8results about How to "Achieve obstacle avoidance" patented technology

The visual navigation unmanned dining car comprises a dining car body and a visual navigation mechanism, access doors are hinged to the front side and the right side of the dining car body through hinges, and a mounting base is arranged in the middle of the front side of the lower end of the dining car body; the visual navigation mechanism comprises a protective cover, a two-dimensional code scanner, limiting grooves, limiting columns, a scraping strip, a cross scraping strip and a visual navigation assembly, the movable protective cover is arranged at the lower end of the outer surface of the mounting base, the two-dimensional code scanner is slidably connected to the middle of the interior of the mounting base through a fixing frame, and the limiting grooves are formed in the middles of the left side wall and the right side wall of the protective cover correspondingly; according to the unmanned dining car with the visual navigation function, linkage of opening and closing of the protective cover and lifting of the two-dimensional code scanner can be achieved through movement of the protective cover, self-cleaning of the scraping strip and the cross-shaped scraping strip is matched, and precise and reliable operation of the unmanned dining car is achieved in combination with multi-source visual navigation.

The invention relates to the technical field of agricultural intelligent equipment, and discloses an intelligent driving system and method applied to an orchard, and the system comprises a four-wheel independent hub motor drive chassis, a terrain sensing module, a dynamic torque distribution module, a multi-sensor fusion positioning module, a path rapid detection module, a transverse tracking control module, and an emergency obstacle avoidance module. According to the intelligent driving system and method applied to the orchard, a four-wheel independent hub motor driving chassis, a terrain sensing module, a dynamic torque distribution module, a multi-sensor fusion positioning module, a rapid path detection module, a transverse tracking control module and an emergency obstacle avoidance module are fused; all-terrain self-adaptive driving and obstacle avoidance of the unmanned transport vehicle, high-precision and anti-interference positioning in a complex environment and rapid detection and navigation of an inter-ridge road advancing path can be realized, so that mechanical intelligent transportation is realized, the labor intensity can be effectively reduced, and the operation efficiency and safety of an orchard can be improved.

This utility model provides a delivery robot, including a chassis with a front and rear side on both sides along its length, and wheels mounted on opposite sides along its width. The wheels are driven by motors installed inside the chassis, and the motors are configured to drive the wheels on both sides of the chassis to rotate in opposite directions along its width. The chassis contains a driver, a power module, an embedded computing module, and a main control board, which is connected to the driver, the power module, and the embedded computing module. This delivery robot uses a depth camera to sense road conditions ahead, avoiding collisions. The motor-controlled wheel steering enables the depth camera to capture images horizontally. Since the depth camera has a large field of view in the vertical direction, the combination of the depth camera and wheel steering allows for comprehensive, blind-spot-free imaging.

The utility model provides a portable formula can manual regulation's track detection dolly relates to track detection technical field, including connecting rod one, the both ends fixed mounting of connecting rod one has the car body. The utility model discloses a 6x6 capacitor sensor matrix is installed in the car body bottom, can more accurately detect the damage condition of track surface and inside, cooperate the image information that OpenMV camera gathers, control terminal comprehensive analysis, has improved the accuracy of track damage identification greatly, effectively solved the problem of low detection accuracy of existing track detection car, in addition, through adopting hand -operated lifting wheel, the staff can manually adjust the distance between car body and track according to track height, make the dolly can nimblely adapt to the track detection demand of different height, at the same time, the flexible rotation of the OpenMV camera driven by the steering wheel can realize multi -angle detection and obstacle avoidance, greatly enhanced the flexibility of track detection dolly work in different track environment.

This utility model provides a delivery robot. Wheels driven by motors are mounted on opposite sides of the chassis in the width direction. The motors are configured to drive the wheels on both sides of the chassis to rotate in opposite directions. An openable takeout box frame is located at the upper end of the chassis. An inner takeout box frame is located inside the outer frame and extends through the opening. A touch screen is located on the outer side of the movable takeout box. This delivery robot uses a fusion of depth camera and LiDAR to sense the surrounding road conditions. The depth camera, combined with wheel steering, enables omnidirectional shooting. Navigation and positioning are achieved through a BeiDou positioning module for precise location. Users can retrieve their takeout by inputting a pickup code via a voice interaction module and the touch screen, meeting the needs of different users. After receiving the correct pickup code, the inner takeout box frame rises, allowing the user to easily retrieve the takeout.

The application discloses a kind of based on quadruped robot and machine vision's building model reconstruction method and system, based on the quadruped robot of laser scanner, utilize simultaneous localization and map construction technology to generate the global map of the region to be reconstructed.Combining three-dimensional ray tracing and A* path search algorithm determines target scanning point and carries out global path planning.Based on the high-precision sensor of quadruped robot, through adaptive monte carlo positioning and improved dynamic window method algorithm, to realize the accurate positioning and obstacle avoidance of quadruped robot in complex environment.After moving to target scanning point, robot stops and starts laser scanner, carries out high-precision point cloud data acquisition, until completing all sampling.After the preprocessing of the collected point cloud data, through point cloud registration and poisson surface reconstruction technology, generate three-dimensional building model.The application can realize comprehensive, efficient and accurate three-dimensional reconstruction in complex building environment.

The invention discloses an unmanned aerial vehicle for logistics transportation and an unmanned aerial vehicle system, and relates to the technical field of logistics unmanned aerial vehicles, the unmanned aerial vehicle comprises a mounting platform, a limiting ring is mounted at the bottom of the mounting platform, a connecting disc is rotatably connected to the inner wall of the limiting ring, a fixing bracket is mounted at the bottom of the connecting disc, and a placement plate is mounted at the bottom of the fixing bracket; according to the unmanned aerial vehicle for logistics transportation and the unmanned aerial vehicle system, through the arrangement of the mounting platform, the fixed bracket, the placement plate, the positioning plate, the protection frame and the extrusion plate, a cargo bearing platform with a horizontal rotation adjusting function is constructed; on the basis, a self-adaptive cargo clamping system in which a lead screw transmission mechanism and a cross connecting rod clamping mechanism cooperatively work is integrated, and a first driving mechanism drives an extension pipe to stretch out and draw back through a positive and negative rotation lead screw, so that quick positioning of cargoes with different widths is realized; therefore, the problems that in the prior art, the cargo loading direction is fixed, air flow interference is likely to happen in the flight process, and unloading in a narrow space is inconvenient are solved.