title: Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors.
abstract: We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser's datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three.
authors.affiliation: Control Engineering Group, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå 97187, Sweden. anas.alhashimi@ltu.se.
authors.forename: Anas
authors.initials: A
authors.lastname: Alhashimi
authors.affiliation: Control Engineering Group, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå 97187, Sweden. damiano.varagnolo@ltu.se.
authors.forename: Damiano
authors.initials: D
authors.lastname: Varagnolo
authors.affiliation: Control Engineering Group, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå 97187, Sweden. thomas.Gustafsson@ltu.se.
authors.forename: Thomas
authors.initials: T
authors.lastname: Gustafsson
keywords: EM; Gaussian mixture model (GMM); LiDAR; SICK LMS200; ToF; maximum likelihood (ML); mode hopping; multi-modality