Yuzhe Gao

Micro tandem bi-copters are capable of passing through narrow gaps owing to their particular slender shape. However, the introduction of the tilting servo motors leads to a non-minimum phase roll dynamics, which affects their flight stability when exploring environments with unpredictable disturbances. In this letter, we propose and design a re-configurable aerial platform consisting of two modular bi-copters with an undocking mechanism. In combined configuration, a crossover docking approach is employed to compensate for the poor stability in their servo-controlled attitude of each bi-copter. In bi-copter configuration, the minimum size (equal to ideal passable gap's width) of the system was reduced by 58% through mid-air separation. In detail, to compare the attitude response of the two configurations, a dynamic model considering servo response and non-minimum phase is established and simulated, and flying poking experiments were also conducted on them respectively. On the other hand, the performance of single bi-copter including trajectory tracking and passing through narrow gaps was demonstrated through flight tests. Finally, the feasibility of the undocking mechanism was verified by mid-air separation experiments. The proposed system is promising to be applied in scenarios containing both complex perturbations and confined spaces, while also having the potential to improve exploration efficiency through collaborative work.

As an amphibious system, aerial-terrestrial vehicles have demonstrated remarkable environmental adaptability. In order to expand their synergistic advantages, in this letter, an Aerial-Terrestrial vehicle consisting of a pair of unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) is proposed, which is capable of performing UAV-UGV autonomous docking and detaching. Under the docking modality, the proposed vehicle can perform amphibious locomotion to adapt to rugged terrains. Under the detaching mode, the distributed UAV and UGV subsystems gain enhanced accessibility to the confined space and can share both air and land information, which is promising to accomplish collaborative missions. In order to achieve the docking and detaching of the two subsystems, a screw-like binding mechanism is proposed. To implement the binding mechanism, it is separated into two pieces, i.e., ‘screw' and ‘nut,’ which are duel-functioned as the landing gear of the UAV or the UGV roof, respectively. To improve the success rate of docking, a mathematical model of the binding mechanism is established to calculate the ideal curve of the guiding surface, which provides important cues for the mechanism fabrication. With such a binding mechanism, UAV or UGV can execute docking or detachment via screwing-like self-spinning motion. The spinning torque of the UAV and UGV are calibrated by torque measurement tests. As a result, each independent vehicle can generate sufficient power to lock or detach via its original actuators, thus omitting the extra actuators. The full stage control, including air-ground docking-detaching and amphibious locomotion, are validated experimentally.

Unmanned Aerial Vehicles (UAVs) autonomous approaching and landing on mobile platforms always play an important role in various application scenarios. Such a complicated autonomous task requires an integrated multi-sensor system to guarantee environmental adaptability in contrast to using each sensor individually. Multi-sensor fusion perception demonstrates great feasibility to compensate for adverse visual events, undesired vibrations of inertia sensors, and satellite positioning loss. In this paper, a UAV autonomous landing scheme based on multi-sensor fusion is proposed. In particular, Ultra Wide-Band (UWB) sensor, Inertial Measurement Unit (IMU), and vision feedback are integrated to guide the UAV to approach and land on a moving object. In the approaching stage, a UWB-IMU-based sensor fusion algorithm is proposed to provide relative position estimation of vehicles with real time and high consistency. Such a sensor integration addresses the open challenge of inaccurate satellite positioning when the UAV is near the ground. It can also be extended to satellite-denied environmental applications. When the landing platform is detected by the onboard camera, the UAV performs autonomous landing. In the landing stage, the vision sensor is involved. With the visual feedback, a deep-learning-based detector and local pose estimator are enabled when the UAV approaches the landing platform. To validate the feasibility of the proposed autonomous landing scheme, both simulation and real-world experiments in extensive scenes are performed. As a result, the proposed landing scheme can land successfully with adequate accuracy in most common scenarios.