Enhancing Insect Tracking Precision from Drones: Fusing Multiple Sensor Data to Estimate Insect Position with Quantified Uncertainty

• Applicant: Professor Dr. Andrew D. Straw
• Subject Area: Measurement Systems
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 543356743

It has recently become possible to track individual flying insects from multicopters. These systems leverage an active optical sensor to obtain directional measurements to the target insect, enabling detailed monitoring of insect behavior over large spatial scales. However, to reach the potential of such systems, there remains a critical challenge in accurately estimating the position of the tracked insect and quantifying the uncertainty associated with these measurements. In this work, we address this challenge by upgrading tracking data and integrating it with attitude and position information obtained from the sensors used by the multicopter's autopilot system, namely gyroscopes, accelerometers, magnetometers, and GNSS sensors. By performing data fusion, uncertainty quantification, a real-time implementation, and validation and testing, we anticipate significantly extending the current limits of drone-based measurements to track insects in the wild.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2433: Metrology on flying platforms