Swarm of micro flying robots in the wild

Science Robotics, Год журнала: 2022, Номер 7(66)

Опубликована: Май 4, 2022

Aerial robots are widely deployed, but highly cluttered environments such as dense forests remain inaccessible to drones and even more so swarms of drones. In these scenarios, previously unknown surroundings narrow corridors combined with requirements swarm coordination can create challenges. To enable navigation in the wild, we develop miniature fully autonomous a trajectory planner that function timely accurate manner based on limited information from onboard sensors. The planning problem satisfies various task including flight efficiency, obstacle avoidance, inter-robot collision dynamical feasibility, coordination, on, thus realizing an extensible planner. Furthermore, proposed deforms shapes adjusts time allocation synchronously spatial-temporal joint optimization. A high-quality be obtained after exhaustively exploiting solution space within only few milliseconds, most constrained environment. is finally integrated into developed palm-sized platform perception, localization, control. Benchmark comparisons validate superior performance quality computing time. Various real-world field experiments demonstrate extensibility our system. Our approach evolves aerial robotics three aspects: capability environment navigation, diverse requirements, without external facilities.

Язык: Английский

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Quantifying the movement, behaviour and environmental context of group‐living animals using drones and computer vision

Journal of Animal Ecology, Год журнала: 2023, Номер 92(7), С. 1357 - 1371

Опубликована: Март 21, 2023

Abstract Methods for collecting animal behaviour data in natural environments, such as direct observation and biologging, are typically limited spatiotemporal resolution, the number of animals that can be observed information about animals' social physical environments. Video imagery capture rich their but image‐based approaches often impractical due to challenges processing large complex multi‐image datasets transforming resulting data, locations, into geographical coordinates. We demonstrate a new system studying wild uses drone‐recorded videos computer vision automatically track location body posture free‐roaming georeferenced coordinates with high resolution embedded contemporaneous 3D landscape models surrounding area. provide two worked examples which we apply this approach gelada monkeys multiple species group‐living African ungulates. how simultaneously, classify individuals by age–sex class, estimate individuals' postures (poses) extract environmental features, including topography trails. By quantifying movement while reconstructing detailed model landscape, our opens door sensory ecology decision‐making within

Язык: Английский

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From animal collective behaviors to swarm robotic cooperation

National Science Review, Год журнала: 2023, Номер 10(5)

Опубликована: Фев. 16, 2023

The collective behaviors of animals, from schooling fish to packing wolves and flocking birds, display plenty fascinating phenomena that result simple interaction rules among individuals. emergent intelligent properties the animal behaviors, such as self-organization, robustness, adaptability expansibility, have inspired design autonomous unmanned swarm systems. This article reviews several typical natural introduces origin connotation intelligence, gives application case behaviors. On this basis, focuses on forefront progress bionic achievements aerial, ground marine robotics swarms, illustrating mapping relationship biological cooperative mechanisms cluster Finally, considering significance coexisting-cooperative-cognitive human-machine system, key technologies be solved are given reference directions for subsequent exploration.

Язык: Английский

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Drone-assisted collection of environmental DNA from tree branches for biodiversity monitoring

Science Robotics, Год журнала: 2023, Номер 8(74)

Опубликована: Янв. 18, 2023

The protection and restoration of the biosphere is crucial for human resilience well-being, but scarcity data on status distribution biodiversity puts these efforts at risk. DNA released into environment by organisms, i.e., environmental (eDNA), can be used to monitor in a scalable manner if equipped with appropriate tool. However, collection eDNA terrestrial environments remains challenge because many potential surfaces sources that need surveyed their limited accessibility. Here, we propose survey sampling outer branches tree canopies an aerial robot. drone combines force-sensing cage haptic-based control strategy establish maintain contact upper surface branches. Surface then collected using adhesive integrated drone. We show autonomously land variety stiffnesses between 1 103 newton/meter without prior knowledge structural stiffness robustness linear angular misalignments. Validation natural demonstrates our method successful detecting animal species, including arthropods vertebrates. Combining robotics from unreachable aboveground substrates offer solution broad-scale monitoring biodiversity.

Язык: Английский

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Embedded Physical Intelligence in Liquid Crystalline Polymer Actuators and Robots

Advanced Materials, Год журнала: 2024, Номер unknown

Опубликована: Фев. 20, 2024

Abstract Responsive materials possess the inherent capacity to autonomously sense and respond various external stimuli, demonstrating physical intelligence. Among diverse array of responsive materials, liquid crystalline polymers (LCPs) stand out for their remarkable reversible stimuli‐responsive shape‐morphing properties potential creating soft robots. While numerous reviews have extensively detailed progress in developing LCP‐based actuators robots, there exists a need comprehensive summaries that elucidate underlying principles governing actuation how intelligence is embedded within these systems. This review provides overview recent advancements robots endowed with using LCPs. structured around stimulus conditions categorizes studies involving LCPs based on fundamental control stimulation logic approach. Specifically, three main categories are examined: systems changing those operating under constant equip learning capabilities. Furthermore, persisting challenges be addressed outlined discuss future avenues research this dynamic field.

Язык: Английский

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Forest in situ observations through a fully automated under-canopy unmanned aerial vehicle

Geo-spatial Information Science, Год журнала: 2024, Номер 27(4), С. 983 - 999

Опубликована: Март 21, 2024

Close-range sensing has yet to attain the status of being a dependable source for in situ forest information as conventional field inventory. Each solution its advantages and disadvantages terms accuracy, completeness, efficiency. For area, Terrestrial Laser Scanning (TLS) highest data quality, but is limited static perspectives lack Mobile Mapping Systems (MMS) systems gain on efficiency compromise quality. More recently, under-canopy UAV caught attentions potential leverage both TLS MMS systems. This study demonstrates feasibility autonomous investigation using an (ULS) system, evaluates performance such system deriving key tree attributes through comparison with other close-range Personal (PLS). The ULS uses onboard LiDAR sensor aid self-traverse unknown environment collect point cloud during movement inside forest. Key factors influencing systems' overall were investigated via various experiments. collected by under canopy deliver similar stem capturing capacity single layer stands less undergrowth. RMSEs DBH estimates 0.81 cm (3.80%), 4.12cm (19.92%), 5.13cm (22.01%), respectively. curve 1.27 (5.48%), 3.97 (17.63%), 5.18 (22.49%), geometric accuracy completeness significantly improved when trajectory was densified. studies route planning complex required improve mobility, applicability future practical observations.

Язык: Английский

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Advanced materials for micro/nanorobotics

Chemical Society Reviews, Год журнала: 2024, Номер 53(18), С. 9190 - 9253

Опубликована: Янв. 1, 2024

Autonomous micro/nanorobots capable of performing programmed missions are at the forefront next-generation micromachinery. These small robotic systems predominantly constructed using functional components sourced from micro- and nanoscale materials; therefore, combining them with various advanced materials represents a pivotal direction toward achieving higher level intelligence multifunctionality. This review provides comprehensive overview for innovative micro/nanorobotics, focusing on five families that have witnessed most rapid advancements over last decade: two-dimensional materials, metal-organic frameworks, semiconductors, polymers, biological cells. Their unique physicochemical, mechanical, optical, properties been integrated into to achieve greater maneuverability, programmability, intelligence, multifunctionality in collective behaviors. The design fabrication methods hybrid discussed based material categories. In addition, their promising potential powering motion and/or (multi-)functionality is described fundamental principles underlying explained. Finally, extensive use variety applications, including environmental remediation, (bio)sensing, therapeutics,

Язык: Английский

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A guidance to intelligent metamaterials and metamaterials intelligence

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Янв. 29, 2025

Язык: Английский

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Micro/Nanorobotic Swarms: From Fundamentals to Functionalities

ACS Nano, Год журнала: 2023, Номер 17(14), С. 12971 - 12999

Опубликована: Июль 11, 2023

Swarms, which stem from collective behaviors among individual elements, are commonly seen in nature. Since two decades ago, scientists have been attempting to understand the principles of natural swarms and leverage them for creating artificial swarms. To date, underlying physics; techniques actuation, navigation, control; field-generation systems; a research community now place. This Review reviews fundamental applications micro/nanorobotic The generation mechanisms emergent micro/nanoagents identified over past elucidated. advantages drawbacks different techniques, existing control systems, major challenges, potential prospects discussed.

Язык: Английский

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Visual SLAM Integration With Semantic Segmentation and Deep Learning: A Review

IEEE Sensors Journal, Год журнала: 2023, Номер 23(19), С. 22119 - 22138

Опубликована: Авг. 23, 2023

Simultaneous localization and mapping (SLAM) technology is essential for robots to navigate unfamiliar environments. It utilizes the sensors robot carries answer question “Where am I?” Of available sensors, cameras are commonly used. Compared other like light detection ranging (LiDARs), method based on cameras, known as visual SLAM, has been extensively explored by researchers due affordability rich image data provide. Although conventional SLAM algorithms have able accurately build a map in static environments, dynamic environments present significant challenge practical robotics scenarios. While efforts made address this issue, such adding semantic segmentation algorithms, comprehensive literature review still lacking. This article discusses challenges approaches of with focus objects their impact feature extraction accuracy. First, two classical reviewed; then, explores application deep learning front-end back-end SLAM. Next, analyzed summarized, insights into future developments elaborated upon. provides effective inspiration how combine promote its development.

Язык: Английский

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