Minimum-Time Trajectory Planning for a Differential Drive Mobile Robot Considering Non-slipping Constraints

Journal of Control, Automation and Electrical Systems - Tập 32 Số 1 - Trang 120-131 - 2021
Okuyama, I. F.1, Maximo, Marcos R. O. A.1, Afonso, Rubens J. M.2,3
1Autonomous Computational Systems Lab (LAB-SCA), Computer Science Division, Aeronautics Institute of Technology, São Paulo, Brazil
2Department of Aerospace and Geodesy, Institute of Flight System Dynamics, Technical University of Munich, Munich, Germany
3Electronic Engineering Division, Aeronautics Institute of Technology, São Paulo, Brazil

Tóm tắt

We propose a real-time minimum-time trajectory planning strategy with obstacle avoidance for a differential-drive mobile robot in the context of robot soccer. The method considers constraints important to maximize the system’s performance, such as the actuator limits and non-slipping conditions. We also present a novel friction model that regards the imbalance of normal forces on the wheels due to the acceleration of the robot. Theoretical guarantees on how to obtain a minimum-time velocity profile on a predetermined parametrized curve considering the modeled constraints are also presented. Then, we introduce a nonlinear, non-convex, local optimization using a version of the Resilient Propagation algorithm that minimizes the time of the curve while avoiding obstacles and respecting system constraints. Finally, employing a new proposed benchmark, we verified that the presented strategy allows the robot to traverse a cluttered field (with dimensions of 1.5 m $$\times $$ 1.3 m) in 2.8 s in 95% of the cases, while the optimization success rate was 85%. We also demonstrated the possibility of running the optimization in real-time, since it takes less than 13.8 ms in 95% of the cases.

Tài liệu tham khảo

Ben-Asher, J. Z., Wetzler, M,, Rimon, E. D., & Diepolder, J. (2019). Optimal trajectories for a mobile robot with bounded accelerations in the presence of a wall or a bounded obstacle. In 2019 27th mediterranean conference on control and automation (MED) (pp. 481–488). IEEE. citation_journal_title=SIAM Journal on Optimization; citation_title=Infeasibility detection and SQP methods for nonlinear optimization; citation_author=RH Byrd, FE Curtis, J Nocedal; citation_volume=20; citation_issue=5; citation_publication_date=2010; citation_pages=2281-2299; citation_doi=10.1137/080738222; citation_id=CR2 citation_journal_title=American Journal of Mathematics; citation_title=On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents; citation_author=LE Dubins; citation_volume=79; citation_issue=3; citation_publication_date=1957; citation_pages=497-516; citation_doi=10.2307/2372560; citation_id=CR3 citation_journal_title=European Journal of Mechanics-A/Solids; citation_title=A random-profile approach for trajectory planning of wheeled mobile robots; citation_author=M Haddad, T Chettibi, S Hanchi, H Lehtihet; citation_volume=26; citation_issue=3; citation_publication_date=2007; citation_pages=519-540; citation_doi=10.1016/j.euromechsol.2006.10.001; citation_id=CR4 citation_journal_title=IEEE Transactions on Systems Science and Cybernetics; citation_title=A formal basis for the heuristic determination of minimum cost paths; citation_author=PE Hart, NJ Nilsson, B Raphael; citation_volume=4; citation_issue=2; citation_publication_date=1968; citation_pages=100-107; citation_doi=10.1109/TSSC.1968.300136; citation_id=CR5 Hérissé, B., & Pepy, R. (2013). Shortest paths for the Dubins’ vehicle in heterogeneous environments. In 52nd IEEE conference on decision and control (pp. 4504–4509). IEEE. Ho, Y. J., & Liu, J. S. (2009). Collision-free curvature-bounded smooth path planning using composite bezier curve based on voronoi diagram. In 2009 IEEE international symposium on computational intelligence in robotics and automation (CIRA), Daejeon, South Korea (pp. 463–468). IEEE. IEEE. (2008). Rules for the IEEE very small competition. http://www.cbrobotica.org/wp-content/uploads/2014/03/VerySmall2008_en.pdf . Accessed April 20th, 2019. Karaman, S., & Frazzoli, E. (2010). Incremental sampling-based algorithms for optimal motion planning. Robotics Science and Systems VI, 104(2). Khatib, O., & Le Maitre, J. (1978). Dynamic control of manipulators operating in a complex environment. In 3rd CISM-IFToMM symposium on theory and practice of robots and manipulators, PWN, Udine, Italy, vol. 267. citation_journal_title=IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics); citation_title=Evolutionary programming-based univector field navigation method for past mobile robots; citation_author=YJ Kim, JH Kim, DS Kwon; citation_volume=31; citation_issue=3; citation_publication_date=2001; citation_pages=450-458; citation_doi=10.1109/3477.931544; citation_id=CR11 citation_title=Robot motion planning; citation_publication_date=2012; citation_id=CR12; citation_author=JC Latombe; citation_publisher=Springer LaValle, S. M. (1998). Rapidly-exploring random trees: A new tool for path planning. Technical report, Ames, IA, USA. citation_title=Planning algorithms; citation_publication_date=2006; citation_id=CR14; citation_author=SM LaValle; citation_publisher=Cambridge University Press citation_journal_title=The International Journal of Robotics Research; citation_title=Randomized kinodynamic planning; citation_author=SM LaValle, JJ Kuffner; citation_volume=20; citation_issue=5; citation_publication_date=2001; citation_pages=378-400; citation_doi=10.1177/02783640122067453; citation_id=CR15 citation_journal_title=Robotics and Autonomous Systems; citation_title=Time optimal path planning considering acceleration limits; citation_author=M Lepetič, G Klančar, I Škrjanc, D Matko, B Potočnik; citation_volume=45; citation_issue=3–4; citation_publication_date=2003; citation_pages=199-210; citation_doi=10.1016/j.robot.2003.09.007; citation_id=CR16 citation_journal_title=IFAC Proceedings Volumes; citation_title=Evolutionary univector field-based navigation with collision avoidance for mobile robot; citation_author=Y Lim, SH Choi, JH Kim, DH Kim; citation_volume=41; citation_issue=2; citation_publication_date=2008; citation_pages=12787-12792; citation_doi=10.3182/20080706-5-KR-1001.02163; citation_id=CR17 citation_journal_title=Communications of the ACM; citation_title=An algorithm for planning collision-free paths among polyhedral obstacles; citation_author=T Lozano-Pérez, MA Wesley; citation_volume=22; citation_issue=10; citation_publication_date=1979; citation_pages=560-570; citation_doi=10.1145/359156.359164; citation_id=CR18 citation_journal_title=IEEE Transactions on Aerospace and Electronic Systems; citation_title=Time optimal trajectories for a mobile robot under explicit acceleration constraints; citation_author=G Manor, JZ Ben-Asher, E Rimon; citation_volume=54; citation_issue=5; citation_publication_date=2018; citation_pages=2220-2232; citation_doi=10.1109/TAES.2018.2811158; citation_id=CR19 citation_journal_title=Journal of the American Statistical Association; citation_title=The monte carlo method; citation_author=N Metropolis, S Ulam; citation_volume=44; citation_issue=247; citation_publication_date=1949; citation_pages=335-341; citation_doi=10.1080/01621459.1949.10483310; citation_id=CR20 citation_journal_title=Safety and Comfort Factors; citation_title=Deterministic trajectory planning for non-holonomic vehicles including road conditions; citation_author=M Morsali, E Frisk, J Åslund; citation_volume=52; citation_issue=5; citation_publication_date=2019; citation_pages=97-102; citation_id=CR21 Okuyama, I. F. (2019). Minimum-time obstacle avoidant trajectory planning for a differential drive robot considering motor and no-slipping constraints. Master’s thesis, Instituto Tecnológico de Aeronáutica. Okuyama, I. F., Maximo, M. R. O. A., Cavalcanti, A. L. O., & Afonso, R. J. M. (2017). Nonlinear grey-box identification of a differential drive mobile robot. In XIII Simpósio Brasileiro de Automação Inteligente., SBAI, Porto Alegre, RS, BR. citation_journal_title=Robotics and Autonomous Systems; citation_title=Trajectory generation and control for four wheeled omnidirectional vehicles; citation_author=O Purwin, R D’Andrea; citation_volume=54; citation_issue=1; citation_publication_date=2006; citation_pages=13-22; citation_doi=10.1016/j.robot.2005.10.002; citation_id=CR24 Riedmiller, M., & Braun, H. (1993). A direct adaptive method for faster backpropagation learning: The RPROP algorithm. In IEEE international conference on neural networks, vol. 1 (pp. 586–591). IEEE, San Francisco, CA, USA. Rimon, E., Koditschek, D. E. (1992). Exact robot navigation using artificial potential functions. Departmental Papers (ESE) p. 323. citation_title=Artificial Intelligence: A Modern Approach; citation_publication_date=2009; citation_id=CR27; citation_author=S Russell; citation_author=P Norvig; citation_publisher=Prentice Hall Press citation_title=Real-time motion planning and control in the 2005 Cornell RoboCup system; citation_inbook_title=Robot Motion and Control; citation_publication_date=2006; citation_pages=245-263; citation_id=CR28; citation_author=M Sherback; citation_author=O Purwin; citation_author=R D’Andrea; citation_publisher=Springer citation_journal_title=IEEE Transactions on Automatic Control; citation_title=Minimum-time control of robotic manipulators with geometric path constraints; citation_author=K Shin, N McKay; citation_volume=30; citation_issue=6; citation_publication_date=1985; citation_pages=531-541; citation_doi=10.1109/TAC.1985.1104009; citation_id=CR29 Sprunk, C. (2008). Planning motion trajectories for mobile robots using splines. Technical Report, Freiburg, Germany. Webb, D. J., & van den Berg, J. (2013). Kinodynamic RRT*: Asymptotically optimal motion planning for robots with linear dynamics. In 2013 IEEE international conference on robotics and automation (pp. 5054–5061). Karlsruhe, Germany. IEEE. Yamamoto, M., Iwamura, M., & Mohri, A. (1998). Time-optimal motion planning of skid-steer mobile robots in the presence of obstacles. In Proceedings of 1998 IEEE/RSJ international conference on intelligent robots and systems. innovations in theory, practice and applications vol. 1 (pp. 32–37). IEEE, Victoria, BC, Canada. Yamamoto, M., Iwamura, M., & Mohri, A. (1999). Quasi-time-optimal motion planning of mobile platforms in the presence of obstacles. In Proceedings 1999 ieee international conference on robotics and automation vol. 4 (pp. 2958–2963). IEEE, Detroit, MI, USA. Zhu, Z., Schmerling, E., & Pavone, M. (2015). A convex optimization approach to smooth trajectories for motion planning with car-like robots. In 2015 54th IEEE conference on decision and control (CDC) (pp. 835–842). IEEE.