- Optimization and filter-based Motion Cueing Algorithms
- Driving simulation
- Kinematics of parallel robot structures
Student projects covering the research topics can be found here.
A driving simulator generates vestibular, visual, acoustic and haptic stimuli (Cues) in order to immerse test persons into a virtual driving scenario. Dynamic movements of the simulator result in forces perceived by the test person’s body. In the field of driving and flight simulation these kind of motion stimuli are called Motion Cues. By analogy, control strategies to estimate the input signal of the motion system are denoted Motion Cueing Algorithms. A significant challenge in the development of Motion Cueing Algorithms are driving simulator restrictions concerning workspace barriers and dynamic boundaries. Most of the time the needed working space as well as the required accelerations are not feasible, for example if a driver accelerates over a distance of 100 m. Typically the following methods are taken into account to guarantee the physical limits:
1. Scaling and filtering of accelerations estimated by the dynamic simulation
2. Using the gravitational acceleration by slowly tilting in one plane in order to reproduce continuous and/or long-running accelerations
3. Moving the platform to a more strategic position (prepositioning) to optimize working space for upcoming manoeuvres, such as turns. Prepositioning methods are commonly known as washout filters.
The technical system often consists of a Hexapod (Stewart-Platform) which exhibits an efficient structure with three translational and rotational degrees of freedom. As a consequence of the non-linear mapping between working space and joint coordinate system the barriers of the working space are non-linear as well and the degrees of freedom are not independent of each other. Discrepancies between the projected visual view and dynamic movements result in disturbing stimuli, which are called False Cues. These cues are most of the time provoked by working space barriers and/or deficits in the Motion Cueing Algorithm, for example if the platform moves to its actuators limits. Frequently occurring False Cues can lead to an abortion of the simulation process as test persons suffer from motion sickness.