2021-11-242021-11-242019Pérez Hurtado de Mendoza, I., Martínez del Amor, M.Á., Zhang, G., Neri, F. y Pérez Jiménez, M.d.J. (2019). Solving the feasibility problem in robotic motion planning by means of Enzymatic Numerical P systems. En ACMC 2019: The 8th Asian Conference on Membrane Computing (152-165), Xiamen, China: IMCS: International Membrane Computing Society.https://hdl.handle.net/11441/127639Solving the feasibility problem in robotic motion planning means to find feasible trajectories for specific mobile robots acting in environments with obstacles whose positions are known a priori. The Rapidly-exploring Random Tree (RRT) algorithm is a classical algorithm to solve such a problem in real-life applications. In this paper, we provide a model in the framework of Enzymatic Numerical P systems to reproduce the behaviour of the RRT algorithm. A C++ ad-hoc simulator is also provided to validate the model.application/pdf14engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Motion PlanningRapidly-exploring Random TreeMembrane computingEnzymatic numerical P systemsinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess