UAV Flight Log Analysis with MATLAB

Overview

Flying a drone, either manually or autonomously, is a complex task. A drone includes several critical parts such as a chassis or platform, motors and sensors. There are numerous reasons why a drone can crash – from incorrect sensor reading to battery issues. It is essential to tune the performance by analyzing the reasons for any failure in simulation or after the test flight.

A flight log analysis tool takes a drone’s log file as an input and provides various plots for flight analysis. You can use the Flight Log Analyzer app with UAV Toolbox in MATLAB for analyzing UAV autopilot flight logs by creating a customized series of plots. You can load different telemetry log files including TLOG, ULOG, and custom file types. You can also use flight log analysis functions to extract and map signals from a telemetry log for generating custom plots.

Highlights

In this webinar, you will learn how to:

• Use Flight Log Analyzer app
• Analyze UAV autopilot flight logs
• Import custom flight log and signal data
• Troubleshoot flight issues by identifying anomalies in flight data

About the Presenters

Mihir Acharya, Product Manager, MathWorks

Mihir Acharya supports Robotics and Autonomous Systems applications at MathWorks, focusing on UAVs and Autonomous Navigation solutions. Prior to MathWorks, Mihir has worked with ABB Corporate Research where he designed robot end effectors for pick-and-place. Mihir also worked with Omron Robotics and developed path planning applications for mobile robots. Mihir has an M.S. in Robotics Engineering from Worcester Polytechnic Institute (WPI).

Venkatesh BalaSubburaman, Development Lead, MathWorks

Venkatesh BalaSubburaman focuses on development of UAV and Robotics algorithms and tools at MathWorks. Prior to MathWorks, Venkatesh was a team lead at Uurmi Systems (acquired by MathWorks) in Hyderabad (India), where he worked on vision and control algorithms for autonomous indoor quadcopters. Venkatesh was worked as an R&D Engineer at Multitel (Belgium), where he developed vision algorithms to detect material defects and crowd analysis. He has also worked on biometrics technologies for automotive use cases at General Motors (Bangalore) and control systems for magnetic bearing at General Electric. He received his B.E in Electronics and Communication Engineering from Ramaiah Institute of Technology, Bangalore and an M.S in Computer Science from Indian Institute of Technology Madras and PhD in Electrical Engineering from École polytechnique fédérale de Lausanne, Switzerland, where his thesis was on object detection and machine learning.