Insects like the stick insect can walk on rough terrain, climb obstacles, and use their legs for other behavioural tasks such as searching or reaching. These complex movements are coordinated by a fairly small, experimentally amenable and reasonably well-studied nervous system. Because of the resource-efficient information processing for solving complex behavioural tasks, the analysis and modelling of insect locomotion have been proposed as a basis for improving artificial autonomous walking robots.
The movement of stick insects can be measured by marker-based motion capturing: markers are attached to the body of the insect and tracked by an infrared camera system. The resulting trajectories (time-ordered xyz -coordinates) describe the movement of the insect in space. Volker Dürr’s group recorded several hours of locomotion sequences from different stick insect species by motion capture. The interpretation of the trajectory data is dependent on the body morphology and the position of the markers on the body. Motion capture datasets have been released in the past, but without specifying the anatomy of the test
subject and the exact marker locations, such that these datasets are of limited use outside their original purpose.
A novel approach is to provide sufficient annotation for calculating joint angle time courses for all degrees of freedom from the trajectory data. This would allow the data to be interpreted and reused in other contexts. Pioneering this approach, the EU project EMICAB will make such calculated data publicly available alongside the experimental raw data and metadata about the experimental conditions under which the data was obtained. A semantic annotation of these datasets would greatly improve their retrieval and interpretation by potential future users.