehabilitation, teleoperation and in research in different areas such as computer vision, artificial intelligence, grasping, planning and control interfaces. The article describes Kinova's hardware platforms, their different control modes (position, velocity and torque), control features and possible control interfaces. Integration to other systems and application examples are also presented.

A Computational, Cognitive, and Situated Framework for Emotional Social Simulations

Human emotions and social processes are evolutionary intertwined, as the result of neuromodulatory mechanisms that define the nature of how bodies interact with the world and create strategies with other bodies and agents. This article presents the previous simulations of TPR, TPR 2.0 and The Game of Emotions. Ideas are also justified in order to achieve the next research level into social emotional simulations. This article describes a defense of the epistemological value of computer simulations for the analysis of emotions and social interactions. Finally, the elements of the model are described as well as is defined a basic sketch of the basic control algorithm.