Learning Action Duration and Synergy in Task Planning for Human-Robot Collaboration

Proceedings of the Workshop “Towards the factory of the future: advancements in planning and control of industrial robots” at the conference IEEE ETFA 2022. Sandrini, Samuele; Faroni, Marco; Pedrocchi, Nicola   ABSTRACT A good estimation of the actions’ cost is key in task planning for human-robot collaboration. The duration of an action depends on agents’…

Towards User-Awareness in Human-Robot Collaboration for Future Cyber-Physical Systems

Proceedings of the Workshop “Towards the factory of the future: advancements in planning and control of industrial robots” at the conference IEEE ETFA 2021 Alessandro Umbrico; Andrea Orlandini; Amedeo Cesta; Spyros Koukas; Andreas Zalonis; Nick Fourtakas; Dionisis Andronas; George Apostolopoulos; Sotiris Makris   ABSTRACT Cyber-Physical Systems constitute one of the core concepts in Industry 4.0…

Simplify the robot programming through an action-and-skill manipulation framework

Proceedings of the Workshop “Towards the factory of the future: advancements in planning and control of industrial robots” at the conference IEEE ETFA 2021 Villagrossi, Enrico; Pedrocchi, Nicola; Beschi, Manuel   ABSTRACT The paper introduces a robotic manipulation framework suitable for the execution of manipulation tasks. Based on the ROS platform, the framework provides advanced…

Open-Box Target for Extrinsic Calibration of LiDAR, Camera and Industrial Robot

Proceedings of International Conference on Mechatronics, Robotics and Automation (ICMRA), 2020 Rashid, Aquib; Kolker, Alexey; Hardt, Wolfram; Bdiwi, Mohamad; Putz, Matthias   Abstract Low cost 3D LiDAR complement cameras in perception application for various industrial environments. Safe and efficient human robot collaboration requires easy and accurate extrinsic calibration of sensors with an industrial robot. This…

Enhanced Cognition for Adaptive Human-Robot Collaboration

Proceedings of the Workshop “Towards the factory of the future: advancements in planning and control of industrial robots” at the conference IEEE ETFA 2021. Alessandro Umbrico; Mikel Anasagasti; Stefan-Octavian Bezrucav; Francesca Canale; Amedeo Cesta; Burkhard Corves; Nils Mandischer; Mikel Mondragon; Cristina Naso; Andrea Orlandini   ABSTRACT Cyber-Physical Systems constitute one of the core concepts in…

Operator training framework for hybrid environments: An Augmented Reality module using machine learning object recognition

Published in: Procedia CIRP: Volume 106 George Apostolopoulos; Dionisis Andronas; Nikos Fourtakas; Sotiris Makris   Abstract As market demands are characterized by more customized products with shorter lifecycles, it is obligatory for modern operators to manage recurrent product or manufacturing system changes. In contrary to previous years, adaptation to such changes prerequires memorization of more…

Modelling Automated Planning Problems for Teams of Mobile Manipulators in a Generic Industrial Scenario

Published in: Applied Sciences: Volume 12 (Issue 5) Stefan-Octavian Bezrucav; Burkhard Corves   Abstract Flexible control strategies are required in industrial scenarios to coordinate the actions of mobile manipulators (e.g., robots and humans). Temporal planning approaches can be used as such control strategies because they can generate those actions for the agents that must be…

Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High Ranges

Published in: Sensors: Volume 21 (Issue 14) Nils Mandischer; Tobias Huhn; Mathias Hüsing; Burkhard Corves Abstract In the EU project SHAREWORK, methods are developed that allow humans and robots to collaborate in an industrial environment. One of the major contributions is a framework for task planning coupled with automated item detection and localization. In this work, we…

Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning

Proceedings of Robotics Science and Systems Conference Julen Urain; Puze Liu; Carlo D’Eramo; Jan Peters (TU Darmmstadt); Anqui Li (University of Washington) Abstract Reactive motion generation problems are usually solved by computing actions as a sum of policies. However, these policies are independent of each other and thus, they can have conflicting behaviors when summing…

Simplifying the A.I. Planning modeling for Human-Robot Collaboration

Proceedings of the 30th IEEE International virtual Conference on Robot & Human Interactive Communication (RO-MAN 2021) Elisa Foderaro; Amedeo Cesta; Alessandro Umbrico; Andrea Orlandini (Institute of Cognitive Science and Technology, National Research Council of Italy) Abstract For an effective deployment in manufacturing, Collaborative Robots should be capable of adapting their behavior to the state of the environment…