Aerial Tensile Perching and Disentangling Mechanism for Long-Term Environmental Monitoring
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Abstract (arXiv)
Aerial robots show significant potential for forest canopy research and environmental monitoring by providing data collection capabilities at high spatial and temporal resolutions. However, limited flight endurance hinders their application. Inspired by natural perching behaviours, we propose a multi-modal aerial robot system that integrates tensile perching for energy conservation and a suspended actuated pod for data collection. The system consists of a quadrotor drone, a slewing ring mechanism allowing 360deg tether rotation, and a streamlined pod with two ducted propellers connected via a tether. Winding and unwinding the tether allows the pod to move within the canopy, and activating the propellers allows the tether to be wrapped around branches for perching or disentangling. We experimentally determined the minimum counterweights required for stable perching under various conditions. Building on this, we devised and evaluated multiple perching and disentangling strategies. Comparisons of perching and disentangling manoeuvres demonstrate energy savings that could be further maximized with the use of the pod or tether winding. These approaches can reduce energy consumption to only 22% and 1.5%, respectively, compared to a drone disentangling manoeuvre. We also calculated the minimum idle time required by the proposed system after the system perching and motor shut down to save energy on a mission, which is 48.9% of the operating time. Overall, the integrated system expands the operational capabilities and enhances the energy efficiency of aerial robots for long-term monitoring tasks.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Mar 2024.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025ForestVO: Enhancing Visual Odometry in Forest Environments through ForestGluecited by 3
- 2025Maintaining Plasticity in Reinforcement Learning: A Cost-Aware Framework for Aerial Robot Control in Non-stationary Environmentscited by 0
- 2025Learning Agile Tensile Perching for Aerial Robots from Demonstrationscited by 0
- 2026Where to Perch in a Tree: Vision-Guidance for Tree-Grasping Dronescited by 0
- 2026Where to Perch in a Tree: Vision-Guidance for Tree-Grasping Drones14 May 2026
- 2025Learning Agile Tensile Perching for Aerial Robots from Demonstrations8 Jul 2025
- 2025ForestVO: Enhancing Visual Odometry in Forest Environments through ForestGlue2 Apr 2025
- 2025Maintaining Plasticity in Reinforcement Learning: A Cost-Aware Framework for Aerial Robot Control in Non-stationary Environments1 Mar 2025