Abstract
This paper proposes a kinodynamic planning algorithm for vehicles with bounds on actuation. The proposed approach is based on identification of homotopy classes to decompose the global obstacle avoidance problem into several simpler subproblems. We formulate the homotopic trajectory planning problem in a multiple phase trajectory optimization scheme, such that at each phase different kinematic constraints are active. This novel formulation satisfies the collision-free constraints and homotopy constraints at the same time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bhattacharya, S., Likhachev, M., Kumar, V.: Topological constraints in search-based robot path planning. Auton. Robots 33(3), 273–290 (2012)
Chazelle, B.: Approximation and decomposition of shapes. Algorithmic Geom. Aspects Robot. 1, 145–185 (1985)
Donald, B., Xavier, P., Canny, J., Reif, J.: Kinodynamic motion planning. J. ACM (JACM) 40(5), 1048–1066 (1993)
Gu, T., Dolan, J.M., Lee, J.W.: Automated tactical maneuver discovery, reasoning and trajectory planning for autonomous driving. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5474–5480. IEEE (2016)
Hernandez, E., Carreras, M., Ridao, P.: A comparison of homotopic path planning algorithms for robotic applications. Robot. Auton. Syst. 64, 44–58 (2015)
Jeon, J.H., Karaman, S., Frazzoli, E.: Anytime computation of time-optimal off-road vehicle maneuvers using the RRT*. In: Decision and Control and European Control Conference (CDC-ECC) (2011)
Kuderer, M., Sprunk, C., Kretzschmar, H., Burgard, W.: Online generation of homotopically distinct navigation paths. In: 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE (2014)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)
Likhachev, M., Ferguson, D.: Planning long dynamically feasible maneuvers for autonomous vehicles. Int. J. Robot. Res. 28(8), 933–945 (2009)
Park, J., Karumanchi, S., Iagnemma, K.: Homotopy-based divide-and-conquer strategy for optimal trajectory planning via mixed-integer programming. IEEE Trans. Robot. 31(5), 1101–1115 (2015)
Patterson, M.A., Rao, A.V.: GPOPS-II: a MATLAB software for solving multiple-phase optimal control problems using hp-adaptive Gaussian quadrature collocation methods and sparse nonlinear programming. ACM Trans. Math. Softw. (TOMS) 41, Article No. 1 (2014)
Pearl, J.: Heuristics: intelligent search strategies for computer problem solving (1984)
Perez, A., Platt, Jr. R., Konidaris, G., Kaelbling, L., Lozano-Perez, T.: LQR-RRT*: optimal sampling-based motion planning with automatically derived extension heuristics. In: Robotics and Automation (ICRA) (2012)
Pivtoraiko, M., Knepper, R.A., Kelly, A.: Differentially constrained mobile robot motion planning in state lattices. J. Field Robot. 26(3), 308–333 (2009)
Ratliff, N., Zucker, M., Bagnell, J.A., Srinivasa, S.: CHOMP: gradient optimization techniques for efficient motion planning. In: IEEE International Conference on Robotics and Automation, ICRA 2009, pp. 489–494. IEEE (2009)
Richter, C., Bry, A., Roy, N.: Polynomial trajectory planning for aggressive quadrotor flight in dense indoor environments. In: Inaba, M., Corke, P. (eds.) Robotics Research. STAR, vol. 114, pp. 649–666. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-28872-7_37
Tarjan, R.: Depth-first search and linear graph algorithms. SIAM J. Comput. 1(2), 146–160 (1972)
Webb, D.J., van den Berg, J.: Kinodynamic RRT*: optimal motion planning for systems with linear differential constraints. arXiv preprint arXiv:1205.5088 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Sakcak, B., Bascetta, L., Ferretti, G. (2018). An Exact Optimal Kinodynamic Planner Based on Homotopy Class Constraints. In: Mazal, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2017. Lecture Notes in Computer Science(), vol 10756. Springer, Cham. https://doi.org/10.1007/978-3-319-76072-8_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-76072-8_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-76071-1
Online ISBN: 978-3-319-76072-8
eBook Packages: Computer ScienceComputer Science (R0)