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Factor-graph based state-estimation for Aerial Robots using novel sensors
Algorithmically integrate a novel type of inertial sensor into our state estimation pipeline. Your results will be used to improve our cutting edge aerial robot.
Unlike regular drones, our novel aerial robots are generic flying robots that can perform physical work from flight.
To do so, they need a very good estimate of their state, as disturbances and model inaccuracies need to be sensed and reacted to as quickly as possible.
In this thesis, you'll explore the integration of a novel type of IMU, that provides some additional hardware features for high-accuracy sensing, into our factor-graph based state estimation pipeline.
You'll get valuable hands-on experience with real state-of-the-art sensor fusion on one of the most advanced aerial robots in the field.
Unlike regular drones, our novel aerial robots are generic flying robots that can perform physical work from flight. To do so, they need a very good estimate of their state, as disturbances and model inaccuracies need to be sensed and reacted to as quickly as possible. In this thesis, you'll explore the integration of a novel type of IMU, that provides some additional hardware features for high-accuracy sensing, into our factor-graph based state estimation pipeline. You'll get valuable hands-on experience with real state-of-the-art sensor fusion on one of the most advanced aerial robots in the field.
- Literature Research
- Familiarization with sensor hardware and characteristics
- Developing novel probabilistic sensor fusion factors
- Integration into complete system
- Evaluation and comparison with traditional IMU
- Literature Research - Familiarization with sensor hardware and characteristics - Developing novel probabilistic sensor fusion factors - Integration into complete system - Evaluation and comparison with traditional IMU
- Good knowledge of C++ and Python
- Experience with ROS
- Basic knowledge of state estimation (IMUs, Kalman filtering, etc)
- Desirable: Basic knowledge of factor graphs
- Very optional but nice to have: Experience with GTSAM (library)
- Good knowledge of C++ and Python - Experience with ROS - Basic knowledge of state estimation (IMUs, Kalman filtering, etc) - Desirable: Basic knowledge of factor graphs - Very optional but nice to have: Experience with GTSAM (library)
Please contact via Sirop directly, including a recent transcript of records and CV. We would also appreciate a very short statement about your motivation/why you are interested in the topic.
Please contact via Sirop directly, including a recent transcript of records and CV. We would also appreciate a very short statement about your motivation/why you are interested in the topic.
