Guest editorial:special issue on digitial enterprise technology

Full text This Proceedings volume contains selected papers from the Fourth International CIRP-sponsored, Conference on Digital Enterprise Technology (DET2007), which was held at the University of Bath, UK, 19–21 September 2007. All selected papers have been suitably enhanced for publication in the Journal and have undergone full review. Digital enterprise technology (DET) is ‘the collection of systems and methods for the digital modelling and analysis of the global product development and realization process, in the context of lifecycle management.’ The principal aim of the DET concept is to provide a coherent context for the development and integration of the various digital technologies that underpin modern design and manufacturing. These technologies can be classified according to the following five key areas. 1. Distributed and collaborative design. 2. Process modelling and process planning. 3. Advanced factory design and modelling. 4. Physical-to-digital environment integrators–verification. 5. Enterprise integration technologies. This special issue is representative of the wide breadth of the DET concept including; a comprehensive review of digital engineering, design processes, digital modelling of machine tools, forming, robotics and machining processes, verification and metrology, and dynamic networks. It is particularly pleasing to see the development of metrology as a key aspect of modern manufacturing technology, linking design intent to process capability. The papers published herein will facilitate the exploration of new and evolving research concepts by the international research community and will influence the development of international standards for the application of DET technologies.

Design and analysis of a 2-DoF split-stator induction motor

A two degrees of freedom (2-DOF) actuator capable of producing linear translation, rotary motion, or helical motion would be a desirable asset to the fields of machine tools, robotics, and various apparatuses. In this paper, a novel 2-DOF split-stator induction motor was proposed and electromagnetic structure pa- rameters of the motor were designed and optimized. The feature of the direct-drive 2-DOF induction motor lies in its solid mover ar- rangement. In order to study the complex distribution of the eddy current field on the ferromagnetic cylinder mover and the motor’s operating characteristics, the mathematical model of the proposed motor was established, and characteristics of the motor were ana- lyzed by adopting the permeation depth method (PDM) and finite element method (FEM). The analytical and numerical results from motor simulation clearly show a correlation between the PDM and FEM models. This may be considered as a fair justification for the proposed machine and design tools.

Adaptive fault-tolerant teleoperation

While the robots gradually become a part of our daily lives, they already play vital roles in many critical operations. Some of these critical tasks include surgeries, battlefield operations, and tasks that take place in hazardous environments or distant locations such as space missions. ^ In most of these tasks, remotely controlled robots are used instead of autonomous robots. This special area of robotics is called teleoperation. Teleoperation systems must be reliable when used in critical tasks; hence, all of the subsystems must be dependable even under a subsystem or communication line failure. ^ These systems are categorized as unilateral or bilateral teleoperation. A special type of bilateral teleoperation is described as force-reflecting teleoperation, which is further investigated as limited- and unlimited-workspace teleoperation. ^ Teleoperation systems configured in this study are tested both in numerical simulations and experiments. A new method, Virtual Rapid Robot Prototyping, is introduced to create system models rapidly and accurately. This method is then extended to configure experimental setups with actual master systems working with system models of the slave robots accompanied with virtual reality screens as well as the actual slaves. Fault-tolerant design and modeling of the master and slave systems are also addressed at different levels to prevent subsystem failure. ^ Teleoperation controllers are designed to compensate for instabilities due to communication time delays. Modifications to the existing controllers are proposed to configure a controller that is reliable in communication line failures. Position/force controllers are also introduced for master and/or slave robots. Later, controller architecture changes are discussed in order to make these controllers dependable even in systems experiencing communication problems. ^ The customary and proposed controllers for teleoperation systems are tested in numerical simulations on single- and multi-DOF teleoperation systems. Experimental studies are then conducted on seven different systems that included limited- and unlimited-workspace teleoperation to verify and improve simulation studies. ^ Experiments of the proposed controllers were successful relative to the customary controllers. Overall, by employing the fault-tolerance features and the proposed controllers, a more reliable teleoperation system is possible to design and configure which allows these systems to be used in a wider range of critical missions. ^

Adaptive Fault-Tolerant Teleoperation

While the robots gradually become a part of our daily lives, they already play vital roles in many critical operations. Some of these critical tasks include surgeries, battlefield operations, and tasks that take place in hazardous environments or distant locations such as space missions. In most of these tasks, remotely controlled robots are used instead of autonomous robots. This special area of robotics is called teleoperation. Teleoperation systems must be reliable when used in critical tasks; hence, all of the subsystems must be dependable even under a subsystem or communication line failure. These systems are categorized as unilateral or bilateral teleoperation. A special type of bilateral teleoperation is described as force-reflecting teleoperation, which is further investigated as limited- and unlimited-workspace teleoperation. Teleoperation systems configured in this study are tested both in numerical simulations and experiments. A new method, Virtual Rapid Robot Prototyping, is introduced to create system models rapidly and accurately. This method is then extended to configure experimental setups with actual master systems working with system models of the slave robots accompanied with virtual reality screens as well as the actual slaves. Fault-tolerant design and modeling of the master and slave systems are also addressed at different levels to prevent subsystem failure. Teleoperation controllers are designed to compensate for instabilities due to communication time delays. Modifications to the existing controllers are proposed to configure a controller that is reliable in communication line failures. Position/force controllers are also introduced for master and/or slave robots. Later, controller architecture changes are discussed in order to make these controllers dependable even in systems experiencing communication problems. The customary and proposed controllers for teleoperation systems are tested in numerical simulations on single- and multi-DOF teleoperation systems. Experimental studies are then conducted on seven different systems that included limited- and unlimited-workspace teleoperation to verify and improve simulation studies. Experiments of the proposed controllers were successful relative to the customary controllers. Overall, by employing the fault-tolerance features and the proposed controllers, a more reliable teleoperation system is possible to design and configure which allows these systems to be used in a wider range of critical missions.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

A ROS-based Workspace Control and Trajectory Planner for a seven degrees of freedom Robotic arm

In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

Rede de aprendizagem em robótica : uma perspectiva educativa de trabalho com jovens

The present research sought to comprehend what is the development perspective of a collective work of educational robotics with high school students. The work started from the development activities Mathematics Sub Project of PIBID (Programa Institucional de Bolsa de Iniciação à Docência, Institutional Program of Initiation to Teaching Scholarship) in a school network from the state of Minas Gerais. The production process of data of this research was done through the follow up of high school students that participated in workshops robotics at the mentioned public school and were selected to continue the project at the Faculty of Mechanical Engineering in Federal University of Uberlândia (UFU). Subsequently, these students were involved in activities related to Robotics championships, elapsed through different spaces in public and private schools of basic education, University and Non-Governmental Organization. The data at the research were registered by photos, videos, field notes, documents produced by the participants and arising from internet like the social media Facebook, questionnaires and, mainly, interviews. At the analysis process of data the followed axes were constituted: Movement Learning Network with Robotics; The Different Roles at the Robotics Events and Experiences in Engineering and Technology. By this axes we understand what is the trajectory of the constitution process of a learning network in educational robotics that we find in expansion and consolidation. In this network the research participants performed different roles which left imprints responsible for their transformation. As a more evident imprint, we detected the robot construction and programming, which as for as they moved their studies forward, they developed the subject autonomy, collaboration, sharing and technological authorship.

The automation of protein crystal presentation for x ray diffraction experiments using standing acoustic waves in a microfluidic chip environment

As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

The automation of protein crystal presentation for X ray diffraction experiments using standing acoustic waves in a microfluidic chip environment

As the pressure continues to grow on Diamond and the world's synchrotrons for higher throughput of diffraction experiments, new and novel techniques are required for presenting micron dimension crystals to the X ray beam. Currently this task is both labour intensive and primarily a serial process. Diffraction measurements typically take milliseconds but sample preparation and presentation can reduce throughput down to 4 measurements an hour. With beamline waiting times as long as two years it is of key importance for researchers to capitalize on available beam time, generating as much data as possible. Other approaches detailed in the literature [1] [2] [3] are very much skewed towards automating, with robotics, the actions of a human protocols. The work detailed here is the development and discussion of a bottom up approach relying on SSAW self assembly, including material selection, microfluidic integration and tuning of the acoustic cavity to order the protein crystals.

A smart surgical robotic for cochlear implantation

In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Automatic Identification of Large Fragments in a Pile of Broken Rock Using a Time-of-Flight Camera

This paper presents a solution to part of the problem of making robotic or semi-robotic digging equipment less dependant on human supervision. A method is described for identifying rocks of a certain size that may affect digging efficiency or require special handling. The process involves three main steps. First, by using range and intensity data from a time-of-flight (TOF) camera, a feature descriptor is used to rank points and separate regions surrounding high scoring points. This allows a wide range of rocks to be recognized because features can represent a whole or just part of a rock. Second, these points are filtered to extract only points thought to belong to the large object. Finally, a check is carried out to verify that the resultant point cloud actually represents a rock. Results are presented from field testing on piles of fragmented rock. Note to Practitioners—This paper presents an algorithm to identify large boulders in a pile of broken rock as a step towards an autonomous mining dig planner. In mining, piles of broken rock can contain large fragments that may need to be specially handled. To assess rock piles for excavation, we make use of a TOF camera that does not rely on external lighting to generate a point cloud of the rock pile. We then segment large boulders from its surface by using a novel feature descriptor and distinguish between real and false boulder candidates. Preliminary field experiments show promising results with the algorithm performing nearly as well as human test subjects.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

HDPR: A Mobile Testbed for Current and Future Rover Technologies

The paper in hand presents a mobile testbed –namely the Heavy Duty Planetary Rover (HDPR)– that was designed and constructed at the Automation and Robotics Laboratories (ARL) of the European Space Agency to fulfill the lab’s internal needs in the context of long range rover exploration as well as in order to provide the means to perform in situ testing of novel algorithms. We designed a rover that: a) is able to reliably perform long range routes, and b) carries an abundant of sensors (both current rover technology and futuristic ones). The testbed includes all the additional hardware and software (i.e. ground control station, UAV, networking, mobile power) to allow the prompt deployment on the field. The reader can find in the paper the description of the system as well as a report on our experiences during our first experiments with the testbed.