title: Application of time dependent probabilistic collision state checkers in highly dynamic environments.
abstract: When computing the trajectory of an autonomous vehicle, inevitable collision states must be avoided at all costs, so no harm comes to the device or pedestrians around it. In dynamic environments, considering collisions as binary events is risky and inefficient, as the future position of moving obstacles is unknown. We introduce a time-dependent probabilistic collision state checker system, which traces a safe route with a minimum collision probability for a robot. We apply a sequential Bayesian model to calculate approximate predictions of the movement patterns of the obstacles, and define a time-dependent variation of the Dijkstra algorithm to compute statistically safe trajectories through a crowded area. We prove the efficiency of our methods through experimentation, using a self-guided robotic device.
authors: Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, La Laguna, Canary Islands, Spain.
authors: Javier
authors: J
authors: Hernández-Aceituno
authors: Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, La Laguna, Canary Islands, Spain.
authors: Leopoldo
authors: L
authors: Acosta
authors: Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, La Laguna, Canary Islands, Spain.
authors: José D
authors: JD
authors: Piñeiro
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D004777:Environment; D006801:Humans; D008962:Models, Theoretical; D011336:Probability; D012371:Robotics / Q000295:instrumentation* / Q000379:methods*; D013997:Time Factors