The recent advances in state estimation, perception, and navigation algorithms have significantly contributed to the ubiquitous use of quadrotors for inspection, mapping, and aerial imaging applications. To further increase the versatility of quadrotors, recent works investigated the use of an adaptive morphology, which consists of modifying the shape of the vehicle during flight to suit a specific task or environment. However, these works either increase the complexity of the platform or decrease its controllability. In this paper, we propose a novel, simpler, yet effective morphing design for quadrotors consisting of a frame with four independently rotating arms that fold around the main frame. To guarantee stable flight at all times, we exploit an optimal control strategy that adapts on the fly to the drone morphology. We demonstrate the versatility of the proposed adaptive morphology in different tasks, such as negotiation of narrow gaps, close inspection of vertical surfaces, and object grasping and transportation. The experiments are performed on an actual, fully autonomous quadrotor relying solely on onboard visual-inertial sensors and compute. No external motion tracking systems and computers are used. This is the first work showing stable quadrotor flight without requiring any symmetry of the morphology.

The combination of bioinspired morphing wing and tail made of artificial feathers improves the flight performance of drones.

An origami inspired by insect wings addresses the challenges of achieving both high load bearing and resilience in folding structures.

A variable stiffness fiber made of silicone and low melting point alloys quickly becomes >700 times softer and >400 times more deformable when heated above 62 °C. It shows remarkable self-healing properties and can be clamped, knitted, and bonded, as shown in a foldable multi-purpose drone, a wearable cast for bone injuries, and a soft multi-directional actuator.

Small-winged drones can face highly varied aerodynamic requirements, such as high manoeuvrability for flight among obstacles and high wind resistance for constant ground speed against strong headwinds that cannot all be optimally addressed by a single aerodynamic profile. Several bird species solve this problem by changing the shape of their wings to adapt to the different aerodynamic requirements. Here, we describe a novel morphing wing design composed of artificial feathers that can rapidly modify its geometry to fulfil different aerodynamic requirements. We show that a fully deployed configuration enhances manoeuvrability while a folded configuration offers low drag at high speeds and is beneficial in strong headwinds. We also show that asymmetric folding of the wings can be used for roll control of the drone. The aerodynamic performance of the morphing wing is characterized in simulations, in wind tunnel measurements and validated in outdoor flights with a small drone.

The protection and restoration of the biosphere is crucial for human resilience and well-being, but the scarcity of data on the status and distribution of biodiversity puts these efforts at risk. DNA released into the environment by organisms, i.e., environmental DNA (eDNA), can be used to monitor biodiversity in a scalable manner if equipped with the appropriate tool. However, the collection of eDNA in terrestrial environments remains a challenge because of the many potential surfaces and sources that need to be surveyed and their limited accessibility. Here, we propose to survey biodiversity by sampling eDNA on the outer branches of tree canopies with an aerial robot. The drone combines a force-sensing cage with a haptic-based control strategy to establish and maintain contact with the upper surface of the branches. Surface eDNA is then collected using an adhesive surface integrated in the cage of the drone. We show that the drone can autonomously land on a variety of branches with stiffnesses between 1 and 10 ³ newton/meter without prior knowledge of their structural stiffness and with robustness to linear and angular misalignments. Validation in the natural environment demonstrates that our method is successful in detecting animal species, including arthropods and vertebrates. Combining robotics with eDNA sampling from a variety of unreachable aboveground substrates can offer a solution for broad-scale monitoring of biodiversity.