Lecture

Basics of Mobile Robotics: Uncertainties

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In course

MICRO-452: Basics of mobile robotics

This course gives an overview of the field of mobile robotics, introducing to the main techniques and allowing to test them in exercises and a team-based project. ...

Description

This lecture covers the basics of mobile robotics, focusing on the uncertainties involved in localization. Starting with the Bayes filter, the instructor explains the discrete Bayes filter and particle filters. Moving on to the Kalman Filter, the lecture delves into Gaussian representations, sensor fusion, and the Extended Kalman Filter. Practical examples include 1D and 2D localization scenarios, sensor fusion using accelerometers and gyroscopes, and the application of the Extended Kalman Filter in orientation estimation.

Instructor

Francesco Mondada

Dr. Mondada received his M.Sc. in micro-engineering in 1991 and his Doctoral degree in 1997 at EPFL. During his thesis he co-founded the company K-Team, being both CEO and president of the company for about 5 years. He is one of the three main developers of the Khepera robot, considered as a standard in bio-inspired robotics and used by more than 1,000 universities and research centers worldwide. Fully back in research in 2000 and after a short period at CALTECH, he participated to the SWARM-BOTS project as the main developer of the s-bot robot platform, which was ranked on position 39 in the list of The 50 Best Robots Ever (fiction or real) by the Wired Journal in 2006. The SWARM-BOTS project was selected as FET-IST success story by the EU commission. He is author of more than 100 papers in the field of bio-inspired robotics and system level robot design. He is co-editor of several international conference proceedings. In November 2005 he received the EPFL Latsis University prize for his contributions to bio-inspired robotics. In 2011 he received the "Crédit Suisse Award for Best Teaching" from EPFL and in 2012 the "polysphère" award from the students as best teacher in the school of engineering. His interests include the development of innovative mechatronic solutions for mobile and modular robots, the creation of know-how for future embedded applications, and making robot platforms more accessible for education, research, and industrial development.

Official source

Ontological neighbourhood

Information engineering

Artificial intelligence: Computer vision

Related concepts (31)

Gyroscope

A gyroscope (from Ancient Greek γῦρος gŷros, "round" and σκοπέω skopéō, "to look") is a device used for measuring or maintaining orientation and angular velocity. It is a spinning wheel or disc in which the axis of rotation (spin axis) is free to assume any orientation by itself. When rotating, the orientation of this axis is unaffected by tilting or rotation of the mounting, according to the conservation of angular momentum.

Ensemble Kalman filter

The ensemble Kalman filter (EnKF) is a recursive filter suitable for problems with a large number of variables, such as discretizations of partial differential equations in geophysical models. The EnKF originated as a version of the Kalman filter for large problems (essentially, the covariance matrix is replaced by the sample covariance), and it is now an important data assimilation component of ensemble forecasting.

Gaussian function

In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the base form and with parametric extension for arbitrary real constants a, b and non-zero c. It is named after the mathematician Carl Friedrich Gauss. The graph of a Gaussian is a characteristic symmetric "bell curve" shape. The parameter a is the height of the curve's peak, b is the position of the center of the peak, and c (the standard deviation, sometimes called the Gaussian RMS width) controls the width of the "bell".

Accelerometer

An accelerometer is a tool that measures proper acceleration. Proper acceleration is the acceleration (the rate of change of velocity) of a body in its own instantaneous rest frame; this is different from coordinate acceleration, which is acceleration in a fixed coordinate system. For example, an accelerometer at rest on the surface of the Earth will measure an acceleration due to Earth's gravity, straight upwards (by definition) of g ≈ 9.81 m/s2. By contrast, accelerometers in free fall (falling toward the center of the Earth at a rate of about 9.

Ring laser gyroscope

A ring laser gyroscope (RLG) consists of a ring laser having two independent counter-propagating resonant modes over the same path; the difference in phase is used to detect rotation. It operates on the principle of the Sagnac effect which shifts the nulls of the internal standing wave pattern in response to angular rotation. Interference between the counter-propagating beams, observed externally, results in motion of the standing wave pattern, and thus indicates rotation.

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