Towards Realization of Aerial Mobile Manipulation: Multirotor Classification and Adaptability to Unknown Environment

Multirotor unmanned aerial vehicles (UAVs) added with the ability to physically interact with the environment has opened endless possibilities for aerial mobile manipulation tasks. With the unlimited reachable workspace and physical interaction capabilities, such robots can enhance human ability to perform dangerous and hard-to-reach tasks. However, realizing aerial mobile manipulation in real-world scenarios is challenging with respect to the diversity in aerial platforms, control fidelity and susceptibility to variations in the environment. Therefore, the first part of the dissertation provides tools to  classify and evaluate different multirotor designs. A measure of responsiveness of a multirotor platform in exerting generalized forces and rejecting disturbances is discussed through the control bandwidth analysis. Superiority in control bandwidth for fully-actuated multirotors is established in a comparison with equivalent under-actuated multirotors. To further classify and distinguish multirotor platforms, a new mobility measure is proposed and compared by surveying all aerial platforms employed for aerial mobile manipulation. In compliance to the control bandwidth analysis, the mobility measure for fully-actuated multirotors is relatively higher making them better suited for manipulation tasks. 

Aerial physical interaction, as a part of aerial mobile manipulation, with partially unknown environments is challenging due to the uncertainties imposed while dexterously exerting force signatures. A hybrid physical interaction (HyPhI) controller is proposed to enable constrained force contact with a steady transition from unconstrained motion, by squelching excess energy during initial impact. However, uncertainties posed by the partially unknown environment requires to understand the surrounding environment and their current physical states, that can enhance interaction performance. The limited resources and flight time of the multirotors requires to simultaneously understand the environment and perform aerial physical interactions. Inspection-on-the-fly is an uncanny ability of humans to intuitively infer states during manipulation while reducing the necessity to conduct inspection and manipulation separately. In this dissertation, the inspection-on-the-fly method based HyPhI controller is proposed to engage in a steady contact with partially unknown environments, while simultaneously estimating the physical states of the surfaces. The proposed method is evaluated in a mockup of real-world facility, to understand the surface properties while engaging in steady interactions. Further, such inspection of surfaces and estimation of various states enables a deeper understanding of the environment while enhancing the ability to physically interact.