Agustín Martín, AlbaOlivares, AlbertoStaffetti, Ernesto2023-09-112023-09-112016Agustín, A., Olivares, A., Staffetti, E. (2016) Using biased randomization for trajectory optimization in robotic manipulators. En León, R., Muñoz-Torres, M. J., Moneva J. M. (Eds.), Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016: proceedings (pp. 145-154). Springer. https://doi.org/10.1007/978-3-319-40506-3_15.978-3-319-40505-610.1007/978-3-319-40506-3_15https://academica-e.unavarra.es/handle/2454/46258We study the problem of optimization of trajectories for a robotic manipulator, with two degrees of freedom, which is constrained to pass through a set of waypoints in the workspace. The aim is to determine the optimal sequence of points and continuous optimal system trajectory. The actual formulation involves an optimal control problem of a dynamic system within integer variables that model the waypoints constrains. The nature of this problem, highly nonlinear and combinatorial, makes it particularly difficult to solve. The proposed method combines a meta-heuristic algorithm to determine the promising sequence of discrete points with a collocation technique to optimize the continuous path of the system. This method does not guarantee the global optimum, but can solve instances of dozens of points in reasonable computation time.application/pdfeng© 2016 Springer International Publishing SwitzerlandRoboticsOptimal controlMotion planningMeta-heuristicsBiased-randomizationContribución a congreso / Biltzarrerako ekarpena2023-09-11Acceso abierto / Sarbide irekiainfo:eu-repo/semantics/openAccess