Autonomous Robots

, Volume 41, Issue 7, pp 1487–1499 | Cite as

A cable-driven robot for architectural constructions: a visual-guided approach for motion control and path-planning

  • Andry Maykol Pinto
  • Eduardo Moreira
  • José Lima
  • José Pedro Sousa
  • Pedro Costa
Article

Abstract

Cable-driven robots have received some attention by the scientific community and, recently, by the industry because they can transport hazardous materials with a high level of safeness which is often required by construction sites. In this context, this research presents an extension of a cable-driven robot called SPIDERobot, that was developed for automated construction of architectural projects. The proposed robot is formed by a rotating claw and a set of four cables, enabling four degrees of freedom. In addition, this paper proposes a new Vision-Guided Path-Planning System (V-GPP) that provides a visual interpretation of the scene: the position of the robot, the target and obstacles location; and optimizes the trajectory of the robot. Moreover, it determines a collision-free trajectory in 3D that takes into account the obstacles and the interaction of the cables with the scene. A set of experiments make possible to validate the contribution of V-GPP to the SPIDERobot while operating in realistic working conditions, as well as, to evaluate the interaction between the V-GPP and the motion controlling system. The results demonstrated that the proposed robot is able to construct architectural structures and to avoid collisions with obstacles in their working environment. The V-GPP system localizes the robot with a precision of 0.006 m, detects the targets and successfully generates a path that takes into account the displacement of cables. Therefore, the results demonstrate that the SPIDERobot can be scaled up to real working conditions.

Keywords

Cable-driven robot Vision-guided positioning Path-planning Scene interpretation 

References

  1. Aoude, G., Luders, B., Joseph, J., Roy, N., & How, J. (2013). Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns. Autonomous Robots, 35(1), 51–76.CrossRefGoogle Scholar
  2. Bhattacharya, S., Likhachev, M., & Kumar, V. (2012). Topological constraints in search-based robot path planning. Autonomous Robots, 33(3), 273–290.CrossRefGoogle Scholar
  3. Borgstrom, P., Jordan, B., Borgstrom, B., Stealey, M., Sukhatme, G., Batalin, M., et al. (2009). Nims-pl: A cable-driven robot with self-calibration capabilities. IEEE Transactions on Robotics, 25(5), 1005–1015.CrossRefGoogle Scholar
  4. Borgstrom, PH., Borgstrom, NP., Stealey, MJ., Jordan, B., Sukhatme, G., Batalin, MA., & Kaiser, WJ. (2008). Generation of energy efficient trajectories for nims3d, a three-dimensional cabled robot. In IEEE International Conference on Robotics and Automation (pp. 2222–2227), IEEE.Google Scholar
  5. Bosscher, P, I. I., RLW, Bryson, L. S., & Castro-Lacouture, D. (2007). Cable-suspended robotic contour crafting system. Automation in Construction, 17(1), 45–55. doi:10.1016/j.autcon.2007.02.011.
  6. Costa, P., Moreira, A. P., & Costa, P. G. (2009). Real-time path planning using a modified a* algorithm. In Conference on mobile robots and competitions (pp. 222–227).Google Scholar
  7. Dallej, T., Gouttefarde, M., Andreff, N., Dahmouche, R., & Martinet, P. (2012). Vision-based modeling and control of large-dimension cable-driven parallel robots. In 2012 IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 1581–1586).Google Scholar
  8. Gagliardini, C., & Gouttefarde, G. (2015). Optimal path planning and reconfiguration strategy for reconfigurable cable-driven parallel robots. In IEEE international conference on robotics and automation (ICRA).Google Scholar
  9. German, J., Jablokow, K. W., & Cannon, D. J. (2001). The cable array robot: Theory and experiment. IEEE International Conference on Robotics and Automation, IEEE, 3, 2804–2810.Google Scholar
  10. Gouttefarde, M., Daney, D., & Merlet, J. P. (2011). Interval-analysis-based determination of the wrench-feasible workspace of parallel cable-driven robots. IEEE Transactions on Robotics, 27(1), 1–13. doi:10.1109/TRO.2010.2090064.CrossRefMATHGoogle Scholar
  11. Hastak, M. (1998). Advanced automation or conventional construction process. Automation in Construction, 7(4), 299–314. doi:10.1016/S0926-5805(98)00047-8.CrossRefGoogle Scholar
  12. Julia, M., Gil, A., & Reinoso, O. (2012). A comparison of path planning strategies for autonomous exploration and mapping of unknown environments. Autonomous Robots, 33(4), 427–444.CrossRefGoogle Scholar
  13. Korayem, M. H., Tourajizadeh, H., Zehfroosh, A., & Korayem, A. H. (2014). Optimal path planning of a cable-suspended robot with moving boundary using optimal feedback linearization approaching. Nonlinear Dyn., 78(2), 1515–1543.CrossRefMATHGoogle Scholar
  14. Lahouar, S., Ottaviano, E., Zeghoul, S., Romdhane, L., & Ceccarelli, M. (2009). Collision free path-planning for cable-driven parallel robots. Robotics and Autonomous Systems, 57(11), 1083–1093. doi:10.1016/j.robot.2009.07.006.CrossRefGoogle Scholar
  15. Moreira, E., Pinto, A. M., Costa, P., Moreira, A. P., Veiga, G., Lima, J., Sousa, J. P., & Costa, P. (2015). Cable robot for non-standard architecture and construction: A dynamic positioning system. In IEEE International Conference on Industrial Technology (ICIT) (Vol. 1, pp. 3184–3189), IEEE.Google Scholar
  16. Mourad Ismail, LR Lahouar Samir. (2013). Dynamic in path planning of a cable driven robot. In Design and modeling of mechanical systems. Lecture notes in mechanical engineering (pp. 11-18).Google Scholar
  17. Oh, S. R., & Agrawal, S. (2006). Generation of feasible set points and control of a cable robot. IEEE Transactions on Robotics, 22(3), 551–558.CrossRefGoogle Scholar
  18. Ottaviano, E., Ceccarelli, M., & De Ciantis, M. (2007) A 4-4 cable-based parallel manipulator for an application in hospital environment. In Mediterranean conference on control automation (pp 1–6).Google Scholar
  19. Pinto, A., Costa, P., Moreira, A. P., Rocha, L. F., Veiga, G., & Moreira, E. (2015). Evaluation of depth sensors for robotic applications. In 2015 IEEE international conference on autonomous robot systems and competitions (ICARSC) (pp. 139–143).Google Scholar
  20. Pinto, A. M., Moreira, A. P., Correia, M. V., & Costa, P. G. (2014). A flow-based motion perception technique for an autonomous robot system. Journal of Intelligent and Robotic Systems, 75(3), 475–492.CrossRefGoogle Scholar
  21. Trevisani, A. (2010). Underconstrained planar cable-direct-driven robots: A trajectory planning method ensuring positive and bounded cable tensions. Mechatronics, 20(1), 20–44.CrossRefGoogle Scholar
  22. Usher, K., Winstanley, G., & Carnie, R. (2005). Air vehicle simulator: an application for a cable array robot. In IEEE international conference on robotics and automation (ICRA) (pp. 2241–2246), IEEE.Google Scholar
  23. Vh, P., Heikkil, T., Kilpelinen, P., Jrviluoma, M., & Gambao, E. (2013). Extending automation of building construction survey on potential sensor technologies and robotic applications. Automation in Construction, 36, 168–178. doi:10.1016/j.autcon.2013.08.002.CrossRefGoogle Scholar
  24. Yu, H., & Beard, R. (2013). A vision-based collision avoidance technique for micro air vehicles using local-level frame mapping and path planning. Autonomous Robots, 34(1–2), 93–109.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.INESC TEC and the Faculty of EngineeringUniversity of PortoPortoPortugal
  2. 2.INESC TECPortoPortugal
  3. 3.INESC TEC and Polytechnic Institute of BragançaPortoPortugal
  4. 4.Faculty of ArchitectureUniversity of PortoPortoPortugal

Personalised recommendations