Thuật toán lập kế hoạch đường đi thời gian thực cho robot song song điều khiển bằng cáp trong môi trường động dựa trên RRT với hướng dẫn tiềm năng nhân tạo

Adiyatov O, Varol HA (2013) Rapidly-exploring random tree based memory efficient motion planning. In: 2013 IEEE International Conference on Mechatronics and Automation. IEEE, pp 354–359 Adiyatov O, Varol HA (2017) A novel RRT*-based algorithm for motion planning in dynamic environments. In: 2017 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, pp 1416–1421 Agarwal S, Gaurav AK, Nirala MK, Sinha S (2018) Potential and sampling based RRT star for real-time dynamic motion planning accounting for momentum in cost function. In International Conference on Neural Information Processing. Springer, Cham, pp 209–221 Aref MM, Taghirad HD (2008) Geometrical workspace analysis of a cable-driven redundant parallel manipulator: KNTU CDRPM. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, pp 1958–1963 Bak JH, Hwang SW, Yoon J, Park JH, Park JO (2019) Collision-free path planning of cable-driven parallel robots in cluttered environments. Intell Serv Rob 12:243–253 Bolboli J, Khosravi MA, Abdollahi F (2019) Stiffness feasible workspace of cable-driven parallel robots with application to optimal design of a planar cable robot. Rob Auton Syst 114:19–28 Bosscher P, Riechel AT, Ebert-Uphoff I (2006) Wrench-feasible workspace generation for cable-driven robots. IEEE Trans Rob 22(5):890–902 Gahinet P, Nemirovski A (1997) The projective method for solving linear matrix inequalities. Math Program 77(1):163–190 Ge SS, Cui YJ (2000) New potential functions for mobile robot path planning. IEEE Trans Rob Autom 16(5):615–620 Gilbert EG, Johnson DW, Keerthi SS (1988) A fast procedure for computing the distance between complex objects in three-dimensional space. IEEE J Rob Autom 4(2):193–203 Gosselin C (2014) Cable-driven parallel mechanisms: state of the art and perspectives. Mech Eng Rev 1(1):DMS0004–DMS0004 Gouttefarde M, Daney D, Merlet JP (2010) Interval-analysis-based determination of the wrench-feasible workspace of parallel cable-driven robots. IEEE Trans Rob 27(1):1–13 Heo JM, Park BJ, Park JO, Kim CS, Jung J, Park KS (2018) Workspace and stability analysis of a 6-DOF cable-driven parallel robot using frequency-based variable constraints. J Mech Sci Technol 32(3):1345–1356 Kang G, Kim YB, Lee YH, Oh HS, You WS, Choi HR (2019) Sampling-based motion planning of manipulator with goal-oriented sampling. Intell Serv Rob 12:265–273 Karaman S, Frazzoli E (2011) Sampling-based algorithms for optimal motion planning. Int J Rob Res 30(7):846–894 Khatib O (1985) Real-time obstacle avoidance for manipulators and mobile robots. In: Proceedings. 1985 IEEE International Conference on Robotics and Automation Vol. 2. IEEE, pp 500–505 Klemm S, Oberländer J, Hermann A, Roennau A, Schamm T, Zollner JM, Dillmann R (2015) RRT∗-Connect: Faster, asymptotically optimal motion planning. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, pp 1670–1677 Lahouar S, Ottaviano E, Zeghoul S, Romdhane L, Ceccarelli M (2009) Collision free path-planning for cable-driven parallel robots. Rob Auton Syst 57(11):1083–1093 Lavalle SM (1998) Rapidly-exploring random trees: a new tool for path planning Martin A, Caro S, Cardou P (2018) Design of a cable-driven parallel robot with grasping device. Procedia Cirp 70:290–295 Michelin M, Baradat C, Nguyen DQ, Gouttefarde M (2015) Simulation and control with xde and matlab/simulink of a cable-driven parallel robot (cogiro). In: cable-driven parallel robots. Springer, Cham, pp 71–83 Mirjalili S, Dong JS, Lewis A (2020) Ant Colony optimizer: theory, literature review, and application in AUV path planning. In: nature-inspired optimizers. Springer, Cham, pp 7–21 Montiel O, Orozco-Rosas U, Sepúlveda R (2015) Path planning for mobile robots using Bacterial Potential Field for avoiding static and dynamic obstacles. Expert Syst Appl 42(12):5177–5191 Nguyen DQ, Gouttefarde M (2014) Study of reconfigurable suspended cable-driven parallel robots for airplane maintenance. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, pp 1682–1689 Otte M, Frazzoli E (2016) RRTX: asymptotically optimal single-query sampling-based motion planning with quick replanning. Int J Rob Res 35(7):797–822 Ren S, He K, Girshick R, Sun J (2015) Faster r-cnn: towards real-time object detection with region proposal networks. In: Advances in neural information processing systems, pp 91–99 Tahir Z, Qureshi AH, Ayaz Y, Nawaz R (2018) Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments. Rob Auton Syst 108:13–27 Wang B, Zi B, Qian S, Zhang D (2016) Collision free force closure workspace determination of reconfigurable planar cable driven parallel robot. In: 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS). IEEE, pp 26–30 Wu Y, Cheng HH, Fingrut A, Crolla K, Yam Y, Lau D (2018) CU-brick cable-driven robot for automated construction of complex brick structures: from simulation to hardware realisation. In: 2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR). IEEE, pp 166–173 Xiang S, Gao H, Liu Z, Gosselin C (2020) Dynamic point-to-point trajectory planning for three degrees-of-freedom cable-suspended parallel robots using rapidly exploring random tree search. J Mech Rob 12(4):041007 Yan P, Yan Z, Zheng H, Guo J (2018). Real time robot path planning method based on improved artificial potential field method. In: 2018 37th Chinese Control Conference (CCC). IEEE, pp 4814–4820 Youssef K, Otis MJD (2020) Reconfigurable fully constrained cable driven parallel mechanism for avoiding interference between cables. Mech Mach Theory 148:103781 Zhang B, Shang W, Cong S (2018) Optimal RRT* planning and synchronous control of cable-driven parallel robots. In: 2018 3rd International Conference on Advanced Robotics and Mechatronics (ICARM). IEEE, pp 95–100 Zhang Z, Wu D, Gu J, Li F (2019) A path-planning strategy for unmanned surface vehicles based on an adaptive hybrid dynamic stepsize and target attractive force-RRT algorithm. J Marine Sci Eng 7(5):132