DOI 10.17586/0021-3454-2022-65-3-185-193
UDC 004.021
MODIFIED INTELLIGENT BIDIRECTIONAL RANDOM TREE ALGORITHM FOR PLANNING THE MOVEMENT OF ANTHROPOMORPHIC MANIPULATORS
ITMO University, Faculty of Control Systems and Robotics, International Laboratory of Biomechatronics and Energy-Efficient Robotics;
K. Artemov
ITMO University, Faculty of Control Systems and Robotics, International Laboratory of Biomechatronics and Energy-Efficient Robotics;
O. I. Borisov
ITMO University, Saint Petersburg, 197101, Russian Federation; postgraduate,engineer
S. h. Zabihifar
Sberbank, Robotics Laboratory;
A. N. Semochkin
Sberbank, Robotics Laboratory;
Read the full article
Abstract. An algorithm for planning the movement of a multi-link robotic system in an environment with obstacles is considered. The main requirements for this task are high performance and efficient memory usage during operation. An algorithm for path planning based on the method of a bidirectional fast-investigating random tree is presented. An approach is used which excludes addition of new vertices to the tree if their location in space can unambiguously conclude that it is inappropriate to use them in the path construction. This modification makes it possible to speed up movement planning and reduce the amount of memory needed to store the environment analysis data.
Keywords: path planning, rapidly-exploring random trees, exclusion of unused vertices, iCub
References:
References:
- Liu W. Mathematics and Mathematical Modelling, 2018, no. 01, pp. 15–58, DOI: 10.24108/mathm.0118.0000098.
- LaValle S. TR 98-11, Computer Science Dept., Iowa State University, October 1998.
- Karaman S. and Frazzoli E. The International Journal of Robotics Research, 2011, vol. 30, pp. 846–894.
- Levin B.R. Teoreticheskiye osnovy staticheskoy radiotekhniki (Theoretical Foundations of Static Radio Engineering), Moscow, 1989, 656 р. (in Russ.)
- Jordan M. and Perez A. Tech. Rep. MITCSAIL-TR-2013-021, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, August 2013.
- Qureshi A.H. and Ayaz Y. ArXiv, 2015, vol. abs/1703.08944.
- Tahir Z., Qureshi A.H., Ayaz Y., and Nawaz R. Robotics Auton. Syst., 2018, vol. 108, pp. 13–27.
- Gammell J., Srinivasa S., and Barfoot T. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014, pp. 2997–3004.
- Burget F., Bennewitz M., and Burgard W. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016, pp. 3714–3721.
- Kingston Z., Moll M., and Kavraki L. The International Journal of Robotics Research, 2019, vol. 38, pp. 1151–1178.
- Hauser K. Motion and Path Planning, Berlin, Heidelberg, Springer, 2020, pp. 1–11.