Lyubomira Miteva
ABSTRACT
Nowadays, robotic manipulators must operate in a dynamic environment and perform more and more complex and precise tasks. Therefore, robots that have more degrees of freedom than the desired task requires are used. These robots are called redundant robots and they can achieve an arbitrary point from their workspace with multiple sets of different joint configurations. Also, they have an extended range of orientations of their end-effectors. There are points in the workspace of the robot which require the end-effector of the robot to move from its current position to change its orientation. This research studies the zones in the workspace of the robot at which it can make orientation change of its end-effector without moving from the current position and these at which that is impossible. Therefore, the paper proposes an approach for trajectory planning for orientation change of the end-effector of a redundant robot with minimal displacement from its current position. Experiments are conducted to evaluate the applicability of this approach.
- Yang Lei, Yanhong Liu and Jinzu Peng. 2020. Advances techniques of the structured light sensing in intelligent welding robots: a review. The International Journal of Advanced Manufacturing Technology. https://doi.org/110. 10.1007/s00170-020-05524-2.Google Scholar
- Hang Su, Hang Chenguang Yang, Giancarlo Ferrigno and Elena De Momi. 2019. Improved Human-Robot Collaborative Control of Redundant Robot for Teleoperated Minimally Invasive Surgery. IEEE Robotics and Automation Letters. 1-1. https://doi.org/10.1109/LRA.2019.2897145.Google Scholar
- K. Wada, T. Shibata, T. Saito and K. Tanie, 2004. Effects of robot-assisted activity for elderly people and nurses at a day service center. In Proceedings of the IEEE, vol. 92, no. 11, pp. 1780-1788. https://doi.org/10.1109/JPROC.2004.835378.Google ScholarCross Ref
- Yanlong Huang, Bernhard Scholkopf and Jan Peters. 2015. Learning optimal striking points for a ping-pong playing robot. 4587-4592. https://doi.org/10.1109/IROS.2015.7354030.Google Scholar
- Wen Yu and Adolfo Perrusquía. 2020. Simplified Stable Admittance Control Using End-Effector Orientations. Int. J. Soc. Robotics 12, 1061-1073.Google ScholarCross Ref
- Stefano Chiaverini, Giuseppe Oriolo and Anthony Maciejewski. 2016. Redundant Robots, 221-242. https://doi.org/10.1007/978-3-319-32552-1_10.Google Scholar
- Kevin M. Lynch and Frank C. Park. 2017. Modern Robotics Mechanics, Planning and Control. Cambridge University Press.Google Scholar
- Yanlong Huang, Fares Abu-Dakka, João Silvério and Darwin Caldwell. 2019. Generalized Orientation Learning in Robot Task Space. https://doi.org/10.1109/ICRA.2019.8793540.Google Scholar
- Hongchao Fang, Ong and Andrew Nee. 2012. Orientation planning of robot end-effector using augmented reality. The International Journal of Advanced Manufacturing Technology. 67. https://doi.org/10.1007/s00170-012-4629-7.Google Scholar
- Caio Viturino, Ubiraton Junior, Conceicao Scolari, Andre and Leizer Schnitman. 2020. Adaptive Artificial Potential Fields with Orientation Control Applied to Robotic Manipulators. IFAC-PapersOnLine. 53. 9924-9929. https://doi.org/10.1016/j.ifacol.2020.12.2706.Google ScholarCross Ref
- Stefan Gadringer, Hubert Gattringer, Andreas Mueller and Ronald Naderer. 2020. Robot Calibration combining Kinematic Model and Neural Network for enhanced Positioning and Orientation Accuracy. IFAC-PapersOnLine. 53. 8432-8437. https://doi.org/10.1016/j.ifacol.2020.12.1436.Google ScholarCross Ref
- M. V. S. Siar and A. Fakharian. 2018. Energy efciency in the robot arm using genetic algorithm. In Proc. 8th Conf. AI Robot. 10th RoboCup Iranopen Int. Symp. (IRANOPEN), Qazvin, Iran, 14-20.Google Scholar
- P. Kalra, P. B. Mahapatra, and D. K. Aggarwal. 2003. On the solution of multimodal robot inverse kinematic functions using real-coded genetic algorithms. In Proc. IEEE Int. Conf. Syst., Man Cybern., Conf. Theme-Syst. Secur. Assurance, Washington, DC, USA, vol. 2, 1840-1845.Google Scholar
- Anoush Sepehri and Moghaddam M. Amirreza. 2021. A Motion Planning Algorithm for Redundant Manipulators Using Rapidly Exploring Randomized Trees and Artificial Potential Fields. IEEE Access. 1-1. https://doi.org/10.1109/ACCESS.2021.3056397.Google Scholar
- M. Duguleana, F. G. Barbuceanu, A. Teirelbar, and G. Mogan. 2011. Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning. Robot. Comput.-Integr. Manuf., vol. 28, no. 2, 132146.Google Scholar
- Wang Wei and Wei Shimin. 2010. 3-D Path Planning Using Neural Networks for a Robot Manipulator. Intelligent Computation Technology and Automation, International Conference on. 1, 3-6. https://doi.org/10.1109/ICICTA.2010.838.Google Scholar
- Ciann-Dong Yang, Z. Lai. 1985. On the Dexterity of Robotic Manipulators—Service Angle. In Journal of Mechanisms Transmissions and Automation in Design, 107.Google Scholar
- Vinogradov, I.B., A.E. Kobrinski, Y.E. Stephenko, L.T. Tives. 1971. Details of Kinematics of Manipulators with the Method of Volumes. In Mekanika Mashin, Vol. 1, No.5, 5-16.Google Scholar
- Lyubomira Miteva, Galya Pavlova, Roumen Trifonov, and Kaloyan Yovchev. 2020. Manipulability Analysis of Redundant Robotic Manipulator. Proceedings of the 21st International Conference on Computer Systems and Technologies '20. Association for Computing Machinery, New York, NY, USA, 135–140. https://doi.org/10.1145/3407982.3407987Google ScholarDigital Library
- Lyubomira Miteva, Ivan Chavdarov and Kaloyan Yovchev. 2020. Trajectory planning for redundant robotic manipulators with constrained joint space. In International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia, 1-6. https://doi.org/10.23919/SoftCOM50211.2020.9238296.Google ScholarCross Ref
- George Boiadjiev, Evgeniy Krastev, Ivan Chavdarov, and Lyubomira Miteva. 2021. A Novel, Oriented to Graphs Model of Robot Arm Dynamics. Robotics. 10, no. 4: 128. https://doi.org/10.3390/robotics10040128Google ScholarCross Ref
Index Terms
- Planning Orientation Change of the End-effector of State Space Constrained Redundant Robotic Manipulators
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