The present generation of robots are based on systems that are equipped with standard products for intelligent sensor systems. These machines are usually embedded in a rigid control unit and have little cognitive abilities. PROFACTOR’s research focuses on innovative technology solutions and systems whose autonomous decision-making power is characterized by increasing complexity.
The goal is to enable machines and systems to adapt their assistance as autonomously as possible, according to the situation and in real time. The acceptance of such solutions by the human operator is also taken into account – regardless of the obligatory safety issues.
PROFACTOR’s current research focuses on the following topics:
- Cooperative Robotics: The focus is on interaction between human and the robot sharing the same workspace and carrying out their work on the same object simultaneously.
- Situated Assistance: The goal is efficient and robust recognition of user behavior in real-time. Instead of considering the user as an obstacle, the user behavior is classified and necessary assistance is offered in real time.
- Decentralized and distributed system architectures: Simplifying the programming effort of the system with heterogeneous elements such as sensors, robots and control.
- Automatic Process Planning: Enabling (semi-) automatic planning of the handling and inspection processes, automatic planning of robotic processes and optimization of adaptively generated process plans.
- New Action Patterns and Modalities: The focus is on the patterns and modalities of human-robot cooperation – taking the user acceptance into account.
Projects
Publications
Zörrer, H., Weichhart, G., Schmoigl Tonis, M., Bieg, T., Propst, M., Schuster, D., Sturm, N., Nativel, C., Salomon, G., Strohmeier, F., Sackl, A., Eberle, M., & Pichler, A. (2023). Enabling End-Users in Designing and Executing of Complex, Collaborative Robotic Processes. Applied System Innovation, 6(3), 56. https://doi.org/10.3390/asi6030056
Deshpande, K., Möhl, P., Hämmerle, A., Weichhart, G., Zörrer, H., & Pichler, A. (2022). Energy Management Simulation with Multi-Agent Reinforcement Learning: An Approach to Achieve Reliability and Resilience. Energies, 15(19). https://doi.org/10.3390/en15197381
Haemmerle, A., Deshpande, K., Moehl, P., & Weichhart, G. (2022). Training an Energy Management Simulation with Multi-Agent Reinforcement Learning. Researchgate.Net, May. https://www.researchgate.net/profile/Kapil-Deshpande-5/publication/360912718_Training_an_Energy_Management_Simulation_with_Multi-Agent_Reinforcement_Learning/links/62920b1455273755ebbda8af/Training-an-Energy-Management-Simulation-with-Multi-Agent-Reinforc
Pratheepkumar, A., Hofmann, M., Ikeda, M., & Pichler, A. (2022). Domain Adaptation With Evolved Target Objects for AI Driven Grasping. IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, 2022-Septe. https://doi.org/10.1109/ETFA52439.2022.9921470
Zörrer, H., Propst, M., Weichhart, G., Pichler, A., Strohmeier, F., & Schmoigl-Tonis, M. (2022). ROBxTASK RTE – a lightweight runtime environment to implement collaborative processes across different robotic systems. IFAC-PapersOnLine, 55(10), 2647–2652. https://doi.org/10.1016/j.ifacol.2022.10.109
Akkaladevi, S. C., Plasch, M., Hofmann, M., & Pichler, A. (2021). Semantic knowledge based reasoning framework for human robot collaboration. Procedia CIRP, 97, 373–378. https://doi.org/10.1016/j.procir.2020.05.253
Ikeda, M., Chitturi, N., Ganglbauer, M., & Pichler, A. (2021). ScienceDirect Knowledge Based Accuracy Improvement in Programming by Demonstration of Point Based Processes. 00(2019).
Ikeda, M., Ganglbauer, M., Chitturi, N., & Pichler, A. (2021). ScienceDirect Geometric Reasoning enabled One Shot Learning for Robotic Tasks. 00(2019).
Plasch, M., Akkaladevi, S. C., Hofmann, M., Wögerer, C., & Pichler, A. (2021). Event-driven knowledge engineering as enabling technology towards configuration of assistance systems in industrial assembly. Smart Innovation, Systems and Technologies, 200, 261–272. https://doi.org/10.1007/978-981-15-8131-1_24
Viktor, A., Ikeda, M., & Pichler, A. (2021). ScienceDirect Panorama Image Based Code Free Programming of Line Based Robotic Operations. 00(2019).
Weichhart, G., Mangler, J., Raschendorfer, A., Mayr-Dorn, C., Huemer, C., Hämmerle, A., & Pichler, A. (2021). An adaptive system-of-systems approach for resilient manufacturing. Elektrotechnik Und Informationstechnik, 138(6), 341–348. https://doi.org/10.1007/s00502-021-00912-2
Weichhart, G., Pichler, A., Strohmeier, F., Schmoigl, M., & Zorrer, H. (2021). The ROBxTASK architecture for interoperability of robotic systems. 2021 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2021 – Proceedings, 449–453. https://doi.org/10.1109/MetroInd4.0IoT51437.2021.9488560
AKKALADEVI, Sharath Chandra, et al. Semantic knowledge based reasoning framework for human robot collaboration. Procedia CIRP, 2021, 97. Jg., S. 373-378.
Chandra, S., Plasch, M., Hofmann, M., & Pichler, A. (2020). ScienceDirect Semantic Knowledge Based Reasoning Framework for Human Robot Collaboration. 00(2019), 1–6.
Spitzer, F., Lindorfer, R., Froschauer, R., Hofmann, M., & Ikeda, M. (2020). A generic Approach for the Industrial Application of Skill-based Engineering using OPC UA. Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), 8.
Weichhart, G., Ikeda, M., & Propst, M. (2020). PlugBot Architecture for Modular Manufacturing Enterprise Interoperability may be seen as one end of a continuum ranging from tight integration of.
Akkaladevi, S. C., Plasch, M., Pichler, A., & Ikeda, M. (2019). Towards reinforcement based learning of an assembly process for human robot collaboration. Procedia Manufacturing, 38(Faim 2019), 1491–1498. https://doi.org/10.1016/j.promfg.2020.01.138
Heindl, C., Ikeda, M., Stübl, G., Pichler, A., & Scharinger, J. (2019). Enhanced Human-Machine Interaction by Combining Proximity Sensing with Global Perception. 2020. http://arxiv.org/abs/1910.02445
Heindl, C., Ikeda, M., Stübl, G., Pichler, A., & Scharinger, J. (2019). Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision. 1. http://arxiv.org/abs/1910.03239
Akkaladevi, S. C., Plasch, M., Eitzinger, C., Pichler, A., & Rinner, B. (2018). Towards a Context Enhanced Framework for Multi Object Tracking in Human Robot Collaboration. IEEE International Conference on Intelligent Robots and Systems, 8435–8442. https://doi.org/10.1109/IROS.2018.8593842
Akkaladevi, S. C., Plasch, M., Maddukuri, S., Eitzinger, C., Pichler, A., & Rinner, B. (2018). Toward an interactive reinforcement based learning framework for human robot collaborative assembly processes. Frontiers Robotics AI, 5(NOV), 1–15. https://doi.org/10.3389/frobt.2018.00126
Fast-Berglund, A., Thorvald, P., Billing, E., Palmquist, A., Romero, D., & Weichhart, G. (2018). Conceptualizing Embodied Automation to Increase Transfer of Tacit knowledge in the Learning Factory. 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 – Proceedings, 358–364. https://doi.org/10.1109/IS.2018.8710482
Weichhart, G., Fast-Berglund, A., Romero, D., & Pichler, A. (2018). An Agent- and Role-based Planning Approach for Flexible Automation of Advanced Production Systems. 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 – Proceedings, 391–399. https://doi.org/10.1109/IS.2018.8710546
Wögerer, C., Mühlberger, M., Ikeda, M., Kastner, J., & Chitturi, N. C. (2018). Inkjet Printings on FFF printed curved surfaces. Fraunhofer Direct Digital Manufacturing Conference, March, 2–5.
Hämmerle, A., & Weichhart, G. (2017). Variable neighbourhood search solving sub-problems of a lagrangian flexible scheduling problem. ICORES 2017 – Proceedings of the 6th International Conference on Operations Research and Enterprise Systems, 2017-Janua, 234–241. https://doi.org/10.5220/0006114102340241
Weichhart, G., & Hämmerle, A. (2017). Lagrangian relaxation realised in the NgMPPS multi actor architecture. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10413 LNAI, 138–155. https://doi.org/10.1007/978-3-319-64798-2_9
Akkaladevi, S. C., Ankerl, M., Fritz, G., & Pichler, A. (2016). Real-time tracking of rigid objects using depth data. Computer Vision and Robotics.
Akkaladevi, S., Ankerl, M., Heindl, C., & Pichler, A. (2016). Tracking multiple rigid symmetric and non-symmetric objects in real-time using depth data. Proceedings – IEEE International Conference on Robotics and Automation, 2016-June, 5644–5649. https://doi.org/10.1109/ICRA.2016.7487784
Maddukuri, S. C., Heidl, W., Eitzinger, C., & Pichler, A. (2016). Structural Synthesis based on PCA: Methodology and Evaluation. 348–355. https://doi.org/10.5220/0005721403480355
Plasch, M., Ebenhofer, G., Hofmann, M., Rooker, M., Akkaladevi, S., & Pichler, A. (2016). Workspace Sharing Assembly Robots: Applying IEC 61499 to System Integration and Application Development. 397–422. https://doi.org/10.1201/b19391-23
Weichhart, G., & Hämmerle, A. (2016). Multi-actor architecture for schedule optimisation based on lagrangian relaxation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9872 LNAI, 190–197. https://doi.org/10.1007/978-3-319-45889-2_14
Wögerer, C., Mühlberger, M., & Ikeda, M. (2016). ADDMANU – An Austrian Lighthouse Project for Additive Manfacturing. c, 35–40.
Akkaladevi, S., & Eitzinger, C. (2015). Performance Evaluation of a Cognitive Robotic System. Austrian Robotic Workshop, Klagenfurt, Austria, 43(0), 7–9.
Akkaladevi, S., Heindl, C., Angerer, A., & Minichberger, J. (2015). Action Recognition for Industrial Applications using Depth Sensors Action Recognition for Industrial Applications using Depth Sensors. 43(November), 1–4.
Zhou, K., Rooker, M., Akkaladevi, S. C., Fritz, G., & Pichler, A. (2015). How industrial robots benefit from affordances. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8926, 455–458. https://doi.org/10.1007/978-3-319-16181-5_35
Plasch, M., Hofmann, M., Ebenhofer, G., & Rooker, M. (2014). Reduction of development time by using scriptable IEC 61499 function blocks in a dynamically loadable type library. 19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014. https://doi.org/10.1109/ETFA.2014.7005164
Rooker, M., Hofmann, M., Minichberger, J., Ikeda, M., Ebenhofer, G., & Pichler, A. (2014). Quality Inspection performed by a Flexible Robot System. 47–51.
Rooker, M., Hofmann, M., Minichberger, J., Ikeda, M., Ebenhofer, G., Fritz, G., & Pichler, A. (2014). Flexible and assistive quality checks with industrial robots. Proceedings for the Joint Conference of ISR 2014 – 45th International Symposium on Robotics and Robotik 2014 – 8th German Conference on Robotics, ISR/ROBOTIK 2014, 184–189.
Akkaladevi, S. C., & Eitzinger, C. (2013). DARWIN – D extrous A ssembler R obot W orking with embodied INtelligence ). 43(0), 7252.
Capco, J., Rooker, M., & Pichler, A. (2013). RRT planner for the binpicking problem. 9th International Workshop on Robot Motion and Control, RoMoCo 2013 – Workshop Proceedings, 1, 154–160. https://doi.org/10.1109/RoMoCo.2013.6614601
Hämmerle, A., & Ankerl, M. (2013). Solving a vehicle routing problem with ant colony optimisation and stochastic ranking. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8111 LNCS(PART 1), 259–266. https://doi.org/10.1007/978-3-642-53856-8-33
Plasch, M., Ebenhofer, G., Hofmann, M., Bauer, H., Wögerer, C., Rooker, M., & Pichler, A. (2013). Ein modulares Roboterassistenzsystem zur Effizienzsteigerung in der Produktion. Internationales Forum Meachtronik.
Rooker, M., Angerer, A., Wallhoff, F., Blume, J., Bannatt, A., Ferrara, P., Olarra, A., Kiirikki, J., & Pichler, A. (2013). Flexible Assistance System for Packaging Electronic Consumer Goods using Industrial Robots *.
Plasch, M., Pichler, A., & Bauer, H. (2012). A Plug & Produce Approach to Design Robot Assistants in a Sustainable Manufacturing Environment. 22nd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2012), 43(0), 8. http://www.locobot.eu/wp-content/uploads/2011/02/A-Plug-Produce-Approach-to-Design-Robot-Assistants-in-a-Sustainable-Manufacturing-Environment_FAIM2012.pdf
Wögerer, C., Bauer, H., Rooker, M., Ebenhofer, G., Rovetta, A., Robertson, N., & Pichler, A. (2012). LOCOBOT – Low cost toolkit for building robot co-workers in assembly lines. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7507 LNAI(PART 2), 449–459. https://doi.org/10.1007/978-3-642-33515-0_45
Ankerl, M., & Hämmerle, A. (2009). Applying Ant colony optimisation to dynamic pickup and delivery. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5717 LNCS, 721–728. https://doi.org/10.1007/978-3-642-04772-5_93
Pichler, A., Ikeda, M., & Stübl, G. (2009). Ein lernfähiger adaptiver Roboter für Handhabung komplexer hochvarianter Teile. Internationales Forum Meachtronik.
Rooker, M. N., Ebenhofer, G., & Strasser, T. (2009). Reconfigurable control in distributed automation systems. Proceedings of the 2009 ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR 2009, 705–714.
Rooker, M. N., Strasser, T., Ebenhofer, G., Hofmarm, M., & Osuna, R. V. (2008). Modeling flexible mechatronical based assembly systems through simulation support. IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, 452–455. https://doi.org/10.1109/ETFA.2008.4638434
Strasser, T., Rooker, M. N., & Ebenhofer, G. (2008). Distributed Control Concept for a 6-DOF Reconfigurable Robot Arm. Control.
Hämmerle, A., Karageorgos, A., Pirker, M., Reitbauer, A., & Weichhart, G. (2004). A role-based infrastructure for customised agent system development in supply networks. Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics, 5, 4692–4699. https://doi.org/10.1109/ICSMC.2004.1401272
Stalker, I. D., Mehandjiev, N. D., Weichhart, G., & Fessl, K. (2004). Agents for Decentralised Process Design. Proceedings of the 12th International Conference on Cooperative Information Systems, 23–25.
Hämmerle, A., Karageorgos, A., Mehandjiev, N., & Weichhart, G. (2003). A GENTCITIES TECHNICAL NOTE Integrated Logisitcs and Prodction Planning. Agentcities Technote Series, 1–15.
Hämmerle, A., Weichhart, G., & Fessl, K. (2002). The MaBE project: An agent-based environment for business networks. Proceedings – International Workshop on Database and Expert Systems Applications, DEXA, 2002-Janua, 646–650. https://doi.org/10.1109/DEXA.2002.1045971
Hämmerle, A., Schleicher, M., Kollingbaum, M., & Lane, M. (1999). Skilled Resources in Holonic Manufacturing Systems.
Hämmerle, A., Dupré, C., & Hingerl, K. (1997). Distributed Knowledge and an Approach To Path-Planning. 8th DAAAM INTERNATIONAL SYMPOSIUM, October.
Akkaladevi, S., Ebenhofer, G., & Matthias, P. (n.d.). Benchmarking a Cognitive System. 4321–4323.
Hofmann, M., Ikeda, M., Minichberger, J., Fritz, G., & Pichler, A. (n.d.). Automatic Coverage Planning System for Quality Inspection of Complex Objects *. 3–4.
Hofmann, M., Propst, M., Ikeda, M., Pichler, A., Spitzer, F., & Froschauer, R. (2023). Framework for Reducing the Complexity of Programming Robot Skills. Lecture Notes in Mechanical Engineering, 592–604. https://doi.org/10.1007/978-3-031-17629-6_62
Sackl, A., Pretolesi, D., Burger, S., Ganglbauer, M., & Tscheligi, M. (2022). Social Robots as Coaches: How Human-Robot Interaction Positively Impacts Motivation in Sports Training Sessions. RO-MAN 2022 – 31st IEEE International Conference on Robot and Human Interactive Communication: Social, Asocial, and Antisocial Robots, 141–148. https://doi.org/10.1109/RO-MAN53752.2022.9900600
Akkaladevi, S. C., Plasch, M., Chitturi, N. C., Hofmann, M., & Pichler, A. (2020). Programming by interactive demonstration for a human robot collaborative assembly. Procedia Manufacturing, 51(2019), 148–155. https://doi.org/10.1016/j.promfg.2020.10.022
Chandra, S., Plasch, M., Chowdhary, N., & Pichler, A. (2020). ScienceDirect Programming by Interactive Demonstration for a Human Robot Collaborative Assembly. 00(2019), 1–8.
Chitturi, N. C., Kulha, P., Plasch, M., Ganglbauer, M., Weinbacher, A., & Pichler, A. (2020). Intuitive Human-Robot Interaction with Inkjet Printed Capacitive Sensors. March, 1–6.
Ganglbauer, M., Plasch, M., Ikeda, M., & Pichler, A. (2020). ScienceDirect Human in the loop online estimation of robotic speed limits for safe human robot collaboration. 00(2019), 0–6.
AKKALADEVI, Sharath Chandra, et al. Programming-free approaches for human–robot collaboration in assembly tasks. In: Advanced Human-Robot Collaboration in Manufacturing. Cham: Springer International Publishing, 2021. S. 283-317.
HOFMANN, Michael, et al. Towards Human and Robot Collaborative Ergonomic Handling of Long Parts with a Loose Grip. In: Smart Technologies for Precision Assembly: 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, Virtual Event, December 14–15, 2020, Revised Selected Papers 9. Springer International Publishing, 2021. S. 249-259.
PROPST, Matthias, et al. Human and Workcell Event Recognition and Its Application Areas in Industrial Assembly. In: Smart Technologies for Precision Assembly: 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, Virtual Event, December 14–15, 2020, Revised Selected Papers 9. Springer International Publishing, 2021. S. 260-275.
Akkaladevi, S. C., Pichler, A., Plasch, M., Ikeda, M., & Hofmann, M. (2019). Skill-based programming of complex robotic assembly tasks for industrial application. Elektrotechnik Und Informationstechnik, 136(7), 326–333. https://doi.org/10.1007/s00502-019-00741-4
Chitturi, N. C., Ganglbauer, M., Plasch, M., Kulha, P., & Pichler, A. (2019). HolisafeHRC: Holistic Safety Concepts ni Human-Robot Collaboration. Systems Biology, 71–75. https://doi.org/10.3217/978-3-85125-663-5-11
Ikeda, M., Ganglbauer, M., Ashok, P., Maddukuri, S., Hofmann, M., & Pichler, A. (2019). Instrumented Tool based Robot Programming – Parameterization of Screwing Process Macros. Procedia Manufacturing, 38(2019), 415–422. https://doi.org/10.1016/j.promfg.2020.01.053
Weichhart, G., Ferscha, A., Mutlu, B., Brillinger, M., Diwold, K., Lindstaedt, S., Schreck, T., & Mayr-Dorn, C. (2019). Human/machine/roboter: technologies for cognitive processes. Elektrotechnik Und Informationstechnik, 136(7), 313–317. https://doi.org/10.1007/s00502-019-00740-5
Wögerer, C., Plasch, M., Tscheligi, M., & Lampl, S. E. (2019). Industrial assistance as an I4.0 topic—MMassist: assistance in production in the context of human–machine cooperation. Smart Innovation, Systems and Technologies, 155, 399–410. https://doi.org/10.1007/978-981-13-9271-9_33
Ikeda, M., Ebenhofer, G., Minichberger, J., Stübl, G., Pichler, A., Huber, A., & Weiss, A. (2018). User Experience in kollaborativen Roboteranwendungen. 1–12.
Ikeda, M., Maddukuri, S., Hofmann, M., Pichler, A., Zhang, X., Polydoros, A., Piater, J., Winkler, K., Brenner, K., Harton, I., & Neugebauer, U. (2018). FlexRoP – flexible, assistive robots for customized production (pp. 53–58). https://doi.org/10.15203/3187-22-1-11
Weichhart, G. (2018). Representing processes of human robot collaboration. CEUR Workshop Proceedings, 2074.
Weichhart, G., Åkerman, M., Akkaladevi, S. C., Plasch, M., Fast-Berglund, Å., & Pichler, A. (2018). Models for Interoperable Human Robot Collaboration. IFAC-PapersOnLine, 51(11), 36–41. https://doi.org/10.1016/j.ifacol.2018.08.231
Wögerer, C., Plasch, M., Tscheligi, M., Egger-Lampl, S., & Pichler, A. (2018). MMAssist_II: Assistance in production in the context of human – machine cooperation. 49–52. https://doi.org/10.15203/3187-22-1-10
Akkaladevi, S. C., Plasch, M., & Pichler, A. (2017). Skill-basiertes Lernen für Montageprozesse. Elektrotechnik Und Informationstechnik, 134(6), 312–315. https://doi.org/10.1007/s00502-017-0514-2
Ikeda, M., Ebenhofer, G., Minichberger, J., Fritz, G., Pichler, A., Huber, A., & Weiss, A. (2017). User-Centered Assistive Robotics for Production Human-Robot Interaction Concepts in the AssistMe project. 45–50. https://doi.org/10.3217/978-3-85125-524-9-09
Pichler, A., Akkaladevi, S. C., Ikeda, M., Hofmann, M., Plasch, M., Wögerer, C., & Fritz, G. (2017). Towards Shared Autonomy for Robotic Tasks in Manufacturing. Procedia Manufacturing, 11(June), 72–82. https://doi.org/10.1016/j.promfg.2017.07.139
Sharath Chandra, A., Plasch, M., Eitzinger, C., & Rinner, B. (2017). Context enhanced multi object tracker for human robot collaboration. ACM/IEEE International Conference on Human-Robot Interaction, 61–62. https://doi.org/10.1145/3029798.3038406
Akkaladevi, S. C., & Heindl, C. (2016). Action recognition for human robot interaction in industrial applications. 2015 IEEE International Conference on Computer Graphics, Vision and Information Security, CGVIS 2015, 94–99. https://doi.org/10.1109/CGVIS.2015.7449900
Chowdhary, M. S., & Rooker Martijn, et al. (2015). Towards Safe Human Robot Collaboration: Sonar Based Collision Avoidance for Robot’s End-Effector. Austrian Robotics Workshop 2015, 36–37.
Rooker, M., Maddukuri, S., Minichberger, J., Pichler, A., Feyrer, C., & Nöhmayer, H. (2015). Interactive Workspace Modelling for Assistive Robot Systems with the Aid of Ultrasonic Sensors. 43(July). https://doi.org/10.13140/RG.2.1.3056.8807
Barattini, P., Morand, C., Almajai, I., Robertson, N., Hopgood, J., Ferrara, P., Bonasso, M., Strassmair, C., Rottenbacher, M., Staehr, M., Neumann, R., Tornari, M., Rovetta, A., Plasch, M., Bauer, H., Capco, J., Woegerer, C., & Pichler, A. (2013). Towards tailor made robot co workers based on a plug&produce framework. Proceedings – 2013 IEEE International Symposium on Assembly and Manufacturing, ISAM 2013, 1–7. https://doi.org/10.1109/isam.2013.6643496
Wögerer, C., Rooker, M., Angerer, A., Blume, J., Bannatt, A., Ferrara, P., Kiirikki, J., & Pichler, A. (2013). A Robotic Assistance System for Flexible Packaging of Consumer Goods in Electronic Industry. Raad 2013, 1–8.
Plasch, M., Pichler, A., & Rooker, M. (2012). Simplified Programming of Modular Robotic Systems Based on Workflow Modeling. Austrian Robotics Workshop.
Plasch, M., Pichler, A., Rooker, M., & Ebenhofer, G. (2012). Ein modellbasierter Plug&Produce-Ansatz für Roboterassistenzsysteme in der Produktion. Internationales Forum Meachtronik.
Oppl, S., & Weichhart, G. (2005). Requirements for Collaborative Process Design. Workshop-Proceedings Der 5. Fachuebergreifenden Konferenz Mensch Und Computer 2005, 197, 15–22.
Your Contact
Dr. Andreas Pichler
CTO
+43 72 52 885 306
andreas.pichler@nullprofactor.at
