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Multi-Sensor Continuous-Time SLAM for UAVs
The goal of this project is a continuous-time incremental trajectory estimation and mapping formulation for multiple sensors on-board of fixed-wing or rotary-wing UAVs
Keywords: Simultaneous Trajectory Estimation and Mapping (STEAM), Simultaneous Localization and Mapping (SLAM), UAVs, State Estimation, Multi-Sensor
Relevant publications:
- S. W. Anderson, "Batch Continuous-Time Trajectory Estimation"
- X. Yan, V. Indelmann, B. Boots, "Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping"
For more information, please send an email with your CV and transcript of records to hitimo@ethz.ch
Relevant publications:
- S. W. Anderson, "Batch Continuous-Time Trajectory Estimation"
- X. Yan, V. Indelmann, B. Boots, "Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping"
For more information, please send an email with your CV and transcript of records to hitimo@ethz.ch
- Literature review on incremental continuous-time simultaneous trajectory estimation and mapping (STEAM)
- Implementation of continuous-time STEAM formulation for various sensors
- Validation in existing comprehensive simulation environment
- Validation on existing real-world datasets
- Comparison to classical discrete-time formulation
- Literature review on incremental continuous-time simultaneous trajectory estimation and mapping (STEAM) - Implementation of continuous-time STEAM formulation for various sensors - Validation in existing comprehensive simulation environment - Validation on existing real-world datasets - Comparison to classical discrete-time formulation
- Strong background in State Estimation
- Experience in C++ beneficial
- Strong background in State Estimation - Experience in C++ beneficial