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[Drone Drilling and Balloon Zapping Challenge] Q300, a full open-source drone platform, accurately visually recognizes circles and balloons, easily traverses circles, and accurately zaps balloons!
#artificial intelligence (ai)#science and technology#higher education#ros#robot#robotics#innovation#agv#autonomous robot#intelligent#uav#drone#opensource
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Robotic arm to pick up eggs
#artificial intelligence (ai)#science and technology#higher education#ros#robot#innovation#robotics#agv#autonomous robot#intelligent
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MINI Arm is an open-source six-axis desktop-level robotic arm based on the ROS system, that supports RVIZ and Gazebo simulation, support for Moveit trajectory planning development, and repeat positioning accuracy of up to 0.2mm, especially suitable for robotic arm movement and trajectory planning teaching. At the same time, the end of the configuration of the vision unit can be combined with the vision of the AI with the relevant service, Intelligent grasping, regional handling, and other scenes of teaching and research development.
#artificial intelligence (ai)#science and technology#higher education#ros#robot#innovation#robotics#agv#autonomous robot#intelligent#robot arm#gazebo
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QR Code Recognition Tracking, a variety of QR Code Recognition packages are available in ROS, which allows the robot to follow forward and backward, left and right by moving the QR Code.
#artificial intelligence (ai)#science and technology#higher education#ros#innovation#robot#agv#robotics#autonomous robot#intelligent#qr
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KCF is a discriminative tracking method, which generally trains a target detector during the tracking process, uses the target detector to detect whether the predicted position of the next frame is the target, and then uses the new detection results to update the training set and then update the target detector. When training the target detector, the target region is generally selected as positive samples, and the surrounding region of the target is negative samples, of course, the closer the region of the target is the greater the likelihood of positive samples.
#kcf#artificial intelligence (ai)#science and technology#higher education#robot#ros#innovation#agv#robotics#autonomous robot#intelligent
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The 5G security inspection robot system RS-INS adopts a multi-device coupling system, starting from mechanism design and optimization, motion planning and control, state estimation and environment sensing, etc. It realizes 4K HD backhaul, remote real-time control, multi-line patrol, target tracking and localization, daytime + nighttime dual-lighting shooting, etc. through a 5G network. It supports multi-channel video-on-demand and video playback. It supports multi-video on-demand and video playback and can realize routine inspection in complex terrain, remote cloud operation, automatic archiving and analysis in the background, etc. It solves the problems of high intensity of manual inspection, uneven quality, and inability to adapt to the complex terrain of the substation, and explores intelligent security and inspection.
#artificial intelligence (ai)#science and technology#5g#higher education#ros#robot#innovation#intelligent#autonomous robot#agv#robotics
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ORB-SLAM2 is a complete simultaneous localization and mapping (SLAM) system for monocular, stereo, and RGB-D cameras, including map reuse, loop closure, and repositioning capabilities.
#ORB#artificial intelligence (ai)#science and technology#higher education#ros#robot#innovation#robotics#agv#autonomous robot#intelligent
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The air-ground cooperative formation system (RS-MUL), mainly consists of intelligent UAVs, intelligent unmanned vehicles, a positioning system, a networking communication system, and five parts of the multi-intelligence body cooperative control system. The positioning system acquires the real-time position of UAV and unmanned The positioning system acquires the real-time position of the UAV and unmanned vehicle and sends it to each unmanned vehicle using the network communication module. The unmanned vehicle obtains the information of the body and the position information of the neighboring aircraft through the communication system, and completes the cooperative control of the unmanned vehicle through the set control algorithm, Through the set control algorithm, the cooperative control of the unmanned vehicle and unmanned aircraft is accomplished. The system can realize different behaviors in different scenarios, including real-time tracking, formation, and convoying of UAVs and unmanned vehicles. The system can realize different behaviors in different scenarios, including UAV and UAV real-time tracking, formation, and formation change; single-vehicle and single-machine coordination; multi-vehicle and multi-machine coordination; ground station control of the single vehicle; vehicle group network expansion; ground station cluster formation simulation
#uav#military#ros#robot#innovation#robotics#agv#autonomous robot#higher education#intelligent#science and technology#artificial intelligence (ai)#execution#soldiers#navy#us military#us marines
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Cargo handling has always been a time-consuming and unavoidable work, the emergence of AGV unmanned trucks, instead of people to complete the different states of the handling operation, greatly reduced people's labor intensity and improved the efficiency of the factory. The factory transportation robot system is based on a HandsFree robot and open source system, realizing the robot from map building, navigation, and motion control; it can autonomously and accurately complete the delivery of production materials under the operation scenario of human-machine mixing and provide the flexible flow of materials between production lines.
#innovation#mobile robot#agv#ultrasound#navigation#positioning#machine dreams#logistics#intelligent#warehousing#robotics#ugv#autonomous robot#higher education#market research#artificial intelligence (ai)#science and technology
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Cutebot takes a mobile cart + robotic arm as the carrier, based on a four-wheel differential motion mechanism, integrating embedded technology, intelligent perception technology, robotics technology, robotic arm technology, SLAM technology, artificial intelligence technology, and machine vision technology, which can cultivate composite talents from the whole process of "structural cognition - electronic control design - programming control - application development".
#innovation#mobile robot#agv#ultrasound#navigation#positioning#machine dreams#logistics#intelligent#warehousing#robotics#ugv#autonomous robot#higher education#market research#artificial intelligence (ai)#science and technology
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Smart agricultural harvesting robots achieve real-time image capture through cameras in agricultural production, and with the support of deep learning technology, accurately identify and harvest.
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Cargo handling has always been a time-consuming and unavoidable work, the emergence of AGV unmanned trucks, instead of people to complete the different states of the handling operation, greatly reduced people's labor intensity and improved the efficiency of the factory. The factory transportation robot system is based on a HandsFree robot and open source system, realizing the robot from map building, navigation, and motion control; it can autonomously and accurately complete the delivery of production materials under the operation scenario of human-machine mixing and provide the flexible flow of materials between production lines.#robot #agv #amr #nvdia #ros #radar #depthcamera #ultrasound #navigation #positioning #machine #learning #logistics #intelligent #warehousing #robotics #ugv #autonomous #edu #research #mobilerobot #innovation
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Gemini is an open-source robotics platform for R&D, education, and personal development, with a smart design and a high price-performance ratio. Gemini combines the concepts of AGV and AMR robotics, based on a two-wheeled Differential Velocity Mechanism, and integrates more than 10 sensors such as laser radar, depth camera, ultrasonic array, microphone array, monocular array, etc., as well as rich computing power from the NVIDIA. The rich ROS/ROS2 software packages and simulation environment for beginner developers allow users to easily develop robot systems, positional guidance systems, and other systems. Users can easily develop robotic systems, positioning and navigation, audio-visual, machine learning, storage, and logistics functions.
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The Intelligent Agricultural Harvesting Robotic System is based on HandsFree Robotics and an open-source system that enables the robots to capture images in real-time through cameras during agricultural production. Supported by deep learning technology, they can accurately recognize and harvest, constantly updating their data, accumulating learning, and becoming "smarter". The intelligent agricultural harvesting robotic system uses LiDAR on a mobile chassis to acquire object position information in an unstructured environment and uses SLAM algorithms to convert the position information into a navigation map of the unstructured environment. Subsequently, the robotic system acquires image data via a camera, processes the image data containing the fruit via a deep learning algorithm, and calculates the approximate location of the fruit. Subsequently, the robot compares the current position with the position of the fruit and sends motion commands to the mobile chassis to move the robot toward the vicinity of the fruit. Next, the position judgment ability of the depth camera is utilized, combined with the visual recognition algorithm, and real-time error correction is achieved through the visual servo algorithm to control the robotic arm to grasp the fruit.
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Remote driving has a wide range of application scenarios in the future. The remote security inspection robot system is based on a HandsFree robot and open source system, based on a mobile platform, HD camera, vision system, and control system, it can accomplish autonomous navigation, intelligent obstacle avoidance, path planning, fixed-point patrol, voice announcement, and other functions. It supports remote manual control. The robot camera acquires the image data of the surrounding environment and transmits it to the cloud server through the 4G/5G network, the cockpit acquires the image data from the remote server by pulling the stream and operates the cockpit controller according to the real-time image data, and the local server returns to the remote server after acquiring the controller's commands and sends them to the robot, so that the robot can make corresponding operations in time, and the robot can make corresponding operations according to the emergency situation of the environment. The robot can also make emergency operations according to the unexpected situation in the environment.
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Cluster formation program supports indoor and outdoor multi-machine formation, including mobile platform, positioning system, network communication, control system and unmanned path planning system, supports unmanned vehicle/unmanned aircraft network expansion, can complete the triangle formation, vertical one-word formation, diamond formation, as well as formation change, air-ground collaboration and other functions, and at the same time, it can rely on the self-developed interactive interface, to realize the simultaneous display of multi-machine trajectories and single-machine control and other work. The function can be realized by the self-developed interactive interface.
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The upgraded Gemini with a jacking mechanism makes logistics and warehousing smarter and more convenient.
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