Continuum Mechanics for Coordinating Massive Microrobot Swarms

This chapter addresses the problem of coordinating the behavior of very large numbers of microrobots to assemble complex, hierarchically structured physical objects. The approach is patterned after morphogenetic processes during embryological development, in which masses of simple agents (cells) coordinate to produce complex three-dimensional structures. To ensure that the coordination mechanisms scale up to hundreds of thousands or millions of microrobots, the swarm is treated as a continuous mass using partial differential equations. A morphogenetic programming notation permits algorithms to be developed for coordinating dense masses of microrobots. The chapter presents algorithms and simulations for assembling segmented structures (artificial spines and legs) and for routing artificial neural fiber bundles. These algorithms scale over more than four orders of magnitude.

Overview of Wireless Sensor Network, Robotics, IoT, and Social Media in Search and Rescue Activities

In recent years, many researchers have shown interest in developing search and rescue systems composed of one or multiple robots. To enhance the robotic systems, wireless sensor networks and internet of things (IoT) were integrated to give more awareness of the environments. Additionally, data exchanged in social media during emergency situations can help rescuers, decision makers, and the public to gain insight into the situation as it unfolds. In the first part of this chapter, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain the challenges related to these systems and the tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the systems that integrates WSNs and IoT with robots and the advantages that brings those. Furthermore, they expose and discuss the remarkable research, the challenges, and the open research challenges that include this cooperation.

Fusion of Gravitational Search Algorithm, Particle Swarm Optimization, and Grey Wolf Optimizer for Odor Source Localization

This chapter concerns the problem of odor source localization by a team of mobile robots. A brief overview of odor source localization is given which is followed by related work. Three methods are proposed for odor source localization. These methods are largely inspired by gravitational search algorithm, grey wolf optimizer, and particle swarm optimization. Objective of the proposed approaches is to reduce the time required to localize the odor source by a team of mobile robots. The intensity of odor across the plume area is assumed to follow the Gaussian distribution. Robots start search from the corner of the workspace. As robots enter in the vicinity of plume area, they form groups using K-nearest neighbor algorithm. To avoid stagnation of the robots at local optima, search counter concept is used. Proposed approaches are tested and validated through simulation.

A Current Review of Human Factors and Ergonomic Intervention With Exoskeletons

Research and development of exoskeletons began as early as the 1960s. Recent advancement in technology has spurred a further research into the field specifically at rehabilitation and human performance augmentation. Human performance augmenting exoskeletons find use in the military, emergency services, industrial and space applications, and training. Rehabilitation exoskeletons assist in posture support and replacing lost function. Exoskeleton research is broadly broken up in this chapter by anthropometry: lower body, upper body, and extremities. The development for various anthropometry has their own unique set of challenges. This chapter provides a brief history, discusses current trends in research, looks at some of the technology involved in development, the potential benefits of using exoskeletons, and looks at the possible future improvements in research.

History of Service Robots and New Trends

The chapter gives an overview of the current developmental trends in service robotics. First the short history of service robots with its precursors is presented together with the definitions. The developmental trends and statistical data are summarized. The overview of service robots includes the ancient robot precursors, the middle ages, and the period of industrial revolution. The representative examples of different kinds of service robots built in the 20th and 21st centuries are also given. The chapter is concluded by discussing the perspectives of service robotics.

Improving Dependability of Robotics Systems

In this chapter, the authors propose an algorithm for the reduction of fault tree expressions that are generated from failure behavioral models. The significance of the sequencing of events is preserved during the generation and all along the reduction process, thus allowing full qualitative analysis. Thorough and detailed analysis results should positively impact the design of condition monitoring and failure prevention mechanisms. A behavioral model of a robotic system that exhibits sequence-dependent failures is used in the study.

Towards Multiple-Layer Self-Adaptations of Multi-Agent Organizations Using Reinforcement Learning

This chapter proposes a multi-agent organization model for self-adaptive software to examine the autonomous components and their self-adaptation that can be occurred at either the fine-grain behavior layer of a software agent or the coarse-grain organization layer of the roles that the agent plays. The authors design two-layer self-adaptation mechanisms and combine them with reinforcement learning together to tackle the uncertainty issues of self-adaptation, which enables software agents to make decisions on self-adaptation by learning at run-time to deal with various unanticipated changes. The reinforcement learning algorithms supporting fine-grain and coarse-grain adaptation mechanisms are designed. In order to support the development of self-adaptive software, the software architecture for individual agents, the development process and the software framework are proposed. A sample is developed in detail to illustrate our method and experiments are conducted to evaluate the effectiveness and efficiency of the proposed approach.

Design, Analysis, and Applications of Mobile Manipulators

Presented in this chapter is a method for design and analysis of a mobile manipulator. The wrench induced by the movement of the robot arm will cause system tip-over or slip. In tip-over analysis, three cases are considered. The first case deals with the effect of the link weights and tip payload on the horizontal position of the CG. The second case deals with the effect of the joint speeds through the coupling terms including centrifugal forces and gyroscopic moments. The third case deals with the effect of the joint accelerations through the inertia forces and moments. In slip analysis, the first case considers the reaction force in relation to the stand-off distance between system and work-piece. The second and third cases investigate the effects of the joint speeds and accelerations. Then, the mobile platform is optimized to have maximum tip-over stability which optimizes the placement of the robot arm and accessory on the mobile platform. The effectiveness of the proposed method is demonstrated.

Visual Servo Kinematic Control for Robotic Manipulators

In the last couple of decades, massive industrial application demands greatly accelerated the advances of control theories for robotic manipulator. However, the autonomous robotic capture is still facing many technical challenges. A novel visual servo kinematic control scheme for robotic manipulators to perform autonomous capture operation of a non-cooperative target is presented. An integrated algorithm of the photogrammetry and the adaptive extended Kalman filter is introduced to estimate the position and orientation of the target. In order to improve the reliability of the robotic control and to avoid the multiple solutions problem of inverse kinematics, a kinematics-based incremental control approach is adopted to control the robotic manipulator in real time. Validating experiments are performed on a custom built robotic manipulator with an eye-in-hand configuration. The experimental results demonstrate the effectiveness and robustness of the proposed control visual servo kinematic control scheme.

Awareness-Based Recommendation by Passively Interactive Learning

In artificial intelligence and robotics, one of the important issues is to design human interface. There are two issues: One is the machine-centered interaction design. Another one is the human-centered interaction design. This research aims at the latter issue. This chapter presents the interactive learning system to assist positive change in the preference of a human toward the true preference. Then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users. As future research directions, a probabilistic event and its basic recommendation way are discussed.