Docking Systems for Drone and UAVs - Detailed Analysis

Landing pads for drones that are integrated into buildings to improve drone delivery efficiency and security. The landing pads have features like scanners, cameras, compartments, and rotating mechanisms to optimize drone delivery and reduce conflicts. They can also have environmental sensors, climate control, and sorting mechanisms to adapt to the delivered parcels. The pads can communicate with drones and other pads to coordinate deliveries and capacity. The goal is to minimize drone collisions, reduce parcel conflicts, shorten delivery times, and improve drone energy efficiency.

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A storage device for unmanned aerial vehicles (UAVs) that enables autonomous takeoff and landing without human intervention. The storage device has a magnet or magnetic body on the upper surface to attract the UAV's own magnets when it lands. This allows the UAV to automatically dock and secure itself to the storage device. Similarly, the UAV can detach and fly away autonomously. This eliminates the need for hand releases or human intervention when the UAV is operating underground or indoors where human access is limited.

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Enabling unmanned aerial vehicles (UAVs) to perform remote takeoff and landing without using the UAV itself as an intermediary. The method involves having multiple ground stations (nests) connected to the terminal. When a UAV needs to take off from one nest and land at another, the terminal sends the UAV's route to the first nest. The nest forwards the route to the UAV. The terminal monitors the UAV's distance to the second nest. If it gets close, the terminal sends the second nest to prepare for landing. The UAV then lands at the second nest instead of returning to the terminal. This allows efficient UAV transportation between nests using the ground stations.

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Elevated unmanned aerial vehicle (UAV) stations for efficient delivery of products using drones. The stations are located above buildings like warehouses, stores, or communities to enable takeoff and landing of drones without requiring a large ground facility. The stations have platforms raised above pedestrian and vehicular traffic levels, allowing close proximity to existing infrastructure. Payloads are conveyed vertically between internal buildings and the elevated UAV station using systems like elevators or cranes. The elevated station assembles, loads, launches, and recovers drones for delivery. This enables streamlined on-demand drone delivery from co-located buildings without needing separate UAV facilities.

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This research investigates the autonomous aerial docking of multirotor UAVs in an outdoor environment. Initially, a novel mechanism utilizing NbFeB magnets is proposed for Multirotor UAV, allowing misalignment errors up to 5 cm. Subsequently, relative position estimation between UAV and obtained by using onboard visual Real-Time-kinematics (RTK) sensing. Eventually, cascade PID-based controller developed ensure precise alignment. Experiment results demonstrate that quadrotor platform can successfully dock with via method.

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This article introduced new way to help avoid of drone crashing into each others. The suggested system facilitates communication between drones, enabling them exchange their current location and planned flight path. By working together, drones can anticipate potential collisions. technique utilizes the principle "repulsion forces," autonomously alter trajectories in response nearby obstacles, such as other drones. collision avoidance behavior adapts dynamically distance vehicles, guaranteeing both safety coordination. Created with simplicity computational efficiency mind, is well-suited for lightweight, cost-effective To assess performance, two simulations were carried out: one groups nine approaching other, another 25 executing formation changes. findings revealed that was able prevent collisions, maintain appropriate spacing adjust different environmental conditions. approach improves swarm coordination shows practical applications like managing air traffic cities, delivering packages autonomously, responding emergencies, monitoring defense operations. Future research plans invo... Read More

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Unmanned aerial vehicles (UAVs) are a fast and effective platform that can be used for item delivery. However, the use of conventional multirotor structure often require payload to manually loaded unloaded, increasing turnaround times reducing efficiency such systems. While adding gripper enable grasping releasing payload, typical solution attaching grippers in an underslung manner below UAV leads undesirable flight dynamics when is carried. In this paper, we aim unify goal delivery with direct capabilities, improving load-carrying UAVs while enabling loading unloading without human presence or external receiving stations. To do so, propose design optimizes transportation by hollowing out center bay. This positioning prevents large changes mass moment inertia between unloaded states, hence control authority vehicle. Combined soft enveloping grasper, proposed successfully demonstrated full mission profile approach, capture, grasp, carry, release. addition, object from as well controlled perching were also performed same demonstrating its multifunctionality. The configuration work prov... Read More

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Automated docking of unmanned aerial vehicles (UAVs) through a novel base station design that enables precise landing and charging operations without human intervention. The base station features a retractable landing surface that can be automatically transitioned between positions, with a unique fiducial marking system that enables precise targeting of the landing surface. The system uses computer vision to detect the fiducial and determine the landing position, then controls the propulsion system to guide the UAV to the designated landing surface. The base station also incorporates advanced charging and cleaning capabilities, including automated charging and cleaning systems.

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Automated docking of unmanned aerial vehicles (UAVs) through a novel docking platform that enables precise landing on a surface without human intervention. The platform comprises a landing surface with a fiducial marker and a docking mechanism that positions the UAV on the surface. The fiducial is detected using onboard sensors, and the UAV's flight trajectory is controlled based on the fiducial's position. The platform automatically transitions between docking positions, with features like retractable arms and charging capabilities. This eliminates the need for manual landing procedures, enabling continuous autonomous operations.

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A mobile device for dispatching and receiving drones that has a landing platform with features to efficiently load and unload drones. The landing platform has parallel drone conveyor belts spaced apart so a drone can be on both simultaneously. Above the belts are sliding bars that can move toward each other to displace the drone. This allows the drone to be moved into positions for transfer to a storage level or loading cargo onto a hoist. The belts and bars coordinated motion moves the drone into the appropriate position for the next step.

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Base station for unmanned aerial vehicles (UAVs) that provides automated servicing, storage, charging, and accommodation for UAVs. The station has features like: 1. Integrated temperature control system with a thermoelectric cooling/heating module to regulate the UAV's power source temperature. 2. Enclosure with a sliding cradle that retracts into the station when not in use. This allows UAVs to dock, charge, and store inside the station to protect them. 3. Base station door that opens and closes to let UAVs enter and exit. 4. Folding propeller mechanism that folds UAV propellers during docking to prevent collision with the station. 5. Visualization system with illumination and imaging to aid docking and precipitation detection. 6. Enclosure with heating elements, fiducials, and actuated door

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Purpose of research. Evaluation the effectiveness UAV automatic landing system on a mobile platform using an infrared beacon based criteria for accuracy and maneuver success at various altitudes. Methods. Modeling process movement complex object (UAV) in Gazebo environment ROS ecosystem. The positioning is mathematical model consisting four pairs emitters. algorithm includes adaptive PID controllers X Y coordinates logo polynomial controller to ensure descent along Z axis. Results. was tested 50 times from heights 5 m, 10 m 15 m. At height time 9.04 seconds (0.504 sec deviation), error 0.18 (0.035 rate 100 %. increased 19.17 (1.78 0.19 (0.036 remained 40.45 (5.502 0.21 (0.046 data distribution became wider, outliers appeared, decreased 92 %, which due signal losses, their attenuation need correct trajectory. Increasing testing impractical decrease probability successful landing. Conclusion. study showed that works effectively UAVs altitudes up providing necessary stability accuracy. above problems arise with loss signals, errors, require improvements reliability

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Electrical communication and charging system for unmanned aerial vehicles (UAVs) that allows efficient charging and communication between UAVs and their landing platforms. The system uses magnetic attraction between conductive pins on the UAV and contact surfaces on the landing platform. This provides a reliable and repeatable electrical connection for charging the UAV battery and communicating with the UAV controller. The magnets assist in alignment and retention of the pins on the contacts. The system allows the UAV to automatically dock and charge without manual intervention.

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A fixed positioning and charging system for vehicle-mounted drones on commercial vehicles that allows autonomous drones to land, dock, charge and store on moving vehicles. The system consists of a drone, a docking station with a charging platform, and a storage compartment. The drone has a laser radar and camera for scene recognition. The docking station has a sliding cross-member, belt drive, and positioning laser. The drone identifies objects, lands on the platform, slides into position, and charges wirelessly. The dock folds for storage when not in use. The system enables autonomous drones to assist vehicles in complex driving scenarios by landing, docking, charging, and storing on moving vehicles.

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An automatic patrol drone system for power transmission lines that enables autonomous inspection and charging of drones without human intervention. The system uses drones equipped with 5G connectivity, image recognition, electric field monitoring, and obstacle avoidance, along with power towers outfitted with 5G base stations, energy storage, and wireless charging. The drones use tower-provided 5G coordinates to autonomously navigate and inspect lines. When low on battery, they locate the nearest tower for wireless charging. This allows sustained autonomous patrols without manual piloting or carrying heavy batteries.

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Aerial charging drone group and charging method that enables fast charging of two drones mid-air. The charging group has two drones, one with a retractable charging plug and the other with a retractable socket. The drone with the socket detects low battery and requests a nearby drone with the plug to fly over. The socket drone guides the plug drone to align the charging holes. The plug drone descends and the socket drone moves up to meet. The charging plug extends and connects. The drones then dock for charging. The drone bodies are transparent for visual alignment. Mechanisms move the charging components.

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System to provide power and data communications to drones on overhead power lines using the existing infrastructure. Drones can dock and charge on specialized stations attached to power lines. The stations collect power from the lines, guide drones for accurate landing, and provide data services. They can also communicate with drones wirelessly. The stations process drone data and relay it back. This allows drones to fly long distances without batteries and access remote areas.

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Automatic drone loading/unloading system for vehicles using geofencing to enable autonomous docking and undocking of drones. The system involves a geofencing unit at the vehicle docking station and a geofencing unit on the drone. The station unit sets a geofence around the docking area with parameters like location, vehicle height, and drone hover altitude. The drone unit receives this geofence info and the docking station communicates with the drone to perform autonomous takeoff/landing inside the geofenced area. This allows the drone to dock and undock without manual intervention.

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A docking system for vertical take-off and landing drones that allows stable take-off and landing without requiring a separate latching or alignment device. The system uses a landing portion on the drone with a horned or pyramidal shape that aligns with and mounts onto a docking portion with a matching shape. The horned/pyramidal landing portion interlocks with the docking portion to securely hold the drone in place during take-off and landing.

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Charging, storing, programming and launching multiple unmanned aerial vehicles (UAVs) in an efficient and automated way. It involves using specialized charging containers that mechanically hold and electrically connect the UAVs for simultaneous charging. The containers also identify the stored UAVs and communicate their identities to a central control system. The central system can then transmit role instructions to the containers, which distribute them to the UAVs. Countdown timers initiate automated takeoffs to perform their assigned roles. The storage containers provide a secure and organized system for managing large numbers of UAVs.

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