Local path planning is a key task for the motion planners of autonomous vehicles since it commands the vehicle across its environment while avoiding any obstacles. To perform this task, the local path planner generates a trajectory and a velocity profile, which are then sent to the vehicle’s actuators. This paper proposes a new local path planner for autonomous vehicles based on the Attractor Dynamic Approach (ADA), which was inspired by the behavior of movement of living beings, along with an algorithm that takes into account four acceleration policies, the ST dynamic vehicle model, and several constraints regarding the comfort and security. The original functions that define the ADA were modified in order to adapt it to the non-holonomic vehicle’s constraints and to improve its response when an impact scenario is detected. The present approach is validated in a well-known simulator for autonomous vehicles under three representative cases of study where the vehicle was capable of generating local paths that ensure the security of the vehicle in such cases. The results show that the approach proposed in this paper is a promising tool for the local path planning of autonomous vehicles since it is able to generate trajectories that are both safe and efficient.
Resumen. En este trabajo se presenta una solución novedosa para el diseñoóptimo de un efector final tipo pinza, para la transmisión de fuerza constante en su espacio de trabajo o agarre. Para tal fin se propone un problema de optimización numérica con restricciones asociado al mecanismo, el cual se resuelve utilizando el algoritmo de evolución diferencial. La función objetivo propuesta es la transmisión de fuerza constante por parte del eslabón de agarre. Los resultados obtenidos muestran una transferencia de fuerza constante con diferentes configuraciones del efector final, comprobándose la naturaleza multimodal del problema.
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