Overview
Pose estimation and localization are critical components for both autonomous systems and systems that require perception for situational awareness. Fusing data from multiple sensors and applying fusion filters is a typical workflow required for accurate localization. Sensor simulation can help with modeling different sensors such as IMU and GPS. Moreover, simulated data can be used to augment the data recorded or streamed from inertial sensors. Further, you can use filters to fuse individual measurements to provide a better result. You can tune these filters based on the sensors and the end-application.
Highlights
Through several examples, we will cover:
- Modeling sensors, tuning filters and calibrating IMU measurements with Allan Variance
- IMU, GPS, altimeter, and wheel encoder sensor fusion for inertial navigation
- Pose estimation from asynchronous sensors fusing accelerometer, gyroscope, magnetometer and GPS
- Automatic filter tuning to find optimal noise parameter values
- Visual-inertial odometry using synthetic data
About the Presenters
Rick Gentile, Sr. Product Manager, MathWorks
Rick Gentile focuses on Radar, Signal Processing, and Sensor Fusion applications at MathWorks. Prior to joining MathWorks, Rick was a Radar Systems Engineer at MITRE and MIT Lincoln Laboratory, where he worked on the development of many large radar systems. Rick also was a DSP Applications Engineer at Analog Devices where he led embedded processor and system level architecture definitions for high performance signal processing systems, including automotive driver assist systems. Rick co-authored the text “Embedded Media Processing” and maintains a monthly blog on mwrf.com. He received a B.S. in Electrical and Computer Engineering from the University of Massachusetts, Amherst and an M.S. in Electrical and Computer Engineering from Northeastern University, where his focus areas of study included Microwave Engineering, Communications and Signal Processing.
Mihir Acharya, Product Manager, MathWorks
Mihir Acharya supports Robotics and Autonomous Systems applications at MathWorks, focusing on Autonomous Navigation. 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).
Brian Fanous, Principal Software Engineer, MathWorks
Brian Fanous develops inertial navigation and sensor fusion tools for MathWorks products. Prior to that, Brian designed HDL and GPU algorithms for signal processing and communications toolboxes at the MathWorks. He has previously worked at MIT Haystack Observatory developing large radio astronomy array hardware. Brian received a B.S in Electrical Engineering and a B.A. in Mathematics from Tufts University and an M.S. in Electrical Engineering from the University of California at Berkeley.
