Our innovative study, ALBERO, introduces a groundbreaking framework aimed at enhancing quadrotor perching capabilities on natural, inclined tree branches. This advancement addresses the challenge of finding suitable horizontal perches, which often leads to increased search times and depleted drone endurance.
Key Features and Methodology
Central to ALBERO is its active gripper design, which stands out for its ultra-fast grasping speed – 67 milliseconds for the larger gripper and an impressive 42 milliseconds for the smaller version. This rapid action is critical for effective perching on steeply inclined branches found in natural settings. Additionally, the design boasts a high power-to-weight ratio, scalability, and exceptional energy efficiency. Its scalability is a significant feature, allowing easy adaptation to different drone sizes, enhancing the system’s versatility across various drone models.
Alongside this mechanical innovation, we have developed a specialized motion planner tailored for the dynamic challenges of agile perching maneuvers. This planner has been validated through extensive real-world flight experiments, demonstrating its effectiveness in dynamically perching on inclined branches.
Achievements in XPRIZE Rainforest Competition
Our research’s practical and innovative nature was recognized at the XPRIZE Rainforest competition held in Singapore in June 2023. Competing as a semifinalist, our team showcased the ALBERO system’s capabilities, earning us a place in the final list of this esteemed competition. This recognition highlights the potential impact of our work in drone technology and environmental applications.
Results
Our system’s efficacy was proven through rigorous indoor and outdoor testing. Outdoor experiments, particularly, demonstrated the system’s real-world applicability, with successful perching on naturally inclined tree branches, guided by visual feedback from a First Person View (FPV) camera.
Conclusion and Future Directions
ALBERO marks a significant leap in drone interaction with natural environments. The combination of our rapid-action, scalable gripper design and advanced motion planning algorithm paves the way for more efficient and versatile drone operations outdoors. Future efforts will focus on integrating computer vision for accurate outdoor pose estimation, further enhancing the reliability and range of perching maneuvers in diverse environments.
@article{zheng_24,
title = {ALBERO: Agile Landing on Branches for Environmental Robotics Operations},
author = {Liming Zheng and Salua Hamaza},
doi = {10.1109/LRA.2024.3349914},
issn = {2377-3766},
year = {2024},
date = {2024-01-04},
urldate = {2024-01-04},
journal = {IEEE Robotics and Automation Letters},
volume = {9},
issue = {3},
pages = {2845-2852},
abstract = {Drones have been increasingly used in various domains, including ecological monitoring in forests. However, the endurance and noise of drones have limited their deployment to short flight missions above canopies. To address these limitations, we introduce ALBERO: a framework comprising a mechanical solution and an optimal planner to realise agile quadrotor perching on tree branches of steep incline. The gripper features an ultra-fast active mechanism inspired by birds' claws that enables quadrotors to perch swiftly on randomly-oriented tree branches. By perching, the drone can preserve energy for extended periods of time, while silently gathering forest data in the canopy. The intrinsic properties of the gripper allow for extra flexibility in size, surface roughness and shape imperfections of natural perches, such as those found in the wild. The gripper also has good scalability properties and can be easily matched to different drones' sizes. The biggest advantage of this novel design lays in its ability to close reactively and ultra-fast (67ms on the large gripper, 42 ms on the small gripper), enabling the quadrotor to perform agile perching manoeuvres from different angles and at different approach speeds. ALBERO's software module comprises of a trajectory planning algorithm adapted for branch perching, ensuring that the drone can perch on inclined cylindrical targets from any starting location in the proximity of the branch. These requirements translate in stringent positioning and orientation accuracy, but they enable the drone to land dynamically from a variety of positions within the forest.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Drones have been increasingly used in various domains, including ecological monitoring in forests. However, the endurance and noise of drones have limited their deployment to short flight missions above canopies. To address these limitations, we introduce ALBERO: a framework comprising a mechanical solution and an optimal planner to realise agile quadrotor perching on tree branches of steep incline. The gripper features an ultra-fast active mechanism inspired by birds' claws that enables quadrotors to perch swiftly on randomly-oriented tree branches. By perching, the drone can preserve energy for extended periods of time, while silently gathering forest data in the canopy. The intrinsic properties of the gripper allow for extra flexibility in size, surface roughness and shape imperfections of natural perches, such as those found in the wild. The gripper also has good scalability properties and can be easily matched to different drones' sizes. The biggest advantage of this novel design lays in its ability to close reactively and ultra-fast (67ms on the large gripper, 42 ms on the small gripper), enabling the quadrotor to perform agile perching manoeuvres from different angles and at different approach speeds. ALBERO's software module comprises of a trajectory planning algorithm adapted for branch perching, ensuring that the drone can perch on inclined cylindrical targets from any starting location in the proximity of the branch. These requirements translate in stringent positioning and orientation accuracy, but they enable the drone to land dynamically from a variety of positions within the forest.
