Jan Skaloud

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Senior Scientist

jan.skaloud@epfl.ch

EPFL > ENAC > IIE > CRYOS

Web site:  Web site:  https://cryos.epfl.ch

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Administrative data

Fields of expertise

Satellite positioning, inertial and integrated navigation Sensor orientation and calibration, attitude determination Mobile mapping, airborne laser scanning Adjustment methods, Kalman Filtering

Publications

Infoscience publications

Teaching & PhD

Teaching

Environmental Sciences and Engineering

PhD Programs

Courses

Inference for large-scale time series with application to sensor fusion

Large-scale time series analysis is performed by a new statistical tool that is superior to other estimators of complex state-space models. The identified stochastic dependences can be used for sensor fusion by Bayesian (e.g. Kalman) filtering or for studying changes in natural/biological phenomena.

Estimation methods

The students treat observations affected by uncertainty in a rigorous manner. They master the main methods to adjust measurements and to estimate parameters. They apply specific models to real-world problems encountered in various experimental sciences.

Sensing and spatial modeling for earth observation

Students get acquainted with the process of mapping from images (orthophoto and DEM), as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotemporal variability of processes.

Sensor orientation

Determination of spatial orientation (i.e. position, velocity, attitude) via integration of inertial sensors with satellite positioning. Prerequisite for many applications related to remote sensing, environmental monitoring, mobile mapping, robotics, space exploration, smart-phone navigation, etc.

Robotics practicals

The goal of this lab series is to practice the various theoretical frameworks acquired in the courses on a variety of robots, ranging from industrial robots to autonomous mobile robots, to robotic devices, all the way to interactive robots.