IAAC – Master in Robotics and Advanced Construction
Hardware II seminar
Faculty: Óscar González
Faculty Assistant: Daniil Koshelyuk
SENSORS & DATA ANALYSIS
Credits: MRAC-IAAC /Wearable-Assistive-Robotics
Syllabus
This seminar will be an introduction to sensors and data analysis techniques. Sensors are a key part of any real world project, as they will give us feedback on the operation of our systems, designs, as well as being a great means towards a better understanding of our environment in ways we initially did not see. In other words, the data and insights from it that can be derived from sensors will bring a much richer understanding of the systems we are dealing with.
We will learn that no sensor setup is perfect, and we will understand the need of data analysis in our systems. We will also see how data analysis can improve not only sensors’ data, but also make use of small pieces of information coming from simple sensors into much broader data flows that can be used in various ways.
We will start with a review of the sensor basics from the perspective of hardware and software, going into more advanced setups in different platforms and sensing techniques.
From 1D sensors, such as touch, distance, orientation, environmental, among others we will cover a wide range of possibilities to capture the environment in many different ways. We will look at how to log the data coming from the sensors, how to process it and extract the most relevant information. With cameras and RGBD cameras along with computer vision techniques we will bring the sense of sight to our robots allowing them to detect faces, objects and orientate within the space.
Learning objectives
At course completion the student will:
- Understanding different types of sensors and measurement principles.
- Learn how to extract meaningful information from different sensor ranges using data analysis techniques.
- Understand data logging processes in real time and with buffers.
- Understand the trade-off between cost and complexity in the sensor selection.