We are excited to announce the INERTIAL 2020 Tutorials!

 

08:00 - 10:00

Giacomo Langfelder

Politecnico di Milano, Italy

"What is good and what is bad challenging about frequency modulated inertial sensors"

This tutorial will first address a review of frequency modulated (FM) MEMS accelerometers and gyroscopes, in terms of different possible working principles, along with an overview of the required electronic building blocks. The focus will then be moved on how to perform a system-level comparison against their amplitude-modulated (AM) counterparts, to highlight sensors and electronics requirements, and to identify the real advantages and a few drawbacks challenges of various FM sensing concepts. Perspectives for high scale-factor stability and high offset-stability will be commented in a stimulating conclusive discussion.

10:20 - 12:20

Akira Umeda

VectorDynamics Corporation

"Consideration and Experimental Results on the Calibration of Inertial Sensors"

Cores of ISO 16063 series standard for accelerometers and gyroscopes will kick off my tutorial talk. They are the de facto standard measurement method used to both single axis accelerometers manufactured by the conventional machining and accelerometers made by silicon micro-machining in particular for multi-axis accelerometers. So-called measurement standard has long been supplied by this technique all over the world by the metrology standard laboratories such as PTB, NIST, and AIST, Japanese metrology laboratories.

I will point out the matter not considered in the techniques.

The mathematical function of the inertial sensors is to transfer the inertial physical quantities such as acceleration and angular velocity in the real engineering space to the signal space. Both spaces are mathematically vector spaces. Therefore sensitivity shall be expressed by matrix if the transformation between the two vector spaces is linear. The mathematical condition that the matrix sensitivity is uniquely derived is explained by using the elementary theory of linear algebra. The explanation ranges up to six-axis inertial sensors.

As an experimental result, I will show you the sensitivity of three-axis accelerometer and six-axis IMU. I will talk about the experimental result that gave me the confidence about the scientific correctness of the method.

I will talk about the instrumentation for motion generation, since vibration generation with 6 DOF is indispensable in this method.

I will talk about the quantitative derivation of non-linearity up to 5th order.

I am going to talk about the IEC 60747-14-4 Semiconductor Accelerometers that is an international standard based on the matrix sensitivity concept.

Uncertainty is a very important concept to be thought in the calibration. I am going to talk about the influence of the uncertainty on the selection of the amplitude vector in the derivation of the sensitivity matrix. I would like to refer to GUM that has long been thought as a Bible.

13:50 - 15:50

"Attitude estimation algorithm and autonomous flight control for small unmanned aerial vehicles"

It is not well known about attitude estimation and flight control mechanisms of small unmanned aerial vehicles(UAVs) that fly in three-dimensional space. This is because a commercially available flight controller can be mounted on the UAV body and autonomous flight can be relatively easily performed. However, its contents are very complicated. In this tutorial, we introduce in detail the attitude estimation algorithm of a small unmanned aerial vehicle flying in three-dimensional space, and describe in detail the model-based autonomous flight control including attitude control using the estimated attitude. We will introduce a quaternion-based algorithm based on three-axis acceleration, gyro, and azimuth data for the attitude estimation algorithm and several approaches for model-based autonomous flight control. This tutorial deals with a multi-rotor drone. We will look into future prospect what guidance, navigation, and control should be in the “sky industrial revolution” era, where many drones fly over the city.

16:10 - 18:10

“Vision Aided Navigation, Guidance and Control in Natural Systems”

In 2019 at this venue, I gave a tutorial looking closely at inertial sensing in insects. This is a fast mechanism to stabilize insect flight that is detected with a variety of body parts. Beyond inertia, there are at least a dozen modes of sensing and half a dozen modes of transduction that all contribute to the guidance, navigation, and control of natural systems.  Vision is a passive sense for autonomous guidance without external inputs that is so critical for flight that blinded insects will not fly. They use it for a wide variety of tasks and they multitask by accomplishing multiple functions with that same sensor. Insects are not dependent on GPS, they are situationally aware, and they navigate over local and long ranges. Also vision contributes heavily to guidance for landing, object detection, target classification and tracking, collision avoidance, interception of prey, stabilization, and avoidance of predators.

 Insects and humans do not always see eye to eye. We will explore the differences between camera type eyes like ours and the compound eyes and simple eyes of insects. We will cover how light is transduced into neural signals, task specific sensor characteristics, and the processing and integration with other senses like inertia to produce amazing behaviors.

Studying these integrated sensing and actuation systems may substantially aid the future development of cheap, fast, agile, autonomous flight. The discovery of the equations of how the bumblebee flies was made possible by combining the tools of engineering and the measurements of biologists, neither discipline alone could have resolved the so-called bumblebee paradox. I will bring the biology if you bring the engineering!