MATLAB | UAV Flight Log Analysis with MATLAB @MATLAB | Uploaded January 2024 | Updated October 2024, 1 week ago.
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.
In this video, 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
Learn more about UAV Toolbox: bit.ly/UAV-Toolbox
About the Presenters
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 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.
Chapters:
0:35 - Stages in UAV Development
1:50 - Introduction on log files
3:47 - Introduction to Flight Log Analyzer App
9:36 - How to add custom plots
11:35 - Build and Save a Session
14:00 - Troubleshoot flight issues
22:02 - Hardware-in-the-loop
25:06 - Conclusion
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© 2023 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
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.
In this video, 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
Learn more about UAV Toolbox: bit.ly/UAV-Toolbox
About the Presenters
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 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.
Chapters:
0:35 - Stages in UAV Development
1:50 - Introduction on log files
3:47 - Introduction to Flight Log Analyzer App
9:36 - How to add custom plots
11:35 - Build and Save a Session
14:00 - Troubleshoot flight issues
22:02 - Hardware-in-the-loop
25:06 - Conclusion
--------------------------------------------------------------------------------------------------------
Get a free product trial: goo.gl/ZHFb5u
Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2023 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
