title: Robot trajectories comparison: a statistical approach.
abstract: The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM(2) and WaveFront, using different environments, robots, and local planners.
authors.affiliation: Autonomous and Smart Systems Unit, IK4 Tekniker, Eibar, Spain.
authors.forename: A
authors.initials: A
authors.lastname: Ansuategui
authors.affiliation: Department of Computation and Artificial Intelligence, Euskal Herriko Unibertsitatea UPV-EHU, Donostia, Spain.
authors.forename: A
authors.initials: A
authors.lastname: Arruti
authors.affiliation: Autonomous and Smart Systems Unit, IK4 Tekniker, Eibar, Spain.
authors.forename: L
authors.initials: L
authors.lastname: Susperregi
authors.affiliation: Department of Computation and Artificial Intelligence, Euskal Herriko Unibertsitatea UPV-EHU, Donostia, Spain.
authors.forename: Y
authors.initials: Y
authors.lastname: Yurramendi
authors.affiliation: Department of Computation and Artificial Intelligence, Euskal Herriko Unibertsitatea UPV-EHU, Donostia, Spain.
authors.forename: E
authors.initials: E
authors.lastname: Jauregi
authors.affiliation: Department of Computation and Artificial Intelligence, Euskal Herriko Unibertsitatea UPV-EHU, Donostia, Spain.
authors.forename: E
authors.initials: E
authors.lastname: Lazkano
authors.affiliation: Department of Computation and Artificial Intelligence, Euskal Herriko Unibertsitatea UPV-EHU, Donostia, Spain.
authors.forename: B
authors.initials: B
authors.lastname: Sierra
mesh_terms: D003198:Computer Simulation; D003625:Data Collection; D004777:Environment; D006761:Hospitals; D006801:Humans; D012371:Robotics; D013223:Statistics as Topic