Abstract
Instead of using the tedious process of turret teaching, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular, circular and torus shaped by providing three converging options named as fast, medium and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using 6 sequences and their options. In order to find a heuristic path on these 2-D configuration maps, the A* algorithm is implemented, which is usually used to find a heuristic path on Cartesian Workspace. Firstly, 4-D configuration space of the double-turret system is obtained by using the method of intersection of point clouds where the bodies in the system are meshed and converted into points. With the help of random simulations, the sequences and the options of these sequences are provided in an appropriate order. A sample path planning was made to examine the performance of the algorithm and thus the converging options. The results obtained for 3 different converging options were simulated on the model of the double-turret system and it was observed that there was no collision between any bodies in these three options. Hence, a collision free motion planning can be carried out for double-turret system operating in a common workspace.
Similar content being viewed by others
References
M. Bahrin, M. Othman, N. H. N. Azli and M. F. Talib, “Industry 4.0: A review on industrial automation and robotic,” Jurnal Teknologi (Sciences and Engineering), pp. 137–143, 2016.
F. Padula and V. Perdereau, “An on-line path planner for industrial manipulators,” International Journal of Advanced Robotic Systems, vol. 10, no. 3, 2013. DOI: https://doi.org/10.5772/55063
S. Yoon, H. Do, and J. Kim, “Collaborative mission and route planning of multi-vehicle systems for autonomous search in marine environment,” Int. J. Control Autom. Syst., vol. 18, no. 3, pp. 546–555, 2020.
M. Reuter, H. Oberc, M. Wannöffel, D. Kreimeier, J. Klippert, P. Pawlicki, and B. Kuhlenkötter, “Learning factories’ trainings as an enabler of proactive workers participation regarding industrie 4.0,” Procedia Manufacturing, pp. 354–360, 2017.
Y. Liu, C. Yu, J. Sheng, and T. Zhang, “Self-collision avoidance trajectory planning and robust control of a dualarm space robot,” Int. J. Control Autom. Syst., vol. 16, no. 6, pp. 2896–2905, 2018.
S. O. Park, M. C. Lee, and J. Kim, “Trajectory planning with collision avoidance for redundant robots using jacobian and artificial potential field-based real-time inverse kinematics,” Int. J. Control Autom. Syst., vol. 18, pp. 2095–2107, 2020.
The requirements for future military robots supporting mobility relevance and possible future role of robotic/unmanned systems for FINABEL land forces, European Land Forces Interoperability Center FINABEL, 2013.
Z. Pan, D. Wang, H. Deng, and K. Li, “A virtual spring method for the multi-robot path planning and formation control,” Int. J. Control Autom. Syst., vol 17, no. 5, pp. 1272–1282, 2019.
J. Zhao, Y. Chao, and Y. Yuan, “A cooperative obstacle-avoidance approach for two-manipulator based on A* algorithm,” International Conference on Intelligent Robotics and Applications (ICIRA), pp. 16–25, 2019.
E. Freund and H. Hoyer, “Real-time path finding in multi-robot systems including obstacle avoidance,” Int J Robotics, vol. 7, no. 1, pp. 42–70, 1988.
Y. Fei, D. Fuqiang, and Z. Xifang, “Collision-free motion planning of dual-arm reconfigurable robots,” Robot.Comput. Manuf., vol. 20, no. 4, pp. 351–357, 2004.
“Multiple cradle launcher,” Roketsan Missiles Inc., https://www.roketsan.com.tr/wpcontent/uploads/2013/05/IDEX-1.pdf (last accessed: April-2020).
“Remote controlled weapon systems,” Aselsan A.a. https://www.aselsan.com.tr/Remote_Controlled_Weapon_Systems_3441.pdf (last accessed: April-2020).
Z. Pan, D. Wang, H. Deng, and K. Li, “A virtual spring method for the multi-robot path planning and formation control,” Int. J. Control Autom. Syst., vol. 17, no. 5, pp. 1272–1282, May 2019.
T. Lozano-Pérez and M. A. Wesley, “An algorithm for planning collision-free paths among polyhedral obstacles,” Commun of the ACM, vol. 22, no. 10, pp. 560–570, 1979.
T. Lozano-Pérez, “Automatic planning of manipulator transfer movements,” IEEE Transactions on Systems, Man and Cybernetics, vol. 11, no. 10, pp. 681–98, October 1981.
T. Lozano-Perez, “Spatial planning: A configuration space approach,” IEEE Transactions on Computers, vol. 32, no. 2, pp. 108–120, February 1983.
J. Pan and D. Manocha, “Efficient configuration space construction and optimization for motion planning,” Engineering, vol. 1, no 1, pp 46–57, 2015.
H. Choset and J. Latombe, “Principles of robot motion: Theory, algorithms, and implementations [Book Review],” IEEE Robotics & Automation Magazine, vol. 12, 2005.
P. Jiménez, F. Thomas, and C. Torras, “3D collision detection: A survey,” Computers & Graphics, vol. 25, no. 2, pp. 269–285, 2001.
T. Liski, 3-D Collision Checking for Improving Machine Operator’s Spatial Awareness, Master Thesis, Aalto University-School of Electrical Engineering, Finland, 2014.
W. Wu, H. Zhu, X. Zhuang, G. Ma, and Y. Cai, “A multishell cover algorithm for contact detection in the three-dimensional discontinuous deformation analysis,” Theoretical and Applied Fracture Mechanics, vol. 72, no. 1, pp. 136–49, 2014.
J. Klein and G. Zachmann, “Point cloud collision detection,” Computer Graphics Forum, vol. 23, no. 3, pp. 567–576, 2004.
J. Schauer and A. Nüchter, “Collision detection between point clouds using an efficient k-d tree implementation,” Advanced Engineering Informatics, vol. 29, no. 3, pp. 440–458, 2015.
W. J. Beksi and N. Papanikolopoulos, “A topology-based descriptor for 3D point cloud modeling: Theory and experiments,” Image and Vision Computing, vol. 88, pp. 84–95, 2019.
J. Han, “An efficient approach to 3D path planning,” Information Sciences, vol. 478, pp. 318–30, April 2019.
Y. Ting, W. I. Lei, and H. C. Jar., “A path planning algorithm for industrial robots,” Comput. Industr. Engineer., vol. 42, no. 2–4, pp. 299–308, April 2002.
X. Cui and H. Shi, “A*-based pathfinding in modern computer games,” Int. J. Comput. Sci. Netw. Secur., vol. 11, pp. 125–130, 2011.
K. H. Kim, S. Sin, and W. Lee, “Exploring 3D shortest distance using A* algorithm in unity3D,” TechArt: Journal of Arts and Imaging Science, vol.2, no. 3, pp. 81–85, August 2015.
C. Yuan, G. Liu, W. Zhang, and X. Pan, “An efficient rrt cache method in dynamic environments for path planning,” Robot. Auton. Sys., vol. 131, 103595, September 2020.
L. Kavraki, P. Svestka, J. C. Latombe, and M. Overmars, “Probabilistic roadmaps for path planning in high-dimensional configuration spaces,” IEEE Trans. Robot. Autom., vol. 12, no. 4, pp. 566–580, August 1996.
A. K. Pamosoaji, M. Piao, and K.-S. Hong, “PSO-based minimum-time motion planning for multiple vehicles under acceleration and velocity limitations,” Int. J. Control Autom. Syst., vol. 17, pp. 2610–2623, 2019.
M. Ramaiah, A. Mukerjee, A. Chakraborty, and S. Sharma, “Visual generalized coordinates,” Mathematics, Computer Science, arXiv:1509.05636 September 2015.
F. C. Park and K. M. Lynch, Introduction to Robotics: Mechanics, Planning, and Control, Cambridge University Press, United Kingdom, 2017.
F. A. Raheem and A. A. Hussain, “Applying A* path planning algorithm based on modified c-space analysis,” Al-Khwarizmi Engineering Journal, vol. 13, no. 4, pp. 124–136, 2017.
L. Jaillet and J. M. Porta, “Efficient asymptotically-optimal path planning on manifolds,” Robot. Auton. Syst., vol. 61, no. 8, pp. 797–807, 2013.
D. Henrich, C. Wurll, and H. Worn, “Online path planning with optimal c-space discretization,” Proceedings of the 1998 IEEE/RSJ International Conference on Robots and System, Victoria, BC, Canada, pp. 1479–84, 1998.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The authors would like to thank FNSS Defense Systems Inc. and Scientific and Technological Research Council of Turkey (TÜBİTAK) for their support.
Ümit Yerlikaya was born in Agri, Turkey in 1990. He received his B.S. degree from Hacettepe University in Turkey and an M.S. degree from Middle East Technical University in mechanical engineering and now pursuing a Ph.D. in the same university. His research interests include dynamic modeling, control of electromechanical systems and path planning of co-working robots.
R. Tuna Balkan was born in Manisa, Turkey in 1957. He received his Ph.D. degree in mechanical engineering from the Middle East Technical University (METU), Ankara, Turkey, in 1988. He is currently a professor in Mechanical Engineering Department of METU and the dean of faculty of engineering of METU. Specific areas of interest include real-time control, Kalman filtering, fluid power control, platform stabilization, and industrial robotic applications such as spray painting and arc welding.
Rights and permissions
About this article
Cite this article
Yerlikaya, Ü., Balkan, R.T. Collision Free Motion Planning for Double Turret System Operating in a Common Workspace. Int. J. Control Autom. Syst. 19, 3487–3502 (2021). https://doi.org/10.1007/s12555-020-0382-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12555-020-0382-0