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Localization can be achieved by different sensors and techniques such as a global positioning system (GPS), wifi, ultrasonic sensors, and cameras. In this paper, we focus on the laser-based localization method for unmanned aerial vehicle (UAV) applications in a GPS denied environment such as a deep tunnel system. Other than a low-cost 2D LiDAR for the planar axes, a single axis Lidar for the vertical axis as well as an inertial measurement unit (IMU) device is used to increase the reliability and accuracy of the localization performance. We present a comparative analysis of the three selected laser-based simultaneous localization and mapping(SLAM) approaches:(i) Hector SLAM; (ii) Gmapping; and(iii) Cartographer. These algorithms have been implemented and tested through real-world experiments. The results are compared with the ground truth data and the experiments are available at https://youtu.be/kQc3mJjw_mw., Accepted to IROS 2019 Workshop on Challenges in Vision-based Drones Navigation

usc Refereed/Peer-reviewed Today's modern cities depend on basic services such as water and sewer systems including tunnels, which are supported by a pervasive infrastructure. The structural condition of these places is naturally prone to deterioration. Therefore, regular inspections are required for early detection of damage and material failure. It is envisaged that robotic systems may provide an up-to-date solution for this inspection task. Considering the challenging conditions in the surrounding environments, unmanned aerial vehicles (UAVs) may be a potential candidate to meet the need for both purely visual (contactless) and subsurface (contact-based) inspection functionalities. When the interaction with an uncooperative target is required, the UAV needs to be aware of the forces arising during the contact phase. This stage brings additional challenges including a variable center of gravity as well as the moment of inertias due to the shift in the attached parts, sliding on the target because of the surface characteristics and reaching desired interaction levels out of the equilibrium point without crashing the dedicated sensors while creating counter forces (reactions) in a desired manner. At the same time, ultrasonic inspection requires uninterrupted contact in certain force ranges. In order to address these factors in a compact and feasible manner, an optimization algorithm consisting of nonlinear moving horizon estimation (NMHE), which is a part of nonlinear model predictive control (NMPC) is proposed. In this algorithm, the baseline model of the UAV is augmented by the external forces where uncertainties, modeling mismatches and disturbances are lumped. Therefore, the NMHE has estimated these values in an online manner. In a simultaneous fashion, the identified external forces are fed into the NMPC to physically interact with the ceiling during the contact phase. The experimental inspection data is collected while autonomously staying in predefined constraint limits. It is observed that the complete inspection data is obtained and streamed via Bluetooth when the force on the ultrasonic tool reached 5.5 N level. The external force update coming from the estimation allows the proposed approach to reach these interaction levels.

With the recent developments in the unmanned aerial vehicles (UAV), it is expected them to interact and collaborate with their surrounding objects, other robots and people in order to wisely plan and execute particular tasks. Although these interaction operations are inherently challenging as compared to free-flight missions, they might bring diverse advantages. One of them is their basic aerodynamic interaction during the flight in close proximities which can result in a reduction of the controller effort. In this study, by collecting real-time data, we have observed that the current drawn by the battery can be decreased while flying very close to the surroundings with the help of the ceiling effect. For the first time, this phenomenon is analyzed in terms of battery lifetime degradation by using a simple full equivalent cycle counting method. Results show that cycling related effect on battery degradation can be reduced by a 15.77% if the UAV can utilize ceiling effect., ICoIAS 2019