Abstract
Robot path planning in a cluttered environment can be a challenging task. In this paper, a new algorithm is proposed to perform path planning of a point-to-point motion of an industrial manipulator. The algorithm starts from a simple joint interpolated movement and, by computing collision detection along the path, creates a set of via-points that form a path which allows the robot to move to the end position without any collision. In the paper, the new algorithm is presented and compared in simulation to other methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Many other functions could be used in place of the third-degree polynomial function.
References
Agrawal, O.P., Yangsheng, X.: On the global optimum path planning for redundant space manipulators. IEEE Trans. Syst. Man Cybern. 24(9), 1306–1316 (1994)
Bertram, D., Kuffner, J., et al.: An integrated approach to inverse kinematics and path planning for redundant manipulators. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006, pp. 1874–1879. IEEE (2006)
Bottin, M., Boschetti, G., Rosati, G.: A novel collision avoidance method for serial robots. In: IFToMM Symposium on Mechanism Design for Robotics, pp. 293–301. Springer (2018)
Bottin, M., Rosati, G.: Trajectory optimization of a redundant serial robot using cartesian via points and kinematic decoupling. Robotics 8(4), 101 (2019)
Carbone, C., Ciniglio, U., et al.: A novel 3D geometric algorithm for aircraft autonomous collision avoidance. In: Proceedings of the 45th IEEE Conference on Decision and Control, pp. 1580–1585. IEEE (2006)
Faccio, M., Bottin, M., Rosati, G.: Collaborative and traditional robotic assembly: a comparison model. Int. J. Adv. Manuf. Technol. 102, 1–18 (2019)
Hrabar, S.: 3D path planning and stereo-based obstacle avoidance for rotorcraft UAVs. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 807–814. IEEE (2008)
Kavraki, L.E., Svestka, P., et al.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Automat. 12(4), 566–580 (1996)
Lagarias, J.C., Reeds, J.A., et al.: Convergence properties of the nelder-mead simplex method in low dimensions. SIAM J. Optim. 9(1), 112–147 (1998)
Lim, Z.Y., Ponnambalam, S.G., et al.: Nature inspired algorithms to optimize robot workcell layouts. Appl. Soft Comput. 49, 570–589 (2016)
Lozano-Pérez, T., Wesley, M.A.: An algorithm for planning collision-free paths among polyhedral obstacles. Commun. ACM 22(10), 560–570 (1979)
Mac, T.T., Copot, C., et al.: Heuristic approaches in robot path planning: a survey. Robot. Auton. Syst. 86, 13–28 (2016)
Rosati, G., Faccio, M., et al.: Fully flexible assembly systems (f-fas): a new concept in flexible automation. Assembly Autom. 33(1), 8–21 (2013)
Saska, M., Macas, M., et al.: Robot path planning using particle swarm optimization of ferguson splines. In: 2006 IEEE Conference on Emerging Technologies and Factory Automation, pp. 833–839. IEEE (2006)
Seereeram, S., Wen, J.T.: A global approach to path planning for redundant manipulators. IEEE Trans. Robot. Autom. 11(1), 152–160 (1995)
Weghe, M V., Ferguson, D., et al.: Randomized path planning for redundant manipulators without inverse kinematics. In: 2007 7th IEEE-RAS International Conference on Humanoid Robots, pp. 477–482. IEEE (2007)
Yoshida, E., Sakaguchi, Esteves C., T, Yokoi K., et al.: Planning 3-d collision-free dynamic robotic motion through iterative reshaping. IEEE Trans. Robot. 24(5), 1186–1198 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Bottin, M., Rosati, G., Cipriani, G. (2021). Iterative Path Planning of a Serial Manipulator in a Cluttered Known Environment. In: Niola, V., Gasparetto, A. (eds) Advances in Italian Mechanism Science. IFToMM ITALY 2020. Mechanisms and Machine Science, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-030-55807-9_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-55807-9_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-55806-2
Online ISBN: 978-3-030-55807-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)