Self Control and Server-Supervisory Control for Multiple Mobile Robots and its Applicability to Intelligent DNC System

Multiple mobile robots with six PSD (Position Sensitive Detector) sensors are designed for experimentally evaluating the performance of two control systems. They are self-control mode and server-supervisory control mode. The control systems are considered to realize swarm behaviors such as Ligia exotica. This is done by using only information of PSD sensors. Experimental results show basic but important behaviors for multiple mobile robots. They are following, avoidance, and schooling behaviors. The collective behaviors such as following, avoidance, and schooling emerge from the local interactions among the robots and/or between the robots and the environment. The objective of the study is to design an actual system for multiple mobile robots, to systematically simulate the behaviors of various creatures who form groups such as a school of fish or a swarm of insect. Further, the applicability of the server-supervisory control scheme to an intelligent DNC (Direct Numerical Control) system is briefly considered for future development. DNC system is an important peripheral apparatus, which can directly control NC machine tools. However, conventional DNC systems can neither deal with various information transmitted from different kinds of sensors through wireless communication nor output suitable G-codes by analyzing the sensors information in real time. The intelligent DNC system proposed at the end of the chapter aims to realize such a novel and flexible function with low cost.

Mobile Laboratory Model for Next-Generation Heterogeneous Wireless Systems

Failure to integrate heterogeneous wireless systems generally makes it difficult, if not impossible, for the continuation of remote working or remote experiments when human operators and equipment coexist through networks in a collaborative environment. Mobile laboratories using ubiquitous mobile communication for next-generation heterogeneous wireless systems have prospects for increasing the operation of distributed communication and mobile ubiquitous systems. All “technology assessors” concur that tomorrow's society will have access to smart objects (mobile devices or apparatuses, mobile equipment, e.g. robots) that contain “programs” that will assist with communication in everyday life. However one of the tomorrow’s challenges will consist of programming those objects to cooperate with and control telecommunications technologies. For a Mobile Laboratory to ensure consistent mobility in an environment, it must combine various wireless networks as a single integrated system. In this chapter we propose a Mobile Laboratory Model with mobile devices that take advantage of multiple mobile gateways by using Internet Protocol (IP) as the interconnection protocol to achieve the objective stated above.

Robot Modeling for Physical Rehabilitation

The science of rehabilitation shows that repeated movements of human limbs can help the patient regain function in the injured limb. There are three types of mechanical systems used for movement rehabilitation: robots, cable-based manipulators, and exoskeletons. Industrial robots can be used because they provide a three-dimensional workspace with a wide range of flexibility to execute different trajectories, which are useful for motion rehabilitation. The cable-based manipulators consist of a movable platform and a base, which are connected by multiple cables that can extend or retract. The exoskeleton is fixed around the patient's limb to provide the physiotherapy movements. This chapter presents a summary of the principal human limb movements, a review of several mechanical systems used for rehabilitation, as well as common mathematical models of such systems.

The Impact of Educational Robotics on Student STEM Learning, Attitudes, and Workplace Skills

This chapter discusses findings from a National Science Foundation (NSF) project funded by the Innovative Technologies Experiences for Student and Teachers (ITEST) program. The project has an ongoing research agenda focusing on the impact of robotics summer camps and competitions targeted at middle school youth. The research focused on the impact of the interventions on youth a) learning of computer programming, mathematics, and engineering concepts, b) science, technology, engineering, and math (STEM) attitudes, c) workplace skills, and d) STEM career interest. Results show that robotics camps and competitions appear to be viable strategies to increase student STEM learning, robotics self-efficacy, and problem solving skills.

Android Robots as Telepresence Media

In this chapter, the authors describe two human-like android robots, known as Geminoid and Telenoid, which they have developed. Geminoid was developed for two reasons: (1) to explore how humans react or respond the android during face-to-face communication and (2) to investigate the advantages of the android as a communication medium compared to traditional communication media, such as the telephone or the television conference system. The authors conducted two experiments: the first was targeted to an interlocutor of Geminoid, and the second was targeted to an operator of it. The results of these experiments showed that Geminoid could emulate a human’s presence in a natural-conversation situation. Additionally, Geminoid could be as persuasive to the interlocutor as a human. The operators of Geminoid were also influenced by the android: during operation, they felt as if their bodies were one and the same with the Geminoid body. The latest challenge has been to develop Telenoid, an android with a more abstract appearance than Geminoid, which looks and behaves as a minimalistic human. At first glance, Telenoid resembles a human; however, its appearance can be interpreted as any sex or any age. Two field experiments were conducted with Telenoid. The results of these experiments showed that Telenoid could be an acceptable communication medium for both young and elderly people. In particular, physical interaction, such as a hug, positively affected the experience of communicating with Telenoid.

Stereo Vision Depth Estimation Methods for Robotic Applications

Vision is undoubtedly the most important sense for humans. Apart from many other low and higher level perception tasks, stereo vision has been proven to provide remarkable results when it comes to depth estimation. As a result, stereo vision is a rather popular and prosperous subject among the computer and machine vision research community. Moreover, the evolution of robotics and the demand for vision-based autonomous behaviors has posed new challenges that need to be tackled. Autonomous operation of robots in real working environments, given limited resources requires effective stereo vision algorithms. This chapter presents suitable depth estimation methods based on stereo vision and discusses potential robotic applications.

Transforming Technical Services

The current economic downturn has resulted in constantly shrinking budgets and drastic staff reduction at the University of California, Santa Cruz (UCSC) Library. Meanwhile, rapid shifting to digital formats as well as dramatic growth in social networking, mobile applications and cloud computing continues. To face these challenges, the Technical Services (TS) at the university library at UCSC need a transformation. This chapter discusses how the authors have adopted the strategy of maximizing technology in utilizing “robot-like” batch processing tools in house to minimize the risk of becoming ineffective or irrelevant. In aligning human resources to apply those tools to achieve our goals in tandem with the mission of the library, the authors learn to work with the various issues and the barriers that we have encountered during the past decade. The authors are examining the changes brought to the department through the process, highlighting a plan of action, and providing guidance for those interested in bringing about a technological transformation that will continue into the future.

Collaborative Exploration based on Simultaneous Localization and Mapping

This chapter focuses on the study of SLAM taking into account different strategies for modeling unknown environments, with the goal of comparing several methodologies and test them in real robots even if they are heterogeneous. The purpose is to combine them in order to reduce the exploration time. Indubitably, it is not an easy work because it is important to take into account the problem of integrating the information related with the changes into the map. In this way, it is necessary to obtain a representation of the surrounding in an efficiently way. Furthermore, the author is interested in the collaboration between robots, because it is well-known that a team of robots is capable of completing a given task faster than a single robot. This assumption will be checked by using both simulations and real robots in different experiments. In addition, the author combines the benefits of both vision-based and laser-based systems in the integration of the algorithms.

Distributed Task Allocation in Swarms of Robots

This chapter introduces a swarm intelligence-inspired approach for target allocation in large teams of autonomous robots. For this purpose, the Distributed Bees Algorithm (DBA) was proposed and developed by the authors. The algorithm allows decentralized decision-making by the robots based on the locally available information, which is an inherent feature of animal swarms in nature. The algorithm’s performance was validated on physical robots. Moreover, a swarm simulator was developed to test the scalability of larger swarms in terms of number of robots and number of targets in the robot arena. Finally, improved target allocation in terms of deployment cost efficiency, measured as the average distance traveled by the robots, was achieved through optimization of the DBA’s control parameters by means of a genetic algorithm.

A Neurorobotics Approach to Investigating Word Learning Behaviors

This chapter presents two examples of how neurorobotics is being used to further understanding of word learning in the human infant. The chapter begins by presenting an example of how neurorobotics has been used to explore the synchrony constraint of word-referent association in young infants. The chapter then demonstrates the application of neurorobotics to free looking behavior, another important basic behavior with repercussions in how infants map visual stimuli to auditory stimuli. Neurorobotics complements other approaches by validating proposed mechanisms, by linking behavior to neural implementation, and by bringing to light very specific questions that would otherwise remain unasked. Neurorobotics requires rigorous implementation of the target behaviors at many vertical levels, from the level of individual neurons up to the level of aggregate measures, such as net looking time. By implementing these in a real-world robot, it is possible to identify discontinuities in our understanding of how parts of the system function. The approach is thus informative for empiricists (both neurally and behaviorally), but it is also pragmatically useful, since it results in functional robotic systems performing human-like behavior.