| Description |
The goal of this dissertation is to enable an aerial robotic system (including an aircraft with a cable-suspended payload) to fly autonomously in GPS-denied environments through vision from a single monocular camera. To achieve this goal, new estimation, motion planning, and control algorithms that exploit the image-based visual-servo framework are developed. Rigorous stability analysis based on the Lyapunov approach is also presented for the developed control systems. The image-based framework is of interest because of its robustness to image noise and lower computational demand compared to position-based techniques where pose estimation is required. However, this research tackles inherent challenges including nonlinear dynamics, singularity issues, and complex stability analysis for cases with relaxed constraints on initial estimation errors, vehicle position, and height. The resulting theoretical outcomes are validated experimentally by showing demonstrations of aerial-robot assisted operations related to emergency response, search and rescue, and package delivery in GPS-denied environments, such inside of buildings or in urban canyons where global vehicle localization and control schemes are ineffective or impractical. Firstly, a new kinematic image-based control algorithm using a mobile overhead camera for aerial robots is developed. The control algorithm exploits adaptation to compensate for uncertainties in the camera parameters and depth information, and repetitive control is used to reject inherent periodic tracking errors in the image plane. Stability analysis in the Lyapunov sense is shown. Both simulations and physical experiments are provided for a quadcopter to demonstrate the approach. Secondly, a new nonlinear flight control scheme that combines a vision-based closed-loop observer with a backstepping-based controller using an onboard camera and the inertial measurement unit (IMU) is developed. This new approach is computationally efficient and asymptotically stable. Flight tests are conducted to validate the algorithms capabilities for take-off, to hover, to track trajectory, and landing. Finally, a new flight control scheme that combines an image-based position controller and a quaternion-based attitude controller are created that enables and aerial robot to fly aggressively through several narrow windows without knowledge of the robot's position and window size, and the approach is extended to control the motion of a cable-suspended payload for package delivery. Both simulations and physical experiments demonstrate that the approaches are capable of flying into and out of a small house and picking up and transporting several packages with unknown mass. iv |
