Steffen Kirchgeorg

Environmental DNA (eDNA) analysis is a powerful tool for studying biodiversity in forests and tree canopies. However, collecting representative eDNA samples from these high and complex environments remains challenging. Traditional methods, such as surface swabbing or tree rolling, are labor-intensive and require significant effort to achieve adequate coverage. This study proposes a novel approach for unmanned aerial vehicles (UAVs) to collect eDNA within tree canopies by using a surface swabbing technique. The method involves lowering a probe from a hovering UAV into the canopy and collecting eDNA as it descends and ascends through branches and leaves. To achieve this, a custom-designed robotic system was developed featuring a winch and a probe for eDNA collection. The design of the probe was optimized, and a control logic for the winch was developed to reduce the risk of entanglement while ensuring sufficient interaction force to facilitate transfer of eDNA onto the probe. The effectiveness of this method was demonstrated during the XPRIZE Rainforest Semi-Finals as 10 eDNA samples were collected from the rainforest canopy, and a total of 152 molecular operational taxonomic units (MOTUs) were identified using eDNA metabarcoding. We further investigate how the number of probe interactions with vegetation, the penetration depth, and the sampling duration influence the DNA concentration and community composition of the samples.

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 10³ 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.

Forests provide vital resources and services for humanity, but preserving and restoring them is challenging due to the difficulty of obtaining actionable data, especially in inaccessible areas such as forest canopies. To address this, we follow the lead of arboreal animals that exploit multiple modes of locomotion.We combine aerial and tethered movements to enable AVOCADO to navigate with in a tree canopy.Starting from the top of a tree, it can descend with the tether and maneuver around obstacles with thrusters. We extend our previous work with a new mechanical design with a protective shell, increased computational power and cameras for state estimation. We introduce a dynamic model and simulation, and perform a quasi-static and dynamic validation. For autonomy, we derive a control framework in simulation to regulate tether length,tilt and heading, before transfer to the robot. We evaluate the controllers for trajectory tracking through experiments. AVOCADO can follow trajectories around obstacles and reject disturbances on the tether. Exploiting multimodal mobility will advance the exploration of tree canopies to actively monitor the true value of our forests.

Labour and resource intensive data collection methods drive the use of unmanned aerial vehicles in the field of environmental monitoring. UAV supported sensor deployment in forests can improve localized and continuous monitoring. To advance this field, we present a two fingered gripper with spines integrated on three phalanxes. The softness of the fingers combined with compliantly-supported microspines integrated into adjustable microspine-clusters allow the gripper to wrap and adhere to tree branches. With a differential drive actuation, microspine cluster adjustability as well as load-sharing between spine clusters is achieved. We characterize the bending behaviour of the soft fingers that adapt to curved and irregular objects. We show that the implementation of compliantly-supported and adjustable microspine-clusters increase holding force and that load-sharing between spine clusters is achieved with the differential drive actuation. The demonstration of UAV perching on a tree branch with the gripper shows that sensor deployment in these environments can be achieved.

The collection of environmental and biodiversity data is essential to manage, preserve and restore forests, but this task remains challenging due to the inaccessibility of these ecosystems. Compared to human intervention, aerial robots can access tree canopies, but their limited flight time and noise continue to stall widespread application. To address this challenge, we present a perching mechanism which allows small drones to rest on overhanging branches and extend their mission while remaining silent. We developed an origami spine with two folding flaps containing a layer of high-friction material. When the spine engages with a branch, the flaps open and conform to irregular branch surfaces generating sufficient friction to support the weight of a drone. With HEDGEHOG, a drone integrating multiple spines on a protective cage, we demonstrated its application in a controlled indoor as well as in a forest environment. We modelled the perching strategy and measured the effects of materials and geometric parameters on the drone's perching performance. By leveraging interactions with nature, our drone can perch on tree branches with diameters up to 86 mm and inclined up to +-15 and potentially remain in the canopy for extended periods of time to acquire data or monitor returning wildlife.

Forest canopies are the biggest habitat for terrestrial life, yet our understanding of environmental processes and biodiversity inside the canopy continues to be limited due to labour and resource intensive data collection. Existing aerial and climbing robots also struggle to access these complex environments, while animals easily navigate them using multiple means of locomotion. Following this insight we present a robot with multimodal mobility obtained by combining aerial and tethered locomotion. After the robot is deployed at the top of the tree, it can descend with the tether and maneuver around leaves and branches with its thrusters. The tether increases robustness and safety and allows for resting as well as emergency retrieval of the system. The aerial locomotion grants the system the ability to move in a conical 3D space constrained by the tether. We modelled the static system and validated the impact of design parameters on it. A simple control architecture for teleoperation is discussed and its performance is analyzed. The proposed multimodal mobility is demonstrated in preliminary outdoor tests, which show how our robot can move within the canopy while continuously monitoring the environment.