Skip to main content
SpringerLink
Log in

Human–computer cooperation platform for developing real-time robotic applications

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

This paper presents a human–computer cooperation platform, which permits the coordination between the user and the tool to improve the development of real-time control applications (e.g., mobile robots). These applications have functional (robot objectives) and temporal requirements to accomplish (deadlines guarantee of tasks). The simulation tool has been designed in order to permit the testing and validation of these two requirements. To this end, the tool is composed of two independent simulators interconnected through a shared memory: the robot simulator (functional level) and the real-time task scheduler simulator (task execution level). Robotic applications can be defined with the robot simulator while the real-time scheduler simulator permits to analyze the schedulability of the robotic tasks. The real-time task simulator incorporates a flexible task model where the task temporal parameters (e.g., computation time) adapt to the requirements of the application (e.g., number of objects in scenes); thus, the use of the CPU is not overestimated. A key issue of the framework is the human–computer interface, which allows the monitoring of different parameters of the application: robot objectives, task schedule, robot speed, computation time, CPU utilization, deadline misses. The usefulness of the simulation tool is shown through different robotic navigation experiments. Finally, the simulation tool has been used to evaluate the proposed flexible model of tasks compared to a traditional fixed temporal parameters task model. Results show that the robot fulfills the objectives earlier, about 32% on average, and consumes on average about 15% less CPU to accomplish the objectives.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Dominguez C, Hassan H, Crespo A (2007) Real-time embedded architecture for pervasive robots. In: The 2007 International Conference on Intelligent Pervasive Computing (IPC 2007), pp 531–536

  2. Audsley NC, Burns A, Davis RI, Tindell KW, Wellings AJ (1995) Fixed priority pre-emptive scheduling: an historical perspective. Real Time Syst 8(2–3):173–198

    Article  Google Scholar 

  3. Stankovic JA, Lee I, Mok A, Rajkumar R (2005) Opportunities and obligations for physical computing systems. Computer 38(11):23–31

    Article  Google Scholar 

  4. Zhen Z, Qixin C, Lo C, Lei Z (2009) A CORBA-based simulation and control framework for mobile robots. Robotica 27(3):459

    Article  Google Scholar 

  5. Ferretti G, Magnani G, Porrati P, Rizzi G, Rocco P, Rusconi A (2008) Real-time simulation of a space robotic arm. In: IROS

  6. Qadi A, Goddard S, Huang J, Farritor S (2005) A performance and schedulability analysis of an autonomous mobile robot. In: 17th Euromicro Conference on Real-Time Systems (ECRTS’05), pp 239–248

  7. Goud GR, Sharma N, Ramamritham K, Malewar S (2006) Efficient real-time support for automotive applications: a case study. In: 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA’06), pp 335–341

  8. Pedreiras P, Luis A (2003) The flexible time-triggered (FTT) paradigm: an approach to QoS management in distributed real-time systems. In: Proceedings International Parallel and Distributed Processing Symposium, p 9

  9. Li H, Sweeney J, Ramamritham K, Grupen R, Shenoy P (2003) Real-time support for mobile robotics. In: The 9th IEEE Real-Time and Embedded Technology and Applications Symposium. Proceedings, pp 10–18

  10. Chetto H, Chetto M (1989) Some results of the earliest deadline scheduling algorithm. IEEE Trans Softw Eng 15(10):1261–1269

    Article  MathSciNet  MATH  Google Scholar 

  11. Liu R, Zhang X (2017) Systems of natural-language-facilitated human-robot cooperation: a review. arXiv:1701.08269v2

  12. Tsarouchi P, Makris S, Chryssolouris G (2016) Human–robot interaction review and challenges on task planning and programming. Int J Comput Integr Manuf 29(8):916–931

    Article  Google Scholar 

  13. Moniz A (2013) Organizational concepts and interaction between humans and robots in industrial environments. In: IEEE-RAS-IARP Joint Workshop on Technical Challenges for Dependable Robots in Human Environment, Tokyo

  14. Mayer MP, Odenthal B, Faber M, Winkelholz C, Schlick CM (2014) Cognitive engineering of automated assembly processes. Hum Factors Ergon Manuf Serv Ind 24(3):348–368

    Article  Google Scholar 

  15. Agostini A, Torras C, Wörgötter F (2011) Integrating task planning and interactive learning for robots to work in human environments. In: IJCAI

  16. Kwon W, Suh I (2014) Planning of proactive behaviors for human–robot cooperative tasks under uncertainty. Knowl Based Syst 72:81–95

    Article  Google Scholar 

  17. Chen F, Sekiyama K, Sasaki H, Huang J, Sun B, Fukuda T (2011) Assembly strategy modeling and selection for human and robot coordinated cell assembly. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 4670–4675

  18. Gombolay M, Wilcox R, Diaz A, Yu F (2013) Towards successful coordination of human and robotic work using automated scheduling tools: an initial pilot study. In: Proceedings of Robotics: Science and Systems, Human–Robot Collaboration Workshop

  19. Gombolay MC, Gutierrez RA, Clarke SG, Sturla GF, Shah JA (2015) Decision-making authority, team efficiency and human worker satisfaction in mixed human–robot teams. Auton Robots 39(3):293–312

    Article  Google Scholar 

  20. Frontoni E, Mancini A, Caponetti F, Zingaretti P (2006) A framework for simulations and tests of mobile robotics tasks. In: 2006 14th Mediterranean Conference on Control and Automation, pp 1–6

  21. I. Embarcadero Technologies, C++ Builder 10.2. https://www.embarcadero.com/

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering (DISCA), Universitat Politècnica de València (UPV), València, Spain

    Carlos Domínguez, Juan-Miguel Martínez, Jose V. Busquets-Mataix & Houcine Hassan

Authors
  1. Carlos Domínguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan-Miguel Martínez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jose V. Busquets-Mataix
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Houcine Hassan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jose V. Busquets-Mataix.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Domínguez, C., Martínez, JM., Busquets-Mataix, J.V. et al. Human–computer cooperation platform for developing real-time robotic applications. J Supercomput 75, 1849–1868 (2019). https://doi.org/10.1007/s11227-018-2343-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-018-2343-4

Keywords

Search

Navigation