53results about How to "Realize autonomous obstacle avoidance" patented technology

The invention relates to a drone cluster self-management system and a control method. The self-management system is connected with a navigation and flight control system of a drone, a task load of thedrone and its own cluster communication link modules through universal interfaces and can be further connected with high-precision navigation, image processing and electrical control units and othermodules based on demands, the drones rely on information interaction for task decision making and coordinated control, and inter-machine coordination functions such as cluster task decomposition, formation flight, target tracking and autonomous obstacle avoidance are realized. Compared with the prior art, the equipped drone can realize cluster flight tasks such as full autonomous formation aggregation and maintenance, regional collaborative search, moving target coordinated tracking, rapid dive approach and the like after simple cluster task binding, and the drone cluster is made to get good robustness, flexibility and scalability.

The invention discloses a mobile robot autonomous navigation system and method. The mobile robot autonomous navigation system comprises an infrared sensor distance measurement unit, an upper computer, a main controller and a motor, and is characterized in that the infrared sensor distance measurement unit is used for measuring the distance between an obstacle in one or more directions and a mobile robot in real time; the upper computer is used for performing path planning on the mobile robot according to the distance between the obstacle and the mobile robot, generating navigation information and sending the navigation information to the main controller; the main controller is used for controlling the motor to operate according to the navigation information sent by the upper computer so as to enable the motor to drive the mobile robot to perform autonomous walking. By using the mobile robot autonomous navigation system and method, requirements for hardware equipment and working environment of the robot are effectively reduced under the condition of ensuring certain navigation accuracy, and the cost-to-performance ratio of products is improved.

The invention relates to a wheel type intelligent autonomous mobile service robot, which is divided into an upper part and a lower part arranged on a chassis. The robot comprises a control system, a movement mechanism, an embedded single board computer, a holder vidicon and sensors, wherein the movement mechanism is controlled by motor drive and (or) a controller; an industrial personal computer (IPC) is connected with the motor drive and (or) the controller by a serial port; the holder vidicon controls the orientation and the angle thereof by the serial port, provides the ambient environmental information of the robot, and connects the collected information with the embedded computer by an image collection card; the sensors are arranged on the upper part and the lower part of the robot, and are connected to the embedded computer after information processing; and the upper part and the lower part of the robot are in folding connection by an upper connecting plate and a lower connecting plate, and a transverse folding shaft and (or) an extraction and insertion part are arranged between the upper connecting plate and the lower connecting plate. The robot can realize autonomous obstacle avoidance according to the ultrasonic sensors, thereby increasing the capabilities of positioning and navigation and map building in none-artificial environments.

The invention provides a robot obstacle avoidance trajectory planning method and system based on deep learning. The robot obstacle avoidance trajectory planning method based on the deep learning comprises the following steps: adding a camera to a simulation environment, taking images from multiple angles and simultaneously inputting the images into a convolutional neural network; obtaining information of a robot arm updated angle according to the input information, and calling a simulation software to update through an interface to obtain a posture; and performing convolutional neural networktraining by means of the deep learning, transferring an obtained characteristic pattern to a one-dimensional vector after convolution operation is performed on the input images, inputting the one-dimensional vector into a subsequent fully connected layer to obtain a q value corresponding to each action, selecting the action with the largest q value and updating the posture, and sending the updatedposture to the simulation environment to obtain a new image input, and executing circularly until the target point is reached. The invention can realize the autonomous obstacle avoidance of an industrial robot and improve the industrial automation production capacity.

The invention discloses a method and device for avoiding obstacles by an unmanned aerial vehicle, equipment and a storage medium. The method comprises the following steps: reconstructing a three-dimensional map based on an acquired image of an obstacle and a monocular Visual SLAM framework to obtain the location of an unmanned aerial vehicle and an axis distance between the unmanned aerial vehicleand the obstacle; according to the flight direction of the unmanned aerial vehicle, projecting the unmanned aerial vehicle; determining whether the projection of the unmanned aerial vehicle in a flight direction is intersected with the plane where the obstacle is located; if so, acquiring an edge point at a shortest distance to the projection center of the unmanned aerial vehicle on the obstacle;forming a preset safety-radius collision circle by using the edge point as the center of the circle; according to the relative positions of the unmanned aerial vehicle and the obstacle as well as thedriving speed of the unmanned aerial vehicle, calculating a deflection angle of the unmanned aerial vehicle; and carrying out route planning based on the collision circle, the deflection angle, the axis distance, and the edge point, enabling the unmanned aerial vehicle to fly around the obstacle via the boundary of the collision circle. Therefore, detection of obstacles and planning of obstacle avoidance paths for unmanned aerial vehicles are realized.

The invention discloses a meteorological popular science robot system with obvious characteristics, which comprises a multifunctional robot carrier and a remote interactive platform, wherein the robot carrier is in an open hardware / software architecture in a modular design mode; wireless remote control and information transmission are supported; the functions of independent movement, barrier avoidance, identification of human faces, human-computer dialogue and the like can be realized; a meteorological sensor of a sensing module can be used for collecting meteorological elements of temperature, humidity, wind directions, wind speed, air pressure, rainfall, radiation degree and the like in real time, processing through a voice module and then broadcasting; simultaneously, the remote interactive platform can exchange with robot carrier information, and also has a repository inquiring function. The whole system allows a robot to move in an indoor or outdoor environment; the system can be widely applied for various popular science exhibits and guest reception; and the system is extended to be combined with meteorological services and can be significantly applied for the fields of meteorological popular science propaganda and exhibition.

The invention belongs to the cognitive nerve technology field and especially relates to a multi-brain area cooperative autonomous decision making method based on multi-modal fusion. Problems that thecost of an existing unmanned aerial vehicle obstacle avoidance technology is high; the technology is not flexible; and an existing reinforcement learning method requires a control object to have a high fault tolerance capability are solved. The multi-brain area cooperative autonomous decision making method based on multi-modal fusion comprises the following steps of acquiring the space position information of an obstacle and inputting into a multi-brain area cooperative reinforcement learning model which is constructed in advance; and according to the reward information fed back by an environment, through dopamine regulation and control and a synaptic plasticity mechanism, updating the multi-brain area cooperative reinforcement learning model, and realizing unmanned aerial vehicle autonomous obstacle avoidance. In the invention, the dangerous degree of the obstacle in a scene can be accurately assessed, a brain autonomous learning process is simulated, the unmanned aerial vehicle can rapidly and accurately learn an obstacle avoidance strategy, autonomous obstacle avoidance is realized and a task is completed.

The invention discloses an intelligent driving vehicle obstacle avoidance system and method. The system comprises a sensing layer, a decision layer and an execution layer, wherein the sensing layer comprises a camera, a laser radar, an ultrasonic sensor, a millimeter wave radar and a GPS device which are mounted on a vehicle body; the decision layer mainly comprises an intelligent driving controller; the execution layer comprises an electronic resistance steering system, an electronically controlled braking system, turn signals and a horn of the vehicle; the input end of the intelligent driving controller is connected to the output ends of the camera, the laser radar, the ultrasonic sensor, the millimeter wave radar and the GPS device of the sensing layer; and the output end of the intelligent driving controller is connected with the controlled ends of the electronic resistance steering system, the electronically controlled braking system, the turn signals and the horn of the executionlayer. The intelligent driving vehicle obstacle avoidance system and method can enable an intelligent vehicle to realize obstacle avoidance, autonomous obstacle avoidance, and even autonomous obstacle avoidance in the whole road section, and improve the driving safety of the intelligent vehicle.

The invention discloses a full-automatic disinfection robot. An upper disinfection assembly ascends and descends in the vertical direction in the working process; a lower disinfection assembly is fixedly mounted above an AGV chassis through bolts; an electrical control assembly used for disinfection control is arranged in the electrical control box, and the electrical control box communicates with an upper dispatching system through a communication module; the upper portion of the AGV chassis is fixedly connected with the electrical control box, and the AGV chassis is driven by the electrical control box to automatically move and conduct obstacle bypassing operation. The full-automatic disinfection robot provided by the invention can provide ultraviolet disinfection, dry fog disinfectant disinfection and air purification functions at the same time; an SLAM navigation technology is adopted, visual and natural navigation obstacle avoidance is fused, the robot can adapt to variable environments, and autonomous obstacle avoidance and autonomous mobile disinfection are achieved; the full-automatic disinfection robot has various light language designs, full-touch screen control, remote control and operation command transmission, has an appointment timing disinfection function, and is complete in function and high in intelligent degree.

The invention provides a local path planning method and device, and the method comprises the steps: obtaining and processing semantic information, and obtaining decision semantic information; acquiring environment sensing information sent by an environment sensing module; obtaining dynamic obstacle prediction information and static obstacle information; acquiring current position information, laneinformation and road information of the vehicle; according to the current position information of the vehicle, the information of the lane where the current position is located, the dynamic obstacleprediction information, the static obstacle information and the decision semantic information, determining the nearest collision obstacle information of the lane where the current position is located,wherein the nearest collision obstacle information comprises position information and speed information of a nearest collision obstacle; taking the position information of the nearest collision obstacle as the center, and taking the transverse safety distance of the vehicle as the translation distance to translate left and right until no collision point exists; carrying out lane changing processing according to the transverse deviation distance and the lane information; and carrying out obstacle avoidance driving according to the maintaining route, the transition route and the extending route.

The invention discloses an ROS-based catering robot and a use method thereof. The ROS-based catering robot comprises a main control robot base, a Kinect vision sensor, a raspberry pi, a bracket, an LCD, a tray and a workstation PC. According to the use method of the ROS-based catering robot, initialization is carried out; a system is started; a workstation controls a robot to walk and establishesan indoor environment map; the established two-dimensional map is loaded in a 3D visualization tool RVIZ; a destination is set in the LCD; and an accessible trajectory is obtained on the basis of global path planning and local path planning, so that a navigation task can be completed. With the use method of the ROS-based catering robot of the invention adopted, the autonomous food delivery of therobot can be realized; a human-machine interaction function can be enhanced; the ability of the robot to cope with emergencies can be improved; and functions such as autonomous navigation and autonomous obstacle avoidance in a navigation process can be realized.

The invention discloses a novel floor mopping robot, which comprises a skeleton, wherein a water tank is arranged in the middle of the skeleton; an upper sealing gland and a lower sealing gland are arranged at the upper part of the water tank; a water pump and a fan are fixed to the skeleton of the floor mopping robot by virtue of bolt groups; a fan connecting piece is arranged on the fan; a filter cup is embedded in the middle of the lower sealing gland; sensor fixing brackets are arranged on the sidewalls of the skeleton; distance measuring sensors are arranged on the sensor fixing brackets; a brush disc driving motor is arranged on each of two sides of the water tank; and brush disc driving motor cover plates are arranged on the tops of the brush disc driving motors. According to the robot disclosed by the invention, since the main body structure of the robot is integrally molded, the sealing performance of the structure is guaranteed and the complexity of processing and assembling is simplified; the robot is small and beautiful in form and flexible to move, and the robot is capable of automatically avoiding obstacles; and in addition, sewage, which is generated in a cleaning process, can be recovered, processed and recycled, so that the robot is quite high in environmental protection value and is suitable for commercial popularization and for development and application.

The invention discloses a robot obstacle avoidance system based on obstacle motion state prediction. The system comprises a mobile robot with bottom layer driving, four ultrasonic sensors, a robot controller and a power supply system, wherein the four ultrasonic sensors are installed around a robot, are connected to the corresponding ports of a robot controller through ports, and are used for acquiring the distance information of an obstacle; the robot controller is used for carrying out fusion analysis and processing on the obstacle distance information acquired by the ultrasonic sensors, andthen making a mobile robot move and avoid the obstacle; and the power supply system is used for supplying power to the mobile robot and the robot controller. The invention also discloses a robot obstacle avoidance method based on obstacle motion state prediction. The system and the method have low cost, good stability, high reliability and good versatility, and can be widely applied to the obstacle avoidance and navigation field of the robot, and the autonomous obstacle avoidance of the mobile robot to a dynamic obstacle can be realized.

The invention relates to a weeding and obstacle-avoiding robot. The weeding and obstacle-avoiding robot comprises a weeding and obstacle-avoiding mechanism, a cutter disc adjusting mechanism and a moving platform, wherein the first end of the cutter disc adjusting mechanism is connected with the weeding and obstacle-avoiding mechanism; the second end of the cutter disc adjusting mechanism is connected with the moving platform; and the cutter disc adjusting mechanism adjusts the height and / or inclination angle of a cutter disc. According to the invention, by adoption of the weeding and obstacle-avoiding mechanism, automatic weeding and effective obstacle avoidance can be simultaneously achieved, and damage to fruit trees is avoided; by adoption of the cutter disc adjusting mechanism, the weeding and obstacle-avoiding robot is applicable to traditional clean tillage and weeding of an orchard, and the hoeing depth and the cutter penetration inclination angle are adjusted; the weeding andobstacle-avoiding robot is applicable to grass-sown orchards, adjusts the height of mowing and meets different weeding requirements; the weeding and obstacle-avoiding robot is applicable to slope weeding, and the inclination angles of the cutter disc and the slope surface are adjusted to the same by utilization of an adjusting structure, so slope weeds can be completely removed; in addition, a large operation space is provided for an operator, and the cutter disc is convenient to be checked and replaced.

The invention discloses a UWB-array-based automatic obstacle avoidance system and method for a drone. The system comprises a collecting unit, a receiving unit, a judging unit, a control unit and an actuator. UWB range sensor arrays assembled in the collecting unit in multiple directions collect the distance data between an obstacle and a drone body, the receiving unit receives the sensing data transmitted by the collecting unit, the judging unit resolves the distance data transmitted by the UWB sensors into distance, the course of the drone is changed into preset course when the distance is smaller than preset distance, and flying height and flying attitude are regulated to avoid the obstacle. The system has the advantages that the problems that the drone cannot avoid the obstacle under a narrow scene and cannot achieve comprehensive obstacle avoidance in the prior art are solved, the system is reliable, real-time, accurate and capable of effectively preventing drone body damage and preventing the drone from destroying other objects during flight, and the like.

The invention relates to a weeding and obstacle avoiding mechanism and a weeding and obstacle avoiding robot. The weeding and obstacle avoiding mechanism comprises a weeding structure and an obstacleavoiding structure, wherein the weeding structure comprises a fixed cutter disc cover and a rotating cutter disc cover; the rotating cutter disc cover is connected with the fixed cutter disc cover through the obstacle avoiding structure; the obstacle avoiding structure comprises a connecting rod and a linear driving part; the first end of the connecting rod is rotatably connected with the fixed cutter disc cover, and the second end of the connecting rod is connected with the rotating cutter disc cover; and the first end of the linear driving part is rotatably connected with the fixed cutter disc cover, and the second end of the linear driving part is rotatably connected with the connecting rod. According to the weeding and obstacle avoiding mechanism and the weeding and obstacle avoiding robot, the obstacle avoiding structure is adopted to drive the rotating cutter disc cover to rotate relative to the fixed cutter disc cover, obstacle avoiding and mowing between plants can be achieved,damage to fruit trees is prevented, and weeds around the fruit trees at different intervals can be removed thoroughly; the weeding width can be changed; and the mowing operation efficiency is improved.

The invention discloses an autonomous obstacle avoidance method for AGV and relates to an AGV. A laser sensor is provided. In combination with a short-term memory method, the obstacle distribution around the AGV is acquired by the laser sensor in real time. According to the acquired obstacle distribution, an obstacle avoidance algorithm is designed and an obstacle avoidance strategy is established, and the AGV is controlled to search out a feasible channel, bypassing the obstacles to reach a target location, thereby achieving autonomous obstacle avoidance. In a complicated environment, the AGVcan automatically avoid obstacles for unobstructed driving, reduces the possibility of accidents, selects the optimal channel, and greatly improves the working efficiency.

The invention relates to a fire hazard rescue robot, which comprises movable vehicle, sensor and protective frame, image sound positioning device, driver, intercom, display and wireless controller. Remote operator can use wireless controller to move vehicle into fire site to find and rescue people; and the positioning device will transmit collected data to the remote controller, to find the people position; remote operator controls the vehicle to approach people; and the people can start the protective frame or drive the vehicle by itself, while the vehicle can be controlled by remote operator.

The invention discloses an outdoor targeting robot. The outdoor targeting robot comprises a chassis; a target body capable of rotating is mounted on the chassis; a skeleton, a base plate, a steering mechanism, a driving mechanism, a controller mounting plate, a wireless communication unit, a controller, a power supply body and an autonomous navigation device are mounted in the chassis; the drivingmechanism, the steering mechanism, the controller and the wireless communication unit are electrically connected with the power supply body; the controller is fixedly mounted on the controller mounting plate; the controller is in control connection with the autonomous navigation device, the steering mechanism and the driving mechanism; and the controller is in communication connection with an upper control center through the wireless communication unit. The outdoor targeting robot adopts an autonomous navigation technology to achieve such functions as path planning and autonomous obstacle avoidance, controls a robot driving mechanism and the steering mechanism to autonomously move from an initial point or a target point to a next target point or terminal according to specific scene conditions, realizes intelligent movement and control, and improves the training personification degree.

The invention belongs to the technical field of robots, and discloses an intelligent distribution robot control system. The intelligent distribution robot control system comprises a camera module, anenvironment monitoring module, a single-chip microcomputer control module, a monitoring identification module, an obstacle avoidance module, a positioning module and a settlement module. Image information of a consumer is collected by the camera module; the temperature, humidity and other information of the environment in the distribution process are monitored by the environment monitoring module;the single-chip microcomputer control module controls the monitoring identification module to conduct an identification operation on a collected image; obstacles in a distribution route are accurately avoided through the obstacle avoidance module; position information of a distribution robot is positioned in real time through the positioning module; settlement confirmation is conducted through the settlement module after an item is received by the consumer. Through the obstacle avoidance module, fuzzy logic processing is used several times, a robot automatically avoids the obstacles more easily and accurately, and the service life of the robot is prolonged; order information of the consumer is obtained according to the face, and the order processing efficiency is greatly improved.

The invention discloses a method and a system for obstacle avoidance of a robot. The method comprises the following steps of according to ultrasonic information and infrared information, obtaining voltage signal data, and drawing a voltage signal curve; according to the voltage signal curve, obtaining a membership function of voltage signals; setting a fuzzy threshold value, and determining a fuzzy set of the voltage signals; according to the fuzzy set of the voltage signals, obtaining a membership function of distances, and further obtaining a fuzzy set of the distances; according to the fuzzy set of the distances, obtaining a fuzzy rule of speeds, so as to enable the robot to avoid obstacles. The method has the advantage that by performing multiple times of fuzzy logic treatment, the autonomous obstacle avoidance of the robot is simply and precisely realized, and the service life of the robot is prolonged.

The invention relates to the technical field of logistics carrying, in particular to an intelligent logistics oriented robot forklift which comprises a forklift body, a lifting module and a control device. The forklift body comprises a forklift head, a supporting assembly, a power driving device and a navigation device; the lifting module comprises a jacking device, a pallet fork assembly and a weighing device; the pallet fork assembly is arranged above the supporting assembly; the jacking device is arranged between the supporting assembly and the pallet fork assembly and used for driving the pallet fork assembly to ascend and descend; and the weighing device is arranged on the pallet fork assembly and used for weighing objects on the pallet fork assembly. According to the robot forklift provided by the invention, the lifting module adopts a geometric center design for lifting and bearing, an eccentric structure does not exist, and stable transportation of the robot forklift can be ensured without arranging a large-size counter weight so as to adapt to logistics transfer in a narrow channel; and the weighing device is arranged at the pallet fork assembly, so that the weight of the inserted and taken objects can be monitored in real time while the objects are inserted and taken, and weight statistics is carried out.

The invention discloses an unmanned aerial vehicle bionic intelligent obstacle-avoiding method based on light streams and belongs to the field of artificial intelligence and computer vision. Obstacle-avoiding flight of an unmanned aerial vehicle is realized through combination of software and hardware. The method comprises the specific steps that an image sequence is captured through a monocular camera carried on the unmanned aerial vehicle, an LK (Lucas Kanade) method is used for calculating a light stream field according to a front frame image and a rear frame image, and noise light streams are filtered; each image is divided into an edge, a left middle part and a right middle part, and whether large obstacles exist on the left side and the right side or not is judged based on an SVM classifier; the sum of TTC in all columns is calculated, free sections and obstacle sections are calibrated and interpolated, and a maximum free communicating section is obtained; a translation amount and a rotation amount are obtained in combination with a left and right light stream balancing strategy, and therefore the unmanned aerial vehicle is controlled to fly avoiding obstacles. By means of the method, real-time obstacle-avoiding flight of the unmanned aerial vehicle in an unknown disordered environment can be realized.

The invention discloses a human body-free obstacle avoidance method and device based on an event camera, and an intelligent human body-free obstacle avoidance method. The method comprises the following steps: collecting an event image of a moving obstacle in real time by using a binocular event camera; calculating and storing center point coordinates of the moving obstacle in the left side event camera image and the right side event camera image at each moment, and size information and depth information of the moving obstacle at each moment; reading a center point coordinate of a moving obstacle in any camera continuous frame event image and size information and depth information of the moving obstacle, and calculating a motion vector of a target obstacle; and according to the size information and the motion vector of the target obstacle and the position of the target obstacle in the event image, setting a human-body-free obstacle avoidance triggering condition, and calculating an obstacle avoidance direction and a motion distance. According to the invention, obstacle avoidance of fast moving obstacles can be realized, unnecessary excessive obstacle avoidance maneuvering behaviors can be effectively avoided, and the calculation cost is low.

The invention provides a sweeping robot obstacle recognition and avoidance method based on depth vision, which is used for enabling a sweeping robot to sense obstacles in a front working area in advance and adopt a corresponding obstacle avoidance mode according to the types of the obstacles. The sweeping robot obstacle recognition and avoidance method based on depth vision comprises the following six steps: firstly, carrying out information acquisition on an area in front of the sweeping robot by using a depth camera; then extracting spatial position information of each pixel point in the depth image, and marking a ground area; marking a path space region in the depth image, and segmenting an image of the obstacle; according to the obstacle image, using an x-axis and y-axis pixel distribution histogram and a depth histogram to distinguish the obstacle category; selecting a detour obstacle avoidance mode or a turn-back obstacle avoidance mode according to the obstacle category, and executing an obstacle avoidance operation; and finally, enabling the sweeping robot to run forwards and carry out normal sweeping, and executing the first five steps circularly.

The invention discloses a robot. The robot comprises a chassis, a lifting mechanism, a mechanical arm and a robot head with a visual function. The lifting mechanism comprises a lifting motor, a lifting platform, a lifting platform mounting seat and a back plate fixed to the chassis. The lifting platform is fixed to the lifting platform mounting seat. A lead screw penetrates through the lifting platform mounting seat in the vertical direction. The lead screw is driven by the lifting motor through a synchronous belt to rotate. The lifting platform mounting seat is in threaded connection with thelead screw. The lifting platform is driven by the lifting platform mounting seat to move up and down. The mechanical arm and the robot head are respectively arranged on the lifting platform. Becausethe robot is provided with the mechanical arm and the lifting mechanism, articles with different heights can be grabbed and presented. The robot can be applied to places such as families, welfare homes and nursing homes to help the disabled, young people and the old.

A wearable intelligent sensing blind guiding system disclosed by the present invention comprises an MCU main control unit, a binocular camera, a voice broadcast module, a GPS positioning module, a local memory, a 4G / 5G communication interface and an antenna, the binocular camera is connected with the MCU main control unit through a USB interface, the GPS positioning module is connected with the MCU main control unit through a UART interface. The local memory is connected with the MCU main control unit through a bus interface, the 4G / 5G communication interface is connected with the MCU main control unit through a DTU interface, the 4G / 5G communication interface is connected with an antenna, and the voice broadcast module is connected with the MCU main control unit through a UART interface; the binocular camera collects environment information, and the MCU uses a CNN deep learning neural network model to detect various obstacles on a walking channel of the visually impaired person, determine distances and orientations of the obstacles, reasonably plan a walking route, identify zebra crossings and traffic lights at a traffic intersection, and prompt the visually impaired person to walk through voice.

The invention relates to an autonomous obstacle-avoidance snakelike track walking-type crushing conveyor. A conveyor front end obstacle avoidance acquisition device is formed by an infrared detection system and a GPS positioning device. When a head dolly runs, an infrared detection device collects information of roads ahead; an intelligent obstacle avoidance system carries out analysis on the collected signals and controls a track walking device and a cylinder steering assisting device to realize active obstacle avoidance; a GPS position recording module records the running tracks of the head dolly; the machine frame dollies at all parts of the conveyor are mutually independent; the dolly at each section adopts the track walking device, so that autonomous moving, and horizontal and vertical being can be realized independently; when the head machine frame dolly carries out autonomous obstacle avoidance, the middle dolly and the tail dolly carry out real-time tracking on the tracks walked by the head machine frame dolly through a control system; and a pressing disc type limitation device can reduce the cases of horizontal off-tracking and belt floating in the working process of a conveyer belt effectively, so that transport efficiency and economic benefit of the conveyer are improved.

The invention discloses an intelligent water surface monitoring triple-hulled vessel which comprises a triple-hulled vessel body and a control system. The triple-hulled vessel body comprises a main hull, side pieces and a connecting bridge; the main hull is provided with a navigation attitude adjusting device, a wind force and wind direction monitoring device, a monitoring device, a propelling device, a wireless charging device, a heat dissipation device, a water quality detection device, a lifting device and a rotating device; and the control system comprises a shipborne control system and aland-based control system. The shipborne control system comprises a positioning module, a remote communication module, a driving control module, a speed measuring module, a distance measuring module,an electric quantity monitoring and managing module, an intelligent obstacle avoidance module, an intelligent navigation attitude adjusting module and a fixed point control module. According to the intelligent water surface monitoring triple-hulled vessel, the inclination angle of the side pieces can be automatically and intelligently adjusted, autonomous obstacle avoidance of the triple-hulled vessel can be realized, and good cruising ability is achieved; and the intelligent water surface monitoring triple-hulled vessel is exquisite in structure, rich in function, high in intelligent degree and wide in application prospect.

The invention discloses a spacecraft surface crawling robot capable of autonomously sensing movement. The crawling robot comprises a mechanical structure and a control system. The mechanical structure comprises six multi-degree-of-freedom legs and feet composed of eighteen steering engines and connecting mechanisms thereof, and a robot platform main body, and the platform main body is provided with a storage battery, an electrostatic adsorption module composed of a relay switch, a voltage booster and an electrostatic adsorption film, and a depth camera with a built-in IMU sensor; the crawling robot achieves adsorption on the surface of a spacecraft based on the electrostatic adsorption principle. The control system adopts hardware such as an embedded microprocessor and an expansion interface board, and autonomous movement is realized through sensing-planning-control. Meanwhile, whether adsorption force exists or not can be controlled in cooperation with gaits of the robot, and the torque needed by leg lifting of the robot is reduced. And finally, a dynamic simulation method is provided to calculate the adsorption force required by the robot, and the crawling ability of the robot is verified. Adsorption, crawling, autonomous sensing and moving of the robot on the surface of the spacecraft are achieved.