Real-time UAV Complex Missions Leveraging Self-Adaptive Controller with Elastic Structure

The expectation of unmanned air vehicles (UAVs) pushes the operation environment to narrow spaces, where the systems may fly very close to an object and perform an interaction. This phase brings the variation in UAV dynamics: thrust and drag coefficient of the propellers might change under different proximity. At the same time, UAVs may need to operate under external disturbances to follow time-based trajectories. Under these challenging conditions, a standard controller approach may not handle all missions with a fixed structure, where there may be a need to adjust its parameters for each different case. With these motivations, practical implementation and evaluation of an autonomous controller applied to a quadrotor UAV are proposed in this work. A self-adaptive controller based on a composite control scheme where a combination of sliding mode control (SMC) and evolving neuro-fuzzy control is used. The parameter vector of the neuro-fuzzy controller is updated adaptively based on the sliding surface of the SMC. The autonomous controller possesses a new elastic structure, where the number of fuzzy rules keeps growing or get pruned based on bias and variance balance. The interaction of the UAV is experimentally evaluated in real time considering the ground effect, ceiling effect and flight through a strong fan-generated wind while following time-based trajectories.Comment: 18 page

UAV Control in Close Proximities - Ceiling Effect on Battery Lifetime

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.Comment: ICoIAS 201

Evaluating Immersive Teleoperation Interfaces: Coordinating Robot Radiation Monitoring Tasks in Nuclear Facilities

We present a virtual reality (VR) teleoperation interface for a ground-based robot, featuring dense 3D environment reconstruction and a low latency video stream, with which operators can immersively explore remote environments. At the UK Atomic Energy Authority's (UKAEA) Remote Applications in Challenging Environments (RACE) facility, we applied the interface in a user study where trained robotics operators completed simulated nuclear monitoring and decommissioning style tasks to compare VR and traditional teleoperation interface designs. We found that operators in the VR condition took longer to complete the experiment, had reduced collisions, and rated the generated 3D map with higher importance when compared to non-VR operators. Additional physiological data suggested that VR operators had a lower objective cognitive workload during the experiment but also experienced increased physical demand. Overall the presented results show that VR interfaces may benefit work patterns in teleoperation tasks within the nuclear industry, but further work is needed to investigate how such interfaces can be integrated into real world decommissioning workflows

Deposition dynamics and analysis of polyurethane foam structure boundaries for Aerial Additive Manufacturing

Additive manufacturing in construction typically consists of ground-based platforms. Introducing aerial capabilities offers scope to create or repair structures in dangerous or elevated locations. The Aerial Additive Manufacturing (AAM) project has developed a pioneering approach using Unmanned Aerial Vehicles (UAV, ‘drones’) to deposit material during self-powered, autonomous, untethered flight. This study investigates high and low-density foams autonomously deposited as structural and insulation materials. Drilling resistance, mechanical, thermal and microscopy tests investigate density variation, interfacial integrity and thermal stability. Autonomous deposition is demonstrated using a flying UAV and robotic arm. Results reveal dense material at interfaces and directionally dependent cell expansion during foaming. Cured interfacial regions are vulnerable to loading parallel to interfaces but resistant to perpendicular loading. Mitigation of trajectory printing errors caused by UAV flight disturbance is demonstrated by a stabilising end effector, with trajectory errors ≤10 mm. AAM provides a significant development towards on-site automation in construction

Design, modeling, and predictive control of aerial physical interaction towards proactive maintenance

Modern cities are dependent on basic services like water and sewer systems including tunnels, which are supported by a pervasive infrastructure. The structural condition of these places is prone to deterioration. To protect the integrity of such systems, regular inspection is required to detect the onset of damage and material failure. It is envisaged that several robotic systems may provide a solution for the inspection task. When the inspection is purely visual, cameras might provide the necessary functionality. However, the subsurface inspection may require a different approach. It is explored that unmanned aerial vehicle (UAV) with contacting probes may be an option. Deploying a UAV to perform contact inspection can be a more demanding task. First, the inspection tool shifts the center of mass and moment of inertias. Second, the terminal velocity needs to be regulated for soft contact. This phase necessitates the system to be working in faster cycles as compared to the free-flight regime. The last challenge, posed by the interaction tool, comes from the sliding phase on the surface because bouncing occurs while it moves. In addition, ceiling effect where variable rotor wake degrades the performance of tracking predefined trajectory, and an unknown surface that must be included in the control algorithm and interaction tool design. The available approaches can handle the UAV control while it flies in free-flight. However, the challenges associated with the interaction require the system to be more responsive, adaptive and resilient. Since the level of interaction requires a force bound, the system has to explicitly consider this limit. The system needs to maintain contact in a certain force range to collect the data while not crashing the sensor at the top. The current state of the art considering constraints makes use of two individual models interaction problems; free-flight and contact phase models that bring additional complexity. Moreover, nominal optimization-based approaches are considered in the UAV control for the physical interaction tasks, wherein the system is lacking the ability to take external forces, changing parameters and unmodelled dynamics into account. In this thesis, a predictive UAV control is proposed to investigate interactions during the contact phase operation in close proximities to the surroundings. The main contribution of this study lies in two aspects: modeling and control of the UAV interaction problem. As opposed to multi-model approaches, a modeling of the whole system is presented with a centralized algorithm in which free flight, target approach, interaction, and sliding have been included. Additionally, a constraint optimization-based algorithm is designed to identify the external forces coming from the interaction tool and environment. It has shown through experiments that the proposed approach is efficient in terms of the optimized performance and applicability. The external force information increases the model size but the efficient open-source solver is adapted to leverage the problem, which consists of a nonlinear predictive controller and nonlinear moving horizon estimator, in milliseconds. In the proposed approach; the disturbances, changing parameters and unmodelled dynamics can be represented through external forces. Therefore; it does not require a precise model, external force measurement, and exact information about the environment. The hypothesized force-based centralized approach implements an optimization method by explicitly considering the external forces in the algorithm to solve the contact-based nondestructive inspection operation in the air. The results have shown that the disturbance and offset caused by the ceiling and tool effects are eliminated on the vertical axis and mitigated on the planar axes. Since there is a direct actuation on the vertical channel, it is achieved to suppress the external forces (in overall 70%). For the planar axes, the actuation is driven by the attitude angles which resulted in an attenuation of the external forces (up to 45%). It is illustrated that the selected configuration in which an elastic compliance mechanism is attached to the UAV is a pioneer to inspect surrounding environments.Doctor of Philosoph