Daniel Losch

Virtual commissioning of automated micro-optical assembly

In this contribution, we present a novel approach to enable virtual commissioning for process developers in micro-optical assembly. Our approach aims at supporting micro-optics experts to effectively develop assisted or fully automated assembly solutions without detailed prior experience in programming while at the same time enabling them to easily implement their own libraries of expert schemes and algorithms for handling optical components. Virtual commissioning is enabled by a 3D simulation and visualization system in which the functionalities and properties of automated systems are modeled, simulated and controlled based on multi-agent systems. For process development, our approach supports event-, state- and time-based visual programming techniques for the agents and allows for their kinematic motion simulation in combination with looped-in simulation results for the optical components. First results have been achieved for simply switching the agents to command the real hardware setup after successful process implementation and validation in the virtual environment. We evaluated and adapted our system to meet the requirements set by industrial partners-- laser manufacturers as well as hardware suppliers of assembly platforms. The concept is applied to the automated assembly of optical components for optically pumped semiconductor lasers and positioning of optical components for beam-shaping

Virtual commissioning and symbolic planning of micro-optical assembly processes

Automation in micro-optical assembly is an emergent, but steadily growing field of research. To advance the optics industrys efforts in this regard, several methods that aid optics engineers with development and deployment of assembly processes have been proposed. However, it is still a non-trivial and time-consuming task to design efficient work orders that consider movement characteristics of integrated robotic assembly systems. In this contribution, we present an approach to combine well-investigated symbolic planning algorithms, semantic modelling techniques and 3D simulation-based virtual commissioning to generate optimized work orders for automated micro-optical assembly and thereby help to overcome the difficulties of manual process design. Our approach is a good example for the efficiency of the eRobotics concept and demonstrates how its systematic application can resolve practical problems with existing approaches. Results indicate that our approach to automated planning is, by enabling a formal definition of quality metrics for action sequences, not only faster but also usually superior to manual generation of work orders.

Symbolic planning for industrial applications - the eRobotics approach

One of the greatest challenges in automated planning in industrial environments is to create the link between a real world scenario and symbolic representations that are used by a planner. In this paper we describe an approach to interface a planner with a close-to-reality simulation system. By using this approach, we move the problematic interface with a physical scenario to the simulation system, where we can benefit from a representation that is connected with the real world by methods being developed in the context of simulation-based control and eRobotics, an evolving branch of eSystems engineering. Along with these methods for grounding, we get full control over the system and its inner state, not only when the real system is running, but also during development in a purely simulated environment. Since the planner is completely decoupled from the environment, the connection to reality can be established when the development process is completed. We are using the Planning Domain Definition Language (PDDL) to interface different planners with our simulation system. Planning components in the context of industrial robotics were developed, which enable intuitive modeling of knowledge representations. A representation of actions using the custom Petri net scripting language SOML++ is used for intuitive visualization of generated planner output and for execution control in the physical and in simulated scenarios.

An Industry 4.0-based repair concept for structural CFRP components in the automotive sector

Due to global warming and a raising awareness of ecological implications of fossil fuel use, electromobility is an aspiring market for the automotive industry. However, electric vehicles still suffer from a couple of issues that are currently under research. One of these problems is the high weight of incorporated rechargeable battery units. To compensate battery weight, automotive manufacturers have replaced metal components by substantially lighter, but structurally equivalent components made of carbon fiber reinforced plastics (CFRP). However, since electric vehicles are still far from being common, there are no economic repair concepts yet. This publication will present such a concept for repairing CFRP-based electric vehicles, based on the Industry 4.0 approach, and first results regarding the automated production of CFRP patches as a part of this concept.

A Novel Cost Estimation Approach for Wood Harvesting Operations Using Symbolic Planning

Abstract While forestry is an important economic factor, the methods commonly used to estimate potential financial gains from undertaking a harvesting operation are usually based on heuristics and experience. Those methods use an abstract view on the harvesting project at hand, focusing on a few general statistical parameters. To improve the accuracy of felling cost estimates, we propose a novel, single-tree-based cost estimation approach, which utilizes knowledge about the harvesting operation at hand to allow for a more specific and accurate estimate of felling costs. The approach utilizes well-known symbolic planning algorithms which are interfaced via the Planning Domain Definition Language (PDDL) and compile work orders. The work orders can then be used to estimate the total working time and thus the estimated cost for an individual harvesting project, as well as some additional efficiency statistics. Since a large proportion of todays harvesting operations are mechanized instead of motor manual, we focus on the planning of harvester and forwarder workflows. However, the use of these heavy forest machines carries the risk of damaging forest soil when repeatedly driving along skidding roads. Our approach readily allows for assessment of these risks.

Minimal-effort planning of active alignment processes for beam-shaping optics

In science and industry, the alignment of beam-shaping optics is usually a manual procedure. Many industrial applications utilizing beam-shaping optical systems require more scalable production solutions and therefore effort has been invested in research regarding the automation of optics assembly. In previous works, the authors and other researchers have proven the feasibility of automated alignment of beam-shaping optics such as collimation lenses or homogenization optics. Nevertheless, the planning efforts as well as additional knowledge from the fields of automation and control required for such alignment processes are immense. This paper presents a novel approach of planning active alignment processes of beam-shaping optics with the focus of minimizing the planning efforts for active alignment. The approach utilizes optical simulation and the genetic programming paradigm from computer science for automatically extracting features from a simulated data basis with a high correlation coefficient regarding the individual degrees of freedom of alignment. The strategy is capable of finding active alignment strategies that can be executed by an automated assembly system. The paper presents a tool making the algorithm available to end-users and it discusses the results of planning the active alignment of the well-known assembly of a fast-axis collimator. The paper concludes with an outlook on the transferability to other use cases such as application specific intensity distributions which will benefit from reduced planning efforts.

3D simulation-based user interfaces for a highly-reconfigurable industrial assembly cell

Although SMEs would benefit from robotic solutions in assembly, the required invests and efforts for their implementation are often too risky and costly for them. Here, the Horizon 2020 project “ReconCell” aims at developing a new type of highy-reconfigurable multi-robot assembly cell which adresses the particular needs of SMEs. At the Institute for Man- Machine Interaction (MMI), we are developing 3D simulation-based user interfaces for ReconCell as the central technology to enable the fast, easy and safe programming of the system. ReconCell heavily builds on previous developments that are transferred from research and prepared for industrial partners with real use cases and demands. Thus, in this contribution, we describe MMIs software platform that will be the basis of the desired user interfaces for robot simulation and control, assembly simulation and execution, Visual Programming and sensor simulation.

Simulation-based analysis of mechanized wood harvest operations

While forestry is an important economic factor, the common methods used to estimate potential financial gains from undertaking a harvest project in Germany are usually based on heuristics and experience. Experience-based estimation methods focus on utilizing a few general statistical parameters that define the harvest operation, employing an abstract view on wood harvesting. To improve the accuracy of felling cost estimates, we propose a novel, simulation-based system that utilizes concrete knowledge about the harvest project at hand to allow for a more specific and accurate estimate of felling costs. The simulation-system offers a wide range of parameterizations to the user, enabling them to model scenarios according to their requirements. In addition to gaining insights into the economic factors of wood harvesting operations, our approach enables us to extract detailed work statistics from the simulation results, providing detailed knowledge about the simulated felling process as well as its impact on the forest ecosystem.

Visual Programming and Development of Manufacturing Processes Based on Hierarchical Petri Nets

In this contribution we present a formalism to combine the well-known process modeling technique based on Petri nets with the recent developments in Visual Programming for robot programming. The resulting modeling approach enables process developers and robot programmers to follow a hierarchical approach to process development and to profit from the extensive analysis techniques developed for Petri nets, as well as the specialized robot programming features of the Visual Programming system. We applied our approach to an exemplary robot manufacturing process, demonstrating its modeling capabilities.