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The cab is first and foremost the driver’s workspace; but especially in long-haul transportation, it must also fulfill additional functions. It is a workplace, living space and sleeping quarters all in one.

Manufacturing processes of carbon fiber reinforced plastics (CFRP) components are often characterized by a high fraction of manual activities especially in terms of handling, cleaning and edge sealing. The innovative machining process introduced in the project CFKComplete comprises a fully integrated and automated workflow reducing unnecessary handling and transportation activities. The concept has been realized on a 5-axis machine tool, providing enough workspace for large structural workpieces and the developed technology units. The units themselves are defined by their modularity, scalability and independency of the guiding machine. Key aspect of the innovative concept are four purpose built and developed interchangeable technology units, which are driven by the base machinery. Thus, the machine’s working scope is being enhanced from machining to a fully integrated workflow including quality inspection, cleaning, sealing and curing.

We present a general approach for realizing safe collaborative behavior and high-accuracy operations in industrial robots. For example, collaborative behavior is required in human robot collaboration, whereas high-accuracy is needed in robotic machining. The operation sequence of a robot with corresponding often-contradictory demands on safety functions, control mode and accuracy is specified in a task-oriented path planner. The task planner generates optimized reference trajectories based on an environmental model, kinematic and task-specific constraints. The resulting reference path is fed into an online operation management, which monitors the workspace, ensures safety, and realizes different online control strategies especially for the dynamic tasks such as human robot collaboration or high-precision operations. For the high-accuracy tasks, we implemented a model predictive controller using a mechatronic model for predicting future configurations of the robot based on the measured present configuration. The model-predictive control is demonstrated for the compensation of deviations due to external forces that acts on the end effector of the robot.

Thermo-elastic errors in machine tools have a significant influence on the machining accuracy. The error at the tool center point can be determined with the structure model based correction, which uses physical based models like finite element models. The output of the structure model is the volumetric thermo-elastic error in the workspace of the machine tool. The correction values of the machine axes are determined based on the volumetric error with the help of a kinematic model. Therefore, three variants are presented in this article and their influence on the correction accuracy is estimated. The evaluation is based on typical thermo-elastic errors in the workspace of machine tools. The influence of the different variants on the correction accuracy is estimated with the Monte Carlo method based on randomly generated errors in the workspace of the machine.

In previous research, an aerodynamic feeding system was developed, which autonomously adapts to different components by using a genetic algorithm that controls the physical parameters of the system (e.g. angle of inclination, nozzle pressure). The algorithm starts with two individuals with random values, generated within the boundaries of the parameters set by the user. Due to this, the setting time - the time that passes until a satisfactory orientation rate is reached - is hard to predict. The aim of this work is to identify basic interactions of geometric component properties with the physical parameters of the aerodynamic feeding system to determine in which areas of the workspace a satisfactory solution can be expected. By doing so, the initial population of the genetic algorithm can be generated based on certain geometric properties and would therefore no longer be random, presumably reducing setting time.

The topic of human-robot collaboration has become an important part of research in recent years. With suitable sensors and intelligent software, the workspace of man and robot is moving ever closer together. Another possibility is the use of soft material robots for the human-robot collaboration. However, the nonlinear material behavior complicate the control of the robots. In this paper, the low-level control of soft pneumatic actuators is researched. Therefore, a test bench for the low-level control is developed. The components of the test bench like the valve, the tubes and the actuator are modeled. Unknown parameters of the model are identified with the particle swarm optimization. Thus, a simulation model in addition to the test bench is built. With the simulation and the test bench, it is possible to investigate control strategies with focus on robustness due to leakage and parameter change. To illustrate this, a linear control strategy is implemented and tested.

The current trend towards mass customization confronts established mass production systems with specific challenges, as these are designed for the production of large quantities with a small number of variants. Future production layouts will have to provide a high degree of flexibility and changeability in order to be able to respond to the demand for individualized mass products. This leads to a production network in which the work schedule of each product and thus the sequence of the individual production resources are flexibly arranged without losing the cost advantages of mass production. The current design forms, as a monolithic AGV system or the use of flexible autonomous units, show specific weaknesses that limit the use of these solutions in a flexible production network. The paper describes the research approach to establish an intralogistics service-based software architecture as an intralogistics execution system, which contains the elementary functions of a cross-platform use of mobile autonomous systems. One key application is the implementation of typespecific routes, which enables the cross-platform digitalization of the workspace to improve the interoperability and efficiency in route and path planning of different transport solution within one scenario. The implementation of the approach shows the advantages of a cross-platform service structure in general and the routing service in particular.

In the promising field of human-robot cooperation, robot manipulators must account for humans in the shared workspace. To this end, current prototypes integrate various algorithms (e.g. path planning or computer vision) into complex solutions for workspace monitoring. The step from research to industrial use for these solutions demands rigid validation of the underlying software with real-world and synthetic data. Related fields (e.g. human factors and ergonomics) implement toolsets to create synthetic data of human-machine interactions. However, existing toolsets employ hand-crafted motion paths or motion segments for their human agents. This limits the variety of resulting motions and implies laborious composition of animation sequences. In contrast to this, we contribute a novel approach to human animation for synthetic validation: We animate our human agents through a realistic physics simulation and we expose motion paths in a flexible and intuitive high-level editing interface. We also generate photo-realistic images of resulting animations through state-of-the-art rendering techniques. Finally, we employ these synthetic images and their ground-truth backing to validate a prototype for a workspace monitoring system and a subsequent online path planner.

Production lines are nowadays transforming into flexible modular and interconnected cells to react to rapidly changing product demands. The arrangement of the workspace inside the modular cells will vary according to the actual product being developed. Tasks like motion planning will not be possible to precompute. Instead, it has to be solved on demand. Planning the trajectories for the industrial robots with respect to changing obstacles and other varying environment parameters is hard to solve with classical path planning approaches. A possible solution is to employ sampling-based planning techniques. In this paper we present a distributed sampling-based path planner and an augmented reality visualization approach for verification of trajectories. Combining the technologies ensures a confirmed continuation of the production process under new conditions. Using parallel and distributed path planning speeds up the planning phase significantly and comparing different mobile devices for augmented reality representation of planned trajectories reveals a clear advantage for hands-free HoloLens. The results are demonstrated in several experiments in laboratory scale.

Industrial robots are established tools in a variety of automation processes. An important goal in actual research is to transfer the advantages of these tools into environments in small and medium sized enterprises (SME). As tasks in SME environments change from time to time, it is necessary to enable nonexpert workers to program an industrial robot in an intuitive way. Furthermore, robot programs must concern unexpected situations as many SME environments are unstructured, because humans and robots share workspace and workpieces. The main contribution of our work is a robot programming architecture, that concerns both aspects: Intuitive robot programming and robust task execution. Our architecture enables users to create robot programs by guiding a robot kinesthetically through tasks. Relevant task information are extracted by an entity-actor based world model. From these information we encode the demonstrated task as a finite state machine (FSM). The FSM allows the reproduction and adaption of a task by the robot in similar situations. Furthermore, the FSM is utilized in a monitoring component, which identifies unexpected events during task execution.

Close quarters human-robot collaboration promises the integration of human flexibility with robot precision, endurance, and strength. However, such collaboration requires a monitoring solution for the shared human-robot workspace to drive the robot manipulator. Recent research has already developed a variety of individual software components for monitoring solutions, from object detection over reconstruction to path planning. In our contribution, we implement existing components for multi-camera reconstruction, risk estimation and path planning in the form of concurrent agents and we connect these agents through a shared blackboard in order to realize risk-minimal path planning for a robot manipulator. We discuss our software architecture, and we evaluate the final software in an example application of human-robot collaboration. In conclusion, our contribution enables risk-minimal path planning on an industrial manipulator at a 10 Hz update rate.

Tubular continuum robots are the smallest among continuum robots. They are composed of multiple, precurved, superelastic tubes. The design space for tubular continuum robots is infinite: each one of the component tubes can be individually parameterized in terms of its length, segmental curvatures, diameter, and material properties. Ad-hoc selection of those parameters is extremely challenging, since the elastic coupling of concentrically arranged and actuated tubes is hard to predict with common sense, especially under the presence of workspace constraints. In this chapter, an overview of the design process is given and the current state of the art in task-specific design of tubular continuum robots is reviewed.

The spatial design of work spaces where people are permanently or temporarily located, results primarily from the type of cooperation and the required levels of communication. Secondly, it is important to promote mental and physical well-being. Finally, under all circumstances, health risks need to be minimized. In terms of communication, planning and implementing tasks of production should be close to each other or “under one roof”, while offices could be planned in various forms. Of special significance is the fire protection, which is regulated in detail in all countries. The chapter describes the practical details and regulations.

An approach for solving the challenges that arise from the increased complexity of modern assembly tasks is believed to be human robot co-operation. In these hybrid workplaces humans and robots do not only work on the same task or interact during certain assembly steps, but also have overlapping workspaces. Therefore, ‘safe robots’ should be developed that do not harm workers in case of a collision. In this chapter, an overview of methods for designing a hardware based soft robot that is inherently safe in human-machine interaction is given. Recent projects show that robots could be soft enough for interaction but they are not able to resist forces that occur in the assembly process. Current solutions show that the designer of such robots must face a trade-off between softness and dexterity on the one hand and rigidity and load carrying capabilities on the other hand. A promising approach is to integrate variable stiffness elements in the robotic system. The chapter classifies two main design rules to achieve stiffness variability, the tuning of material properties and geometric parameters. Existing solutions are described and four concepts are presented to show how different mechanisms and materials could be combined to design safe assembly robots with a variable stiffness structure.

Bio-inspired locomotion control method is one of the ways to promote the site application of biped robots. This paper synthesizes the main idea and structure of central pattern generator (CPG) inspired biped walking control methods into two kinds of common strategies: joint space control methods and workspace control methods. The key problems of these two approaches are deeply explored. Finally, the research direction of the CPG-inspired control method is discussed. The motivation of this paper is to synthesize the current mainly methods for biped robots to present a practical guide to researchers and engineers interested in the CPG-inspired control approaches.

The new structure of spatial parallel robots from Delta robots family is elaborated in this research. The proposed novel mechanism like ordinary Delta parallel mechanism has three degrees of pure translational freedom, but the position of robot’s three active joints relative to each other is one difference between this mechanism and Delta parallel mechanism, which has caused the change in geometry of platforms, and it shapes the asymmetrical structure in the robot mechanism and its workspace. Another difference arises from an architectural optimization methodology by consideration of mixed performance index which has utilized in this mechanism for reaching a better compromise between the dexterity of manipulator and its workspace volume. Inverse dynamic modeling is performed based on Lagrange formulation. The PD and PID controllers of Computed Torque method (C-T) usually need manual retuning to make a successful industrial application, particularly in the presence of disturbance. In the present paper, we study feasibility of applying fuzzy supervisory control for PD and PID used in C-T method. Numerous computer simulations demonstrate the effectiveness of proposed control method in comparison with ordinary C-T method.

This paper presents the design, and characterization of a single degree of freedom haptic device based upon the Peaucellier-Lipkin mechanism, which is a perfect straight line motion. As compared to other single degree of freedom devices, the device features a larger workspace, and force output, while providing perfect straight line motion. Link lengths to minimize the size of the mechanism for the desired workspace size were determined following an optimization procedure. A prototype of the device has been built, and evaluated using bandwidth and apparent inertia measurements.

One of the main challenges while teleoperating a humanoid robot consists in maintaining the slave’s balance while satisfying the operator’s intention. The main goal of this work is to settle whether feeding back the robot’s balance state to the operator by the mean of a vibrotactile belt can lead to an enhanced quality teleoperation. This study examines if an adequate cutaneous guidance can enable the operator to understand when the robot is approaching a loss-of-balance configuration, and use this information to adjust his teleoperation strategy. To achieve this objective, three different feedback patterns were compared during an initial experimental study. The evaluation focused on the subjects capacity to recognize the boundaries of a virtual workspace under each feedback mode and to adapt accordingly their teleoperated motions. The best suited feedback mode was selected and used during a second experiment which compared the performances obtained with and without tactile feedback during the teleoperation of the humanoid robot COMAN. Results clearly reveal that the cutaneous feedback of the slave’s balance state leads towards an enhanced quality teleoperation combining an increased safety as well as an unrestrained use of the entire stable workspace.

Routing tendons in straight paths along an elastic backbone is a widely used method of actuation for continuum robots. Tendon routing paths which are general curves in space enable a much larger family of robots to be designed, with configuration spaces and workspaces that are unattainable with straight tendon routing. Harnessing general tendon routing to extend the capabilities of continuum robots requires a model for the kinematics and statics of the robot, which is the primary focus of this paper. Our approach is to couple the classical Cosserat theories of strings and rods using a geometrically exact derivation of the distributed loads that the tendons impose along the robot. Experiments demonstrate that the model accurately predicts tip position to 1.7% of the total arc length, on a prototype robot that includes both straight and helical tendon routing and is subject to both point and distributed loads.

The performance of a haptic device generally varies across its workspace. This work measures the force rendering accuracy and maximum force output rendering capabilities of two commercial devices – the Falcon and Omega devices – in six directions at 46 and 49 set locations, respectively, in the mechanical workspace. The results are compared to several theoretical measures of performance based on force ellipsoids. Findings quantify the differences in rendering capability across the tested locations, and show that this variability can be mostly explained by the highly nonlinear nature of the Jacobian.

Wi-Fi Direct is a new feature in the 4.0 version of the Android operating system, allowing devices to connect directly to each other via Wi-Fi without an intermediate access point. Based on the Wi-Fi Direct feature, in this paper, we present a collaborative framework named DirectSpace that supports various collaborative situations to resolve the problems of traditional application paradigm such as client-server model. For this, we design collaborative services to support various environments, and develop collaborative protocols for providing workspaces over Wi-Fi Direct. On the top of DirectSpace, we also present a collaborative application for utilizing the group workspaces.

We describe the development of a vision-based cooperative localization and tracking framework for a team of small autonomous ground robots operating in an indoor environment. The objective is to enable a team of small mobile ground robots with limited sensing to explore, monitor, and search for objects of interest in regions in the workspace that may be inaccessible to larger mobile ground robots. In this work, we describe a vision-based cooperative localization and tracking framework for a team of small networked ground robots. We assume each robot is equipped with an LED-based identifier/marker, a color camera, wheel encoders, and wireless communication capabilities. Cooperative localization and tracking is achieved using the on-board cameras and local inter-agent communication. We describe our approach and present experimental and simulation results where a team of small ground vehicles cooperatively track other ground robots as they move around the workspace.

A fully-fledged programming paradigm based on ideas from multi-agent systems requires a lot more than early agent-oriented programming languages envisaged. More than interaction between autonomous entities, the social level of multi-agent systems as well as the shared environment where the agents are situated also need to be suitably designed. In fact, the abstractions used at each of those three levels are all equally important and interrelated. In this chapter, we discuss JaCaMo, a platform for multi-agent-oriented programming that covers abstractions such as: beliefs, goals, and plans at the agent level; groups, roles, functional schemes (i.e., social plans), and norms at the organizational level; and artifacts and workspaces at the environment level. The chapter also includes a simple multi-agent system example to illustrate the approach.

Integration of a tactile display onto the end effector of a robot allows free-hand exploration of an encountered-type environment that provides both kinesthetic and cutaneous feedback. A novel tactile display approach, called Haptic Jamming, uses a combination of particle jamming and pneumatics to control the stiffness and shape of a surface. The tactile display mounts to the cable-driven platform of a kinesthetic system for medical simulation, called KineSys MedSim. The parallel structure of the robot provides a high strength-to-weight ratio for kinesthetic feedback in combination with a spatially aligned visual display. Its controller uses hand tracking to move the platform to the portion of the workspace the user is reaching toward. Data from a lump localization simulation demonstrates that the integrated system successfully tracks the user’s hand and reconfigures the tactile display according to the location of the end effector.

With the increasing demand for robots to assist humans in shared workspaces and environments designed for humans, research on human-robot interaction (HRI) gains more and more importance. Robots in shared environments must be safe and act in a way understandable by humans, through the way they interact and move. As visual cues such as facial expressions are important in human-human communication, research on emotion recognition, expression, and emotionally enriched communication is of great importance to HRI and has also gained increasing attention during the last two decades [1, 3, 4, 6, 8]. Most of the existing work focuses on the recognition of human emotions or mimicking their expression [1, 6] and emotional action selection [3, 5]. Less work is done on the role of emotions in influencing human behaviour in HRI [4].

Multiple independent robots sharing the workspace need to be able to navigate to their goals while avoiding collisions with each other. In this paper, we describe and evaluate two algorithms for smooth and collision-free navigation for multiple independent differential-drive robots.We extend reciprocal collision avoidance algorithms based on velocity obstacles and on acceleration-velocity obstacles. We implement bothmethods on multiple iRobot Create differential-drive robots, and report on the quality and ability of the robots using the two algorithms to navigate to their goals in a smooth and collision-free manner.