AGV wants to walk autonomously mainly to solve the three problems of "Where?", "Where are you going?", "How to get?" "Where?" is the question of positioning, "Where to go?" is the problem of path planning, "how to go?" is the problem of navigation. Solving these three problems basically solves the problem of agv free walking. Positioning and navigation are generally complementary. The advantages and disadvantages of traditional positioning and navigation methods (electromagnetic navigation, magnetic strip navigation) are shown in the following chart. The advantages and limitations of these solutions are obvious. The slightly flexible navigation and positioning scheme uses two-dimensional codes, reflectors, etc., and manually presets some features to locate. A typical example is Amazon's Kiva. Amazon's Kiva â– SLAM (synchronous positioning and map construction) algorithm used in AGV trolley At present, the most advanced navigation method used by AGV manufacturers is the positioning and navigation technology of Lidar+SLAM. SLAM means that the mobile robot can position itself according to the sensors it carries and the perception of the surrounding environment during the movement without the information of the surrounding environment, and incrementally construct the surrounding environment map. SLAM can improve the autonomous ability and environment adaptability of mobile robots, and achieve autonomous positioning and navigation in an unknown environment. SLAM is used in the AGV logistics trolley, which can eliminate the need to pre-lay any track, facilitate the upgrading of the factory production line and the change of the navigation route, avoid obstacles in real time, have strong environmental adaptability, and better realize the coordinated control of multiple AGV trolleys. â– The use of laser radar in AGV trolleys The main sensors that can sense environmental information in SLAM are laser radar, camera, and so on. Among them, the method based on laser radar for AGV trolley autonomous positioning and mapping, because of its high measurement accuracy and long detection distance, and is not easily interfered by the external environment, is the most suitable sensor for AGV trolley SLAM positioning and mapping. N301 navigation laser radar Radium God's intelligent laser radar has a long range of detection, up to 200 meters, high measurement accuracy, and can be used for map construction. It is widely used in the autonomous positioning and navigation of AGV cars. WXX0XAGV anti-collision laser radar WXX0X is a series of products for indoor equipment collision avoidance and intelligent area detection. This series of products is very suitable for AGV, RGV, robots, etc. This series of products can select any one of 15 group sets (FieldSet) as the current working area group through 4 switch input signal combinations, adapt to the complex and varied application environment, and also output point cloud data. â– Five functions that can be realized by Radium Laser Lidar+SLAM algorithm <1>SLAM map construction based on lidar-based sensor Lidar can perform 360° 2D or 3D scanning within the detection range to generate data information. SLAM can build a map of the surrounding environment and calculate its location based on the data information provided by the lidar. The advantage of laser radar over other sensors is that it can measure the angle and distance of obstacle points with higher precision, which is convenient for positioning navigation and map construction. <2>Learning path learning based on map and scene application mode The AGV car travels on the established map, remembers while driving, learns new paths, stores the learned paths, and intelligently selects the best path to complete the task in the same scenario. <3> Free route cruise according to the established learning path and working mode command Freely switch the best path based on the work you need to do. <4>Using anti-collision laser radar to realize intelligent multi-level obstacle avoidance protection during exercise During the free route cruise, the lidar continues to scan the surrounding environment. When a dynamic object or an unknown obstacle is found, the local planner determines the motion in the short term based on the local information of the scan. When the obstacle avoidance behavior has a higher priority than the original path, the local planner can obtain the control of the execution system through competition, so that the AGV moves according to the local planning result. After completing the avoidance behavior of the current obstacle, the global planner again obtains control of the execution system, so that the AGV returns to the global planning path and continues to move according to the learned path. The warning zone, the deceleration zone and the stop driving zone can be set as needed to achieve the purpose of intelligent multi-level obstacle avoidance. <5>Standard motion control technology under different shafts of drive wheel and AGV body Since the chassis movement is not synchronized with the AGV body position, it is necessary to add an encoder to the chassis and the body connecting shaft to synchronize the motion adjustment between the two. Shenzhen Linx Technology Co., Ltd. , https://www.linxheadphone.com
