In this paper, we introduce a Modular Single Actuator Monocopter (M-SAM), which is capable of flying in both singular configuration and cooperative configuration. From singular mode, M-SAMs can be manually assembled into cooperative mode, using magnetic connectors built into the body of each M-SAM unit. The design of the connectors allow for passive separation of the units without the need for a dedicated separating actuator, by harnessing the variable centrifugal force from controlled adjustment of the rotating speed of the craft. To achieve control in both configurations, we firstly studied and analyzed their full dynamic models by introducing equilibrium state and relaxed hovering condition. Next, we derived a reduced model to approximate the dynamical behavior of both singular and cooperative configuration in flight to design a generalized cyclic-based cascaded flight controller. Finally, we validated the proposed controller and separation mechanism by conducting several flight experiments for two M-SAMs in singular mode, cooperative mode as well as mid-air separating under motion capture system.

Large scale aerial deployment of miniature sensors in tough environmental conditions requires a deployment device that is lightweight, robust, and steerable. We present a novel samara-inspired autorotating craft that is capable of two flight modes (autorotating mode and diving mode) with an average glide angle of 28.9$^{\circ }$(1.81 m lateral distance per 1 m loss of altitude) in the former mode. The bidirectional transition between the two modes and directional control is achieved by using only a single actuator. Also, in order to minimize its glide angle, a design optimization methodology is presented for our prototype, diving samara autorotating wing, along with a new cyclic control strategy for directional control of autorotating descent. The dynamic model, simulated in a six degrees-of-freedom environment using the blade element theory, is integrated with genetic algorithm to derive parameters for the wing geometry, flap angle for autorotation, and the proposed cyclic control. The physical prototype autorotates at a descent velocity of 1.43 m/s and rotation speed 4.17 Hz, and is able to transit to diving mode in an average duration of 272 ms to increase its descent velocity by at least 17.6 times. At any point during the dive, it is able to transit back into autorotation in an average duration of 327 ms. Semioutdoor experiments were used to investigate the bidirectional transitions and verify the glide angle (28.9$^{\circ }$), which is much improved from the previous prototype (SAW+, 58.4$^{\circ }$). Lastly, as a demonstration of a real-life deployment scenario and environmental conditions, the prototypes were dropped from a fixed-wing unmanned aerial vehicle at a suburban test site.

In this work, reinforcement learning is used to develop a position controller for an underactuated nature-inspired Unmanned Aerial Vehicle (UAV). This particular configuration of UAVs achieves lift by spinning its entire body contrary to standard multi-rotors or fixed-wing aircraft. Deep Deterministic Policy Gradients (DDPG) with Ape-X Distributed Prioritized Experience Replay was used to train neural network function approximators that were implemented as the final control policy. The reinforcement learning agent was trained in simulations and directly ported over to real-life hardware. Position control tests were performed on the learned control policy and compared to a baseline PID controller. The learned controller was found to exhibit better control over the inherent oscillations that arise from the non-linear dynamics of the platform.

The seeds of Maple trees (Samara) use autorotation as a unique mechanism to disperse their seeds. By exploiting gyroscopic stability of a spinning wing, the Samara is able to cover large horizontal distance despite having no form of propulsion. We applied and adapted this natural ability in our novel concept, the Samara Autorotating Wings (SAW), and extended its stability and direction controllability by generalizing the mechanism to incorporate designs with more than 1 wing. By conceiving cyclic control, the translational motion of autorotation is regulated. A nonlinear model of SAW with $n$ wings is derived and control schemes developed to control the translational position during autorotation. Numerical simulations were performed to investigate the performance of the multi-wing SAW prototypes to track a conical spiral autorotation trajectory. Direct experiments were conducted in a vertical wind-tunnel through a special ball joint that allows z-axis translation and all three rotational degrees of freedom. Finally, free-fall drop tests are used to verify the directional controllability and performance of SAW.