2026-05-30T04:43:34Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/351612026-02-03T11:34:50Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Lin-Yang, Da-hui author Pastor, Francisco author García-Cerezo, Alfonso José author 2024 In the field of mobile robots, achieving minimum time in executing trajectories is crucial for applications like delivery, inspection, and search and rescue. In this article, a novel time-optimal planner based on optimization methods is introduced. Despite the high computational cost associated with such methods, the solution calculates time-optimal multi-waypoint trajectories, achieving results in the order of milliseconds. The proposed method formulates a time-optimal trajectory using the Pontryagin's maximum principle as a policy. By utilizing a point mass model, the planner generates trajectories that are adaptable to different robot models. The approach incorporates a definition of a search space to guarantee convergence while considering the system limits. Simulation and real-world experiments are performed to validate the feasibility of our method with different configurations. Simulation results compared to a benchmark method demonstrate our approach's superior performance in terms of computational time, achieving near-optimal solutions. In addition, in the real-world experiments, the integration of the method into practical applications is validated. Lin-Yang, D.-h., Pastor, F. and García-Cerezo, A.J. (2024), Low Computational Cost for Multiple Waypoints Trajectory Planning: A Time-Optimal-Based Approach. Adv. Intell. Syst. 2400363. https://doi.org/10.1002/aisy.202400363 https://hdl.handle.net/10630/35161 10.1002/aisy.202400363 Robótica Low Computational Cost for Multiple Waypoints Trajectory Planning: A Time-optimal Based Approach