ABSTRACT
Fully autonomous vehicles, capable of completing entire end-to-end journeys without the interference of a human driver, will be one of the biggest transforming technologies of the next decades. As the journey towards fully autonomous vehicles progresses, there will be an increase in the number of highly automated vehicles on the roads, requiring the human driver to take back control in situations, which cannot be handled by the vehicle autonomously. These human-robot take-over requests can lead to safety risks, in particular in scenarios when the driver fails to understand the take-over request and, hence, lacks situational awareness. This paper presents the acceptance and usability assessment of a haptic feedback driver seat capable of informing the driver of a take-over request through static mechano-tactile haptic feedback. The seat is equipped with an embedded array of soft pneumatic actuators, that have been fully modelled and characterised. The evaluation process of the haptic feedback seat engaged 21 participants who experienced both auditory and haptic feedback from the seat in a number of simulation experiments within a driving simulator. The vehicular technology was assessed through well-established methods to understand the acceptance (usefulness and satisfaction) and usability of the haptic feedback driver seat.
ABSTRACT
Inspection in confined spaces and difficult-to-access machines is a challenging quality assurance task and particularly difficult to quantify and automate. Using the example of aero engine inspection, an approach for the high-precision inspection of movable turbine blades in confined spaces will be demonstrated. To assess the condition and damages of turbine blades, a borescopic inspection approach in which the pose of the turbine blades is estimated on the basis of measured point clouds is presented. By means of a feature extraction approach, film-cooling holes are identified and used to pre-align the measured point clouds to a reference geometry. Based on the segmented features of the measurement and reference geometry a RANSAC-based feature matching is applied, and a multi-stage registration process is performed. Subsequently, an initial damage assessment of the turbine blades is derived, and engine disassembly decisions can be assisted by metric geometry deviations. During engine disassembly, the blade root is exposed to high disassembly forces, which can damage the blade root and is crucial for possible repair. To check for dismantling damage, a fast inspection of the blade root is executed using the borescopic sensor.
ABSTRACT
To further advance closed-loop control for soft robotics, suitable sensor and modeling strategies have to be investigated. Although there are many flexible and soft sensors available, the integration into the actuator and the use in a control loop is still challenging. Therefore, a state-space model for closed-loop low-level control of a fiber-reinforced actuator using pressure and orientation measurement is investigated. To do so, the integration of an inertial measurement unit and geometric modeling of actuator is presented. The piecewise constant curvature approach is used to describe the actuator's shape and deformation variables. For low-level control, the chamber's lengths are reconstructed from bending angles with a geometrical model and the identified material characteristics. For parameter identification and model validation, data from a camera tracking system is analyzed. Then, a closed-loop control of pressure and chambers' length of the actuator is investigated. It will be shown, that the reconstruction model is suitable for estimating the state variables of the actuator. In addition, the use of the inertial measurement unit will demonstrate a cost-effective and compact sensor for soft pneumatic actuators.
