Object-oriented and distributed approach for programming robotic manufacturing cells

Flexible manufacturing systems (FMS) are essential for small/medium batch and job shop manufacturing. These types of production systems are used to manufacture a considerable variety of products with medium/small production volumes. Therefore, the manufacturing platforms supporting these types of production must be flexible and organized in flexible manufacturing cells (FMC). Programming FMCs remains a difficult task and is an actual area of research and development. This paper reports an object-oriented approach developed for FMC programming. The work presented was first thought for application in industrial robot manipulators, and later extended to other FMC equipments just by putting the underlying ideas in a general framework. Initially, the motivation for this work was to develop means to add force control to a standard industrial robot manipulator. This problem requires remote access to the robot controller, remote programming and monitoring, as also is required to program and monitor any other FMC equipment. The proposed approach is distributed based on a client/server model and runs on Win32 platforms, i.e., Microsoft Windows and Windows NT. Implementation for the special case of industrial robot manipulators is presented, along with some application examples used for educational, research and industrial purposes.     

Reusable robot system for display and disposal tasks at convenience stores based on a SysML model and RT Middleware

Service robots are increasingly being expected to replace human labor; however, in practical settings, these robots have not been fully utilized, partly because the applications that service robots are expected are quite broad. Suitable hardware and software should be developed in order to cope with a wide variety of applications. Ideally, these resources should be developed using common hardware and software platforms are required. Middleware platforms for robotics software, such as ROS and RT Middleware, have already been developed. However, these platforms still face reusability problems due to the inconsistency present in system architectures. Systems are typically assumed to be reused with a given architecture, and if the user-side software architecture is inconsistent with this assumption, the system's reusability suffers. To address this issue, we propose a procedure for optimizing system development using SysML. In this study, our robot system is designed to complete a display disposal tasks in a convenience store; we verify the validity of the robot system using this task. In addition, to verify the reusability of the developed robot system, we employ system functions developed for another task and demonstrate their reuse and operation.     

Multivariate evaluation of interactive robot systems

In designing robot systems for human interaction, designers draw on aspects of human behavior that help them achieve specific design goals. For instance, the designer of an educational robot system may use speech, gaze, and gesture cues in a way that enhances its student’s learning. But what set of behaviors improve such outcomes? How might designers of such a robot system determine this set of behaviors? Conventional approaches to answering such questions primarily involve designers carrying out a series of experiments in which they manipulate a small number of design variables and measure the effects of these manipulations on specific interaction outcomes. However, these methods become infeasible when the design space is large and when the designer needs to understand the extent to which each variable contributes to achieving the desired effects. In this paper, we present a novel multivariate method for evaluating what behaviors of interactive robot systems improve interaction outcomes. We illustrate the use of this method in a case study in which we explore how different types of narrative gestures of a storytelling robot improve its users’ recall of the robot’s story, their ability to retell the robot’s story, their perceptions of and rapport with the robot, and their overall engagement in the experiment.     

Storytelling by a kindergarten social assistive robot: A tool for constructive learning in preschool education

Kindergarten Social Assistive Robotics (KindSAR) is a novel technology that offers kindergarten staff an innovative tool for achieving educational aims through social interaction. Children in a preschool setting have previously been shown to benefit from playing educational games with the KindSAR robot. The experiment presented here was designed to examine how KindSAR can be used to engage preschool children in constructive learning. The basic principle of constructivist education is that learning occurs when the learner is actively involved in a process of knowledge construction. In this study, storytelling was used as a paradigm of a constructive educational activity. An interactive robot served as a teacher assistant by telling prerecorded stories to small groups of children while incorporating song and motor activities in the process. Our results show that the children enjoyed interacting with the robot and accepted its authority. This study demonstrates the feasibility and expected benefits of incorporating KindSAR in preschool education.     

Simultaneous Parameter Calibration,Localization, and Mapping

Abstract

The calibration parameters of a mobile robot play a substantial role in navigation tasks. Often these parameters are subject to variations that depend either on changes in the environment or on the load of the robot. In this paper, we propose an approach to simultaneously estimate a map of the environment, the position of the on-board sensors of the robot, and its kinematic parameters. Our method requires no prior knowledge about the environment and relies only on a rough initial guess of the parameters of the platform. The proposed approach estimates the parameters online and it is able to adapt to non-stationary changes of the configuration. We tested our approach in simulated environments and on a wide range of real-world data using different types of robotic platforms.     

Discovery of sound sources by an autonomous mobile robot

In this work, we describe an autonomous mobile robotic system for finding, investigating, and modeling ambient noise sources in the environment. The system has been fully implemented in two different environments, using two different robotic platforms and a variety of sound source types. Making use of a two-step approach to autonomous exploration of the auditory scene, the robot first quickly moves through the environment to find and roughly localize unknown sound sources using the auditory evidence grid algorithm. Then, using the knowledge gained from the initial exploration, the robot investigates each source in more depth, improving upon the initial localization accuracy, identifying volume and directivity, and, finally, building a classification vector useful for detecting the sound source in the future.     

End-user programming architecture facilitates the uptake of robots in social therapies

This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations. It aims to facilitate the uptake and actual use of robot technologies in therapies for training social skills to autistic children. However, the framework is easy to generalize for an arbitrary human–robot interaction application, where users with no technical background need to program robots, i.e. in various assistive robotics applications. We identified the main needs of end-user programming of robots as a basic prerequisite for the uptake of robots in assistive applications. These are reusability, modularity, affordances for natural interaction and the ease of use. After reviewing the shortcomings of the existing architectures, we developed an initial architecture according to these principles and embedded it in a robot platform. Further, we used a co-creation process to develop and concretize the architecture to facilitate solutions and create affordances for robot specialists and therapists. Several pilot tests showed that different user groups, including therapists with general computer skills and adolescents with autism could make simple training or general behavioral scenarios within 1 h, by connecting existing behavioral blocks and by typing textual robot commands for fine-tuning the behaviors. In addition, this paper explains the basic concepts behind the TiViPE based robot control platform, and gives guidelines for choosing the robot programming tool and designing end-user platforms for robots.     

Proposal for a new concept for a robot in which the constructing module can be exchanged seamlessly

Although industrial robots have developed considerably since the end of the last century, and have been used in various fields, robotics is still being actively researched in Japan. Following the work of national research institutes and educational institutions, robot manufacturers have also put considerable resources into developing a new generation of robots. Moreover, society in general has high expectations of robots. To provide a low-price robot that can be widely used in the home, in medical treatments, in welfare, and in disaster relief, etc., a high-function, low-cost module that can easily be exchanged for maintenance or repair is very necessary. To achieve this aim, it is undesirable to develop robots based on different original standards from research institutes, educational institutions, and robot manufacturers, etc. Therefore, a common standard in robotic development needs to be established, and robots must be developed based on that standard. In this research, a new concept for the next generation of robot development is proposed. This concept includes a high-intelligence module, lower manufacturing costs, and an easy exchange operation.     

Iterative design of a semi-autonomous social telepresence robot research platform: a chronology

Our research focuses on how a telepresence robot operator, the people with the robot, and the robot itself collaborate so that the operator reaches his/her intended destination. Our research requires higher levels of autonomous navigation so that the robot can, for example, go to a specified destination and follow a person. However, commercial telepresence robots are primarily teleoperated, and only a few provide assisted navigation around obstacles. Our system must include sensors and processing to enable these capabilities. We present the chronology of our iterative design for augmenting two VGo Communications’ VGo robots, Hugo and Margo, over a period of 3 years. We detail the requirements and design constraints encountered while developing our telepresence robot platforms.     

A case study in multi-core parallelism for the reliability evaluation of composite power systems

The probabilistic evaluation of composite power system reliability is an important but computationally intense task that requires the sampling/searching of a large search space. While multiple methods have been used for performing these computations, a remaining area of research is the impact that modern platforms for parallel computation may have on this computation. Studies have been performed in the past, but they have been primarily limited to cluster-based computing. In addition, the most recent works in this area have used outdated technology or been evaluated using smaller test systems. In the modern era, a wide variety of platforms are available for achieving parallelism in computation including options like multi-core processors, clusters, and accelerators. Each of these platforms provides unique opportunities for accelerating computation and exploiting scalability. In order to fill this gap in the research, this study implements and evaluates two methods of parallel computation—batch parallelism and pipeline parallelism—using a multi-core architecture in a cloud computing environment on Amazon Web Services using up to 36 virtual compute cores. Further, the methodologies are contrasted and compared in terms of computation time, speedup, efficiency, and scalability. Results are collected using IEEE reliability test systems, and speedups upwards of 5x are demonstrated across multiple test systems.     

Dynamic Modeling and Robust Controller Design of a Two-Stage Parallel Cable Robot

Cable robots have been extensively used for the loading and unloading of cargo in shipping industries. In this paper, we look at a two stage cable robot, i.e., a cable robot with two moving platforms connected in series. The sea condition introduces disturbance into the system. This disturbance is considered while modeling the dynamics of the two stage cable robot. A robust controller is designed which can assure robust tracking of the desired end-effector trajectory in the presence of the disturbance. Simulation results presented show the effectiveness of the controller.     

An autonomous educational mobile robot mediator

So far, most of the applications of robotic technology to education have mainly focused on supporting the teaching of subjects that are closely related to the Robotics field, such as robot programming, robot construction, or mechatronics. Moreover, most of the applications have used the robot as an end or a passive tool of the learning activity, where the robot has been constructed or programmed. In this paper, we present a novel application of robotic technologies to education, where we use the real world situatedness of a robot to teach non-robotic related subjects, such as math and physics. Furthermore, we also provide the robot with a suitable degree of autonomy to actively guide and mediate in the development of the educational activity. We present our approach as an educational framework based on a collaborative and constructivist learning environment, where the robot is able to act as an interaction mediator capable of managing the interactions occurring among the working students. We illustrate the use of this framework by a 4-step methodology that is used to implement two educational activities. These activities were tested at local schools with encouraging results. Accordingly, the main contributions of this work are: i) A novel use of a mobile robot to illustrate and teach relevant concepts and properties of the real world; ii) A novel use of robots as mediators that autonomously guide an educational activity using a collaborative and constructivist learning approach; iii) The implementation and testing of these ideas in a real scenario, working with students at local schools.

Big Data 2.0 Processing Systems: Taxonomy and Open Challenges

Data is key resource in the modern world. Big data has become a popular term which is used to describe the exponential growth and availability of data. In practice, the growing demand for large-scale data processing and data analysis applications spurred the development of novel solutions from both the industry and academia. For a decade, the MapReduce framework, and its open source realization, Hadoop, has emerged as a highly successful framework that has created a lot of momentum in both the research and industrial communities such that it has become the defacto standard of big data processing platforms. However, in recent years, academia and industry have started to recognize the limitations of the Hadoop framework in several application domains and big data processing scenarios such as large scale processing of structured data, graph data and streaming data. Thus, we have witnessed an unprecedented interest to tackle these challenges with new solutions which constituted a new wave of mostly domain-specific, optimized big data processing platforms. In this article, we refer to this new wave of systems as Big Data 2.0 processing systems. To better understand the latest ongoing developments in the world of big data processing systems, we provide a taxonomy and detailed analysis of the state-of-the-art in this domain. In addition, we identify a set of the current open research challenges and discuss some promising directions for future research.     

Sustainable polymorphic colonial robotics and large scale off-world construction

Self-reliant mobile robots have the potential to perform useful and productive work in remote and hostile environments. A colonial architecture, comprising a population of both static operations robots and modular mobile robots, enables self-reliance. Sustainability extends operational life and enables continued operation beyond disabling events. Polymorphism enables performance of multiple roles at optimal efficiency. In this paper, we present algorithms enabling fault detection, identification and rectification whilst achieving and maintaining mobile robot build orders within an error prone environment. Modules that exhibited faulty behaviour are identified and replaced. When a robot is not required then it is disassembled for storage or polymorphed into a new role. Near optimal physical graceful degradation is demonstrated on a robot module scale. The application described in this research is the automated deployment of a large scale off-world human habitat for 10 to 50 personnel from site clearing to radiation shielding.     

Toward combining autonomy and interactivity for social robots

The success of social robots in achieving natural coexistence with humans depends on both their level of autonomy and their interactive abilities. Although a lot of robotic architectures have been suggested and many researchers have focused on human–robot interaction, a robotic architecture that can effectively combine interactivity and autonomy is still unavailable. This paper contributes to the research efforts toward this architecture in the following ways. First a theoretical analysis is provided that leads to the notion of co-evolution between the agent and its environment and with other agents as the condition needed to combine both autonomy and interactivity. The analysis also shows that the basic competencies needed to achieve the required level of autonomy and the envisioned level of interactivity are similar but not the same. Secondly nine specific requirements are then formalized that should be achieved by the architecture. Thirdly a robotic architecture that tries to achieve those requirements by utilizing two main theoretical hypothesis and several insights from social science, developmental psychology and neuroscience is detailed. Lastly two experiments with a humanoid robot and a simulated agent are reported to show the potential of the proposed architecture.     

Leveraging proficiency and preference for online Karaoke recommendation

Recently,many online Karaoke(KTV)platforms have been released,where music lovers sing songs on these platforms.In the meantime,the system automatically evaluates user proficiency according to their singing behavior.Recommending approximate songs to users can initialize singers5 participation and improve users,loyalty to these platforms.However,this is not an easy task due to the unique characteristics of these platforms.First,since users may be not achieving high scores evaluated by the system on their favorite songs,how to balance user preferences with user proficiency on singing for song recommendation is still open.Second,the sparsity of the user-song interaction behavior may greatly impact the recommendation task.To solve the above two challenges,in this paper,we propose an informationfused song recommendation model by considering the unique characteristics of the singing data.Specifically,we first devise a pseudo-rating matrix by combing users’singing behavior and the system evaluations,thus users'preferences and proficiency are leveraged.Then we mitigate the data sparsity problem by fusing users*and songs'rich information in the matrix factorization process of the pseudo-rating matrix.Finally,extensive experimental results on a real-world dataset show the effectiveness of our proposed model.     

A survey on run-time supporting platforms for cyber physical systems

Cyber physical systems (CPSs) incorporate computation, communication, and physical processes. The deep coupling and continuous interaction between such processes lead to a significant increase in complexity in the design and implementation of CPSs. Consequently, whereas developing CPSs from scratch is inefficient, developing them with the aid of CPS run-time sup-porting platforms can be efficient. In recent years, much research has been actively conducted on CPS run-time supporting plat-forms. However, few surveys have been conducted on these platforms. In this paper, we analyze and evaluate existing CPS run-time supporting platforms by first classifying them into three categories from the viewpoint of software architecture: com-ponent-based platforms, service-based platforms, and agent-based platforms. Then, for each type, we detail its design philosophy, key technical problems, and corresponding solutions with specific use cases. Subsequently, we compare existing platforms from two aspects: construction approaches for CPS tasks and support for non-functional properties. Finally, we outline several im-portant future research issues.     

Map merging for multiple robots using Hough peak matching

Navigation in a GPS-denied environment is an essential requirement for increased robotics autonomy. While this is in some sense solved for a single robot, the next challenge is to design algorithms for a team of robots to be able to map and navigate efficiently.The key requirement for achieving this team autonomy is to provide the robots with a collaborative ability to accurately map an environment. This problem is referred to as cooperative simultaneous localization and mapping (SLAM). In this research, the mapping process is extended to multiple robots with a novel occupancy grid map fusion algorithm. Map fusion is achieved by transforming individual maps into the Hough space where they are represented in an abstract form. Properties of the Hough transform are used to find the common regions in the maps, which are then used to calculate the unknown transformation between the maps.Results are shown from tests performed on benchmark datasets and real-world experiments with multiple robotic platforms.     

Robotic Urban Search and Rescue: A Survey from the Control Perspective

Robotic urban search and rescue (USAR) is a challenging yet promising research area which has significant application potentials as has been seen during the rescue and recovery operations of recent disaster events. To date, the majority of rescue robots used in the field are teleoperated. In order to minimize a robot operator’s workload in time-critical disaster scenes, recent efforts have been made to equip these robots with some level of autonomy. This paper provides a detailed overview of developments in the exciting and challenging area of robotic control for USAR environments. In particular, we discuss the efforts that have been made in the literature towards: 1) developing low-level controllers for rescue robot autonomy in traversing uneven terrain and stairs, and perception-based simultaneous localization and mapping (SLAM) algorithms for developing 3D maps of USAR scenes, 2) task sharing of multiple tasks between operator and robot via semi-autonomous control, and 3) high-level control schemes that have been designed for multi-robot rescue teams.