Robotics

Software development of industrial robots requires interdisciplinary knowledge and technical experience. Due to the heterogeneity of the manufacturer-dependent programming languages and tools, robot programming remains highly complex, although robots themselves are flexible and can be used for a wide range of applications. To support different roles during the development, including component provider, application developer, system integrator and end user, a model based approach was developed in the research project ReApp. The data exchange format AutomationML was used for the modelling of robot components and systems. Based on domain ontologies, the AutomationML models were processed semantically and converted to a machine-interpretable information model, from which source code was generated.

In contrast to the use of robots in standardized production processes, robots must be flexible and adaptable within dynamic logistics processes in order to cope with variable environmental conditions and non-standardized goods. Due to the recent advances in the field of artificial intelligence and networking through industry 4.0, robots will perform complex tasks in logistics in a reliable way in future. A crucial component of a robot system represents the interpretation of the work environment with the help of multi-modal sensor systems, especially image processing systems. This paper describes applications for robotic systems in logistics as well as a concrete example of focusing on the interpretation of multi-modal sensor data for the automation of a logistics task.

New areas of application arise for robots due to collaborative robots and new operation concepts. We describe important characteristics of these robotic systems and, as a possible application area for these systems, we present in this article a robotic assistant system for manual manufacturing tasks, which is controlled with a multi-modal user interface.

The methods presented allow the splitting of classic monolithic numerical controls of industrial robots and machine tools into their functional units. The core functionalities can then be brought onto different computers in even separate places. Using techniques of augmented reality allows enriching a captured scene with additional information, as a virtual model of the industrial robot or the planned paths. Combining these approaches leads to a simplified programming task for industrial robots as the programs can be visualized in their context. This decreases setup time and improves quality.

Intelligent and autonomous robots are an essential part of the development of industry 4.0 solutions. They will act as a direct interaction partner to humans together in teams and perform works that are much more complex than today‘s typical tasks for industrial robots. Such robots need to deal with a confusing and unpredictable environment and have to react to unforeseeable events. In order to capture this environment and to plan actions, real-time processing of complex sensor information is necessary. Conventional computer architectures appear to be insufficient for such kind of tasks. To solve this problem, hardware accelerators for robotics based on the dataflow paradigm are developed at the Robotics Innovation Center of the German Research Center for Artificial Intelligence.

In many fields of production for processing tasks with high frequency and repeatability, robots are commonly used. However, the use of industrial and service robots also increases in the logistics sector. Container handling, particularly the unloading of for example coffee sacks, has enormous potential for automation with robotics. The heavy weight together with the deformability of these sacks and unpredictable stack situations inside a container have the highest mechanical and cognitive demands on the gripper technology and the corresponding gripping strategy. This paper describes the development and implementation of such a gripping process.

Due to the growing application of robotic systems in logistic companies, the demand of qualified professionals is growing. The potentials of individualized robotic solutions are currently not exploited by small and medium enterprises. Therefore a target group specific further education for robotics in logistics has been developed. The modular design ensures the close connection of the education modules to the core work processes of the industry sector. The “Lessons Learned” summarize important insights from the educational scientific examinations in logistic companies as well as from the execution of the education modules.

In the field of automobile production, automation has been implemented since the nineteen-seventies. In logistics, however, robotics has only been used to automate logistics processes with low complexity. These include processes with a high repetition rate and a highly standardized goods portfolio. In cooperation with EASY-ROB, BIBA has developed a new strategy for an intuitive programming of robotics that might be used to fulfill rather complex tasks. The operator defines the process type and important parameters via a common tracking system. Based on this data, a simulation tool calculates the movement of the robot and executes a collision control. Finally, the simulation tool generates the corresponding machine code and the robot starts its process. The intuitive programming excels at a favorably cost-benefit ratio. A demonstrator, focusing on the unloading of pallets has been presented on the CeMAT 2011. After a very brief introduction, interested visitors were able to operate the ...

To expand capabilities of robots in manufacturing and service but also to meet needs in the ever-increasing desire for a flexible and changeable production, a new class of robots is required. These robots have to be able to independently react to changes - so called autonomous systems which do not have to be programmed for any task, butreact to the changed situation and new tasks autonomously, according to their sensory perception .On the basis of two current examples from industry-related research in this paper the possibilities for the use of systems with an autonomous path planning are presented. This is a mobile robot for automated inspection of material flow systems and an industrial robot, equipped with a new sensor system for bin picking.