http://dl.gi.de/handle/20.500.12116/36216 Thu, 23 Jul 2026 07:57:06 GMT 2026-07-23T07:57:06Z http://dl.gi.de/handle/20.500.12116/36232 Perception-Guided Mobile Manipulation Robots for Automation of Warehouse Logistics Bartels, Georg; Beetz, Michael Tue, 01 Jan 2019 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36232 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36236 Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory Rehse, Jana-Rebecca; Mehdiyev, Nijat; Fettke, Peter With the advent of digitization on the shopfloor and the developments of Industry 4.0, companies are faced with opportunities and challenges alike. This can be illustrated by the example of AI-based process predictions, which can be valuable for real-time process management in a smart factory. However, to constructively collaborate with such a prediction, users need to establish confidence in its decisions. Explainable artificial intelligence (XAI) has emerged as a new research area to enable humans to understand, trust, and manage the AI they work with. In this contribution, we illustrate the opportunities and challenges of process predictions and XAI for Industry 4.0 with the DFKI-Smart-Lego-Factory. This fully automated factory prototype built out of LEGO $$^\circledR$$ ® bricks demonstrates the potentials of Industry 4.0 in an innovative, yet easily accessible way. It includes a showcase that predicts likely process outcomes and uses state-of-the-art XAI techniques to explain them to its workers and visitors. Tue, 01 Jan 2019 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36236 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36235 Vision-Based Solutions for Robotic Manipulation and Navigation Applied to Object Picking and Distribution Roa-Garzón, Máximo A.; Gambaro, Elena F.; Florek-Jasinska, Monika; Endres, Felix; Ruess, Felix; Schaller, Raphael; Emmerich, Christian; Muenster, Korbinian; Suppa, Michael This paper presents a robotic demonstrator for manipulation and distribution of objects. The demonstrator relies on robust 3D vision-based solutions for navigation, object detection and detection of graspable surfaces using the rc _ visard , a self-registering stereo vision sensor. Suitable software modules were developed for SLAM and for model-free suction gripping. The modules run onboard the sensor, which enables creating the presented demonstrator as a standalone application that does not require an additional host PC. The modules are interfaced with ROS, which allows a quick implementation of a fully functional robotic application. Tue, 01 Jan 2019 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36235 2019-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36233 Editorial Ragni, Marco Tue, 01 Jan 2019 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36233 2019-01-01T00:00:00Z