Crash Landing onto "you": Untethered Soft Aerial Robots for Safe Environmental Interaction, Sensing, and Perching
Pham Huy Nguyen
TL;DR
The paper addresses safe environmental interaction by enabling untethered soft aerial robots to perch across forest canopies for extended data collection. It argues for metamorphic, soft-bodied designs that couple flight and perching without bulky perching modules that degrade endurance. The authors synthesize past work on inflatable soft bodies, soft grippers, and metamorphic arms, showing robustness to impacts and dynamic engagement with branches. They outline future directions—high-speed dynamic perching, vision-based branch detection with synthetic data, and onboard environmental sensing networks (acoustic, eDNA, and gas sensors)—to realize scalable, field-deployable forest monitoring.
Abstract
There are various desired capabilities to create aerial forest-traversing robots capable of monitoring both biological and abiotic data. The features range from multi-functionality, robustness, and adaptability. These robots have to weather turbulent winds and various obstacles such as forest flora and wildlife thus amplifying the complexity of operating in such uncertain environments. The key for successful data collection is the flexibility to intermittently move from tree-to-tree, in order to perch at vantage locations for elongated time. This effort to perch not only reduces the disturbance caused by multi-rotor systems during data collection, but also allows the system to rest and recharge for longer outdoor missions. Current systems feature the addition of perching modules that increase the aerial robots' weight and reduce the drone's overall endurance. Thus in our work, the key questions currently studied are: "How do we develop a single robot capable of metamorphosing its body for multi-modal flight and dynamic perching?", "How do we detect and land on perchable objects robustly and dynamically?", and "What important spatial-temporal data is important for us to collect?"