UBC Theses and Dissertations
High-throughput kinematic tracking of bird wings using inertial sensor arrays Senthivasan, Shreeram
Birds accomplish an impressive diversity of flight maneuvers primarily through variation in the motion of their wings. It is for this reason that an understanding of wing kinematics is of broad interest to the study of the physics and control of bird flight. However, current optical approaches to animal motion capture struggle to automate the tracking of fixed points on the wing due to the periodic folding and occlusion of flight surfaces during flapping flight. This greatly increases the time and effort needed to record wing kinematics, as the raw data must be digitized by hand. In this thesis, I made progress towards a new high-throughput approach to recording wing kinematics using body- and wing-mounted inertial sensors. The data loggers designed for this purpose have a mass of 4g including a battery, and are capable of collecting inertial data from up to four sensors at 450Hz for 20 minutes. An accompanying set of R functions were developed to estimate the orientations of the body and wing segments from the raw inertial data, which in turn were used to estimate joint angles over time. These tools were validated against an optical motion capture system and were able estimate the orientation of individual bodies within 3° and angles between bodies within 6° in controlled tests. However, the tools could not be used to record the wing kinematics of pigeons because the angular velocity of the wings exceeded the sensing range of the gyroscopes used in the current design. Specialized high-range gyroscopes are commercially available and could be incorporated into future designs to overcome this limitation. Inertial motion capture has the potential to be a high-throughput, cost-effective, and portable alternative to high-speed video for recording wing kinematics in freely flying birds. This approach could also be used to record detailed kinematics in other animal systems where optical motion capture is infeasible, such as in situations with poor visibility or to study behaviours that occur over large spatial scales.
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