Abstract
Current packaging machine vendors do not provide any automated mechanism for blank feeding and the state of the art is to have a human operator dedicated to feed the blank piles to the packaging machine. This is a tedious, repetitive and tiring task. This also results in problems with unintentional errors, such as using the wrong pile of blanks. An alternative solution is the use of a fixed robotic arm surrounded by a protective cage. However, this solution is restricted to a single packaging machine, a unique type of blank shapes and does not cooperate with humans. TIMAIRIS is a joint effort between IMA S.p.A., Italy, (IMA) and the Universidade de Aveiro, Portugal, (UAVR), promoted by the European Robotics Challenges (EuRoC) project. Together, we propose a system based on a mobile manipulator for flexible, autonomous and collaborative blank feeding of packaging machines on industrial shop floor. The system provides a software architecture that allows a mobile robot to take high level decisions on how the task should be executed, which can depend on variables such as the number of packaging machines to feed and the rate of blank consumption at each one. Through a computer vision system, blanks of different shapes and sizes are correctly identified for adequate manipulation. The manipulation of the piles of blanks is performed using a single arm using compliant modes of operation to increase manipulation safety and robustness. Additionally, it has a safe navigation system that allows the robot to be integrated in an industrial environment where humans are present. Finally, it provides an enhanced multimodal interaction between human and robot that can be adapted to the environment and operator characteristics to make communication intuitive, redundant and safe.
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References
Hermann, M., Pentek, T., Otto, B.: Design principles for industrie 4.0 scenarios. In: 2016 49th Hawaii International Conference on System Sciences (HICSS), pp. 3928–3937. IEEE (2016)
Bischoff, R., Guhl, T.: The strategic research agenda for robotics in Rurope [industrial activities]. IEEE Robot. Autom. Mag. 17(1), 15–16 (2010)
Siciliano, B., Caccavale, F., Zwicker, E., Achtelik, M., Mansard, N., Borst, C., Achtelik, M., Jepsen, N.O., Awad, R., Bischoff, R.: Euroc—the challenge initiative for European robotics. In: ISR/Robotik 2014; 41st International Symposium on Robotics, pp. 1–7. VDE (2014)
Pedrocchi, N., Vicentini, F., Matteo, M., Tosatti, L.M.: Safe human-robot cooperation in an industrial environment. Int. J. Adv. Robot. Syst. 10(1), 27 (2013)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, p. 5. Kobe, Japan (2009)
Pedrosa, E., Lau, N., Pereira, A., Cunha, B.: A skill-based architecture for pick and place manipulation tasks. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) Progress in Artificial Intelligence, pp. 457–468, Coimbra, Portugal, September 2015. Springer International Publishing
Amaral, F., Pedrosa, E., Lim, G.H., Shafii, N., Pereira, A., Azevedo, J.L., Cunha, B., Reis, L.P., Badini, S., Lau, N.: Skill-based anytime agent architecture for logistics and manipulation tasks: EuRoC Challenge 2, Stage II—Realistic Labs: Benchmarking. In: 2017 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2017, pp. 198–203 (2017)
Rusu, R.B., Marton, Z.C., Blodow, N., Dolha, M., Beetz, M.: Towards 3D point cloud based object maps for household environments. Robot. Auton. Syst. 56(11), 927–941 (2008). Semantic Knowledge in Robotics
Rusu, R.B.: Semantic 3D object maps for everyday manipulation in human living environments. Ph.D. Thesis, Computer Science department, Technische Universitaet Muenchen, Germany, October 2009
Hamidreza Kasaei, S., Seabra Lopes, L., Tomé, A.M., Oliveira, M.: An orthographic descriptor for 3D object learning and recognition. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4158–4163 (2016)
Pedrosa, E., Pereira, A., Lau, N.: A scan matching approach to SLAM with a dynamic likelihood field. In: 2016 International Conference on Autonomous Robot Systems and Competitions (ICARSC), pp. 35–40, Portugal, Bragança. IEEE (2016)
Lim, G.H., Pedrosa, E., Amaral, F., Lau, N., Pereira, A., Dias, P., Azevedo, J.L., Cunha, B., Reis, L.P.: Rich and robust human-robot interaction on gesture recognition for assembly tasks. In: 2017 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2017, pp. 159–164 (2017)
Gleeson, B., MacLean, K., Haddadi, A., Croft, E., Alcazar, J.: Gestures for industry: intuitive human-robot communication from human observation. In: Proceedings of the 8th ACM/IEEE International Conference on Human-Robot Interaction, pp. 349–356. IEEE Press (2013)
Lim, G.H., Suh, I.H.: Robust robot knowledge instantiation for intelligent service robots. Intell. Serv. Robot. 3(2), 115–123 (2010)
Norvig, P.: Natural language corpus data. In: Beautiful Data, pp. 219–242 (2009)
Lowe, D.G.: Object recognition from local scale-invariant features. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision, vol. 2, pp. 1150–1157. IEEE (1999)
Tudico, A., Lau, N., Pedrosa, E., Amaral, F., Mazzotti, C., Carricato, M.: Improving and benchmarking motion planning for a mobile manipulator operating in unstructured environments. In: Portuguese Conference on Artificial Intelligence, pp. 498–509. Springer (2017)
Lim, G.H., Pedrosa, E., Amaral, F., Dias, R., Pereira, A., Lau, N., Azevedo, J., Cunha, B., Reis, L.P.: Human-robot collaboration and safety management for logistics and manipulation tasks. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds.) Advances in Intelligent Systems and Computing, vol. 694, pp. 15–27. Portugal. Springer International Publishing, Porto (2017)
Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)
Coles, A., Coles, A., Fox, M., Long, D.: Forward-chaining partial-order planning. In: Proceedings of the Twentieth International Conference on International Conference on Automated Planning and Scheduling, ICAPS’10, pp. 42–49. AAAI Press (2010)
Cashmore, M., Fox, M., Long, D., Magazzeni, D., Ridder, B., Carreraa, A., Palomeras, N., Hurtós, N., Carrerasa, M.: ROSPlan: planning in the robot operating system. In: Proceedings of the Twenty-Fifth International Conference on International Conference on Automated Planning and Scheduling, ICAPS’15, pp. 333–341. AAAI Press (2015)
Acknowledgements
This work was supported by the EuRoC Project under Grant no. 608849 and by Portuguese National Funds through the FCT—Foundation for Science and Technology, in the context of the project UID/CEC/00127/2019.
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Pedrosa, E. et al. (2020). TIMAIRIS: Autonomous Blank Feeding for Packaging Machines. In: Caccavale, F., Ott, C., Winkler, B., Taylor, Z. (eds) Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users. Springer Tracts in Advanced Robotics, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-030-34507-5_7
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