14results about How to "Improve obstacle avoidance efficiency" patented technology

The invention relates to the technical field of cooperative obstacle avoidance systems, in particular to a cooperative obstacle avoidance system for an autonomous vehicle and a control method thereof, comprising an obstacle sensing unit for identifying a path of an obstacle in a road; and an obstacle avoidance unit planning an obstacle avoidance path of the vehicle through sensing information of the obstacle sensing unit, the obstacle sensing unit including: a first sensing data input unit for receiving, from at least two distance sensors, whether there is an obstacle and relative distance data of the obstacle; a first calculation unit for obtaining position information of the obstacle based on the relative distance data received from the first sensing data input unit; the system comprises an obstacle sensing unit and an obstacle avoidance unit, the environment can be comprehensively sensed, complex information can be rapidly processed, an optimal decision can be made, and real-time information exchange and decision coordination between vehicles are achieved.

The invention discloses an unmanned aerial vehicle obstacle avoidance method based on a millimeter wave radar, and relates to the technical field of unmanned aerial vehicle obstacle avoidance. The unmanned aerial vehicle obstacle avoidance method based on the millimeter-wave radar comprises the following specific steps that a user constructs an environment map with an unmanned aerial vehicle as the center based on millimeter-wave radar data; the motion state of the obstacle is judged through detection sound waves, and when the static coordinate (x1, y1) of the obstacle is obtained, or when the vector # imgabs0 # millimeter wave radar obtains the vector # imgabs1 # of the dynamic coordinate of the obstacle, the predicted motion trail of the unmanned aerial vehicle and the motion trail of the obstacle are generated. Dynamic coordinates of a dynamic obstacle are obtained through the millimeter wave radar, multiple pieces of position information and position coordinates of the obstacle are obtained through detection sound waves returned at two adjacent times, the path track of the dynamic obstacle is integrated on the basis, and whether the dynamic obstacle has a contact point with follow-up flight of the unmanned aerial vehicle or not is judged through the execution module and a user; the unmanned aerial vehicle based on the millimeter-wave radar can avoid dynamic obstacles.

The application provides a low-altitude terrain following flight path guiding method for unmanned helicopters, and is based on an enhanced vector field histogram algorithm and on-board laser radar spatial gridding data, and proposes a low-altitude terrain following flight path guiding method for unmanned helicopters in a three-dimensional space, introduces unmanned aerial vehicle flight performance constraints and safe flight standards, constructs a safe flight pipeline model for unmanned helicopters, designs a laser radar gridding detection information partial loss filling model based on a first-order model, fully utilizes the detection information of the on-board laser radar, guarantees the robustness of algorithm solving and the safety of calculation results, and meets the obstacle avoidance requirements in a three-dimensional space in a complex and severe flight environment. According to the on-board laser radar detection data and the safe flight constraints of the unmanned helicopter, the application can realize the calculation of optimal flight waypoints for the low-altitude terrain following flight path guiding of the unmanned helicopter.

The present invention discloses a method for robot recognition of obstacles based on human-computer interaction, S1, taking a panoramic photo including the starting point and the end point of the robot, uploading the photo to a remote terminal, uploading the photo to a central processing module in the robot through the remote terminal, S2, after the robot receives the photo, plans a straight path of the starting point and the end point through an original path planning module and sends it to an operation decision unit, the present invention relates to the field of robot technology. The method for robot recognition of obstacles based on human-computer interaction can select the optimal obstacle avoidance direction according to the shape of the obstacle, and after selecting the correct direction, can calculate the optimal path in real time according to the shape of different obstacles, ensuring that the robot can safely, effectively, accurately and efficiently select the optimal path during the obstacle avoidance process, thereby greatly improving the robot's obstacle avoidance efficiency.

The present disclosure relates to the technical field of intelligent device control, and provides a control method and device for a surface cleaning device. The method comprises: acquiring an obstacle detection signal on a current travel route of the surface cleaning device; determining an obstacle type of an obstacle corresponding to the obstacle detection signal according to the obstacle detection signal and a reference detection signal; and controlling a cleaning component of the surface cleaning device according to the obstacle type of the obstacle corresponding to the obstacle detection signal.

The invention relates to the field of robots, in particular to a robot, an emergency obstacle avoidance method and device thereof and a program product. The method comprises the following steps: predicting state information of the robot; performing external expansion based on the state information of the robot to obtain a dangerous area and an alarm area corresponding to the robot; detecting the positions of obstacles in the alarm area and the dangerous area; and determining the moving speed of the robot according to a preset corresponding relation between the position of the obstacle and the moving speed, and carrying out emergency obstacle avoidance based on the moving speed. The method does not need to re-plan and calculate, is beneficial to improving the obstacle avoidance efficiency, reduces the out-of-control probability of the robot, and improves the working efficiency and safety of the robot.

The application discloses a rare earth mine path planning method based on a particle swarm optimization algorithm unmanned aerial vehicle, and comprises the following steps: establishing an unmanned aerial vehicle automatic path planning model under a rare earth mine three-dimensional map, establishing a cost function, establishing a main constraint model of the unmanned aerial vehicle path planning, establishing an unmanned aerial vehicle path planning mathematical model, solving the unmanned aerial vehicle automatic path planning by using a TLDEPSO algorithm, dividing each round of iteration in the evolution process into two stages, and respectively adopting respective learning mechanisms for different particles in the population in different stages. A particle modification method is used to correct the search direction of the particle and guide the population to explore the problem space; a top-level neighborhood exploration mechanism is proposed to guarantee the convergence performance of the algorithm. The application has the advantages that in a complex rare earth mine three-dimensional flight scene, the obstacle avoidance capability and the optimal obstacle avoidance route are best, all obstacle threats in the test scene can be perfectly avoided, and the obstacle avoidance efficiency is higher.

The present invention discloses a method for optimizing positioning, navigation and path planning of unmanned aerial vehicles based on machine learning, including dividing the unmanned aerial vehicle activity area into three-dimensional grids based on the coverage of sensors, obtaining the obstacle layout of each grid, calculating the environmental complexity of each grid based on the obstacle layout, setting a response time for the grid according to the environmental complexity, constructing an obstacle avoidance model, obtaining an obstacle avoidance strategy according to the obstacle avoidance model, constructing a pathfinding algorithm based on the obstacle avoidance strategy, using the response time as the interval search time of the pathfinding algorithm, obtaining a feasible path set based on the pathfinding algorithm in the unmanned aerial vehicle activity area, constructing a multi-objective function to optimize the feasible path set, and obtaining the optimal path. The method adopts a machine learning method, can adapt to the needs of different environments and tasks, effectively enhances the obstacle avoidance capability and optimizes the path, and at the same time improves the autonomy and intelligence level of the unmanned aerial vehicle, and has good interpretability.

The embodiments of the present application disclose an intelligent obstacle avoidance method, device, lawn mowing robot and storage medium, including: detecting whether there is an obstacle in the current path of the lawn mowing robot, if there is, generating an obstacle avoidance path through the first detection results of the first ultrasonic sensor and the second ultrasonic sensor, and controlling the lawn mowing robot to operate according to the obstacle avoidance path, during the operation of the lawn mowing robot, detecting the obstacle again through the second ultrasonic sensor, correcting the obstacle avoidance path according to the second detection result of the second ultrasonic sensor, and controlling the lawn mowing robot to continue operating according to the corrected obstacle avoidance path. The embodiments of the present application can generate an obstacle avoidance path by combining two ultrasonic sensors with different detection angles and correct the obstacle avoidance path, thereby improving the obstacle avoidance efficiency of the lawn mowing robot.

The application discloses a mechanical arm singular point avoidance method, system, device and storage medium, and technical scheme points thereof are as follows: acquiring a pose and a joint angle of a mechanical arm; judging whether to enter a singular region and a singular type according to the pose and the joint angle; performing first-level processing in the case of a wrist singular type, performing second-level processing in the case of a shoulder singular type, and performing third-level processing in the case of an elbow singular type. The application can improve obstacle avoidance efficiency, ensure motion stability and reduce calculation complexity.

The application is suitable for the technical field of dynamic path planning, and particularly relates to an industrial robot dynamic path planning learning method and system.The method comprises the following steps: S100: demarcating a working area of an industrial robot, selecting a deployment position of a plurality of marker lights in each industrial robot, setting the color of each marker light, and generating a combined code, wherein the combined code of each industrial robot is different; collecting video monitoring data containing all industrial robots by using a video monitoring device pre-deployed in the working area; according to a preset step, a plurality of snapshots are intercepted, and the position of the industrial robot is located through the combined code; and S200: grid division is performed on the working area, and a reference point is selected.The application can realize incremental planning of the industrial robot by defining a conflict line, can dynamically adjust the moving route, is convenient for quickly adapting to changes in obstacles, and greatly improves the obstacle avoidance efficiency of the industrial robot.

The invention discloses an obstacle avoidance path determination method and device, engineering equipment and a machine readable storage medium, and relates to the technical field of engineering equipment. The method comprises the following steps: when an obstacle is detected, determining whether an obstacle avoidance control condition is satisfied based on obtained distance detection information; under the condition that the obstacle avoidance control condition is met, the size parameter of the obstacle is determined based on the distance detection information; acquiring position information of each joint of the cantilever crane; and determining an obstacle avoidance control path based on the size parameters and the position information. The distance detection of the obstacle is realized through the simple distance detection device so as to determine whether the obstacle exists or not, and the size parameter of the obstacle is determined based on the distance detection information when the obstacle exists, so that an effective data reference is provided for avoiding the obstacle. The difficulty of obstacle avoidance planning is reduced, and through automatic obstacle avoidance control, the experience requirements on operators are reduced, the labor cost is reduced, and the obstacle avoidance efficiency is improved.

Embodiments of the present application disclose a vehicle obstacle avoidance path planning method and device and electronic equipment, and relate to the technical field of automatic driving. The method comprises the following steps: determining a target obstacle in a current cruising lane; predicting a running state of the target obstacle at each discrete time point within a predetermined time length; determining, based on a current execution path of the ego vehicle, a running state of the ego vehicle at two or more predicted positions of the ego vehicle in a lateral direction of the current cruising lane at each discrete time point; calculating, according to the running state of the target obstacle at each discrete time point, the running state of the ego vehicle at each predicted position of the ego vehicle at each discrete time point, and a preset dangerous degree model, a dangerous degree of the target obstacle to each predicted position of the ego vehicle at each discrete time point; and determining, based on the dangerous degree of the target obstacle to each predicted position of the ego vehicle, an initial obstacle avoidance route of the ego vehicle to the target obstacle within the predetermined time length. The present application is suitable for obstacle avoidance.

The invention relates to the technical field of unmanned aerial vehicle obstacle avoidance control, in particular to a radar-based unmanned aerial vehicle obstacle avoidance control method, system and device, and the method comprises the steps: collecting obstacle data nearby a flight process of an unmanned aerial vehicle through a laser radar; preliminarily screening the interval by using the braking distance of the unmanned aerial vehicle and the obstacle distance closest to the unmanned aerial vehicle; if no obstacle exists in the interval, marking the interval as a first selectable interval; based on the distribution condition of obstacles in the interval, determining the avoidance priority of the interval, and further screening a second selectable interval; and determining the next movement direction of the unmanned aerial vehicle by using the closeness degrees of the center directions of the first selectable interval and the second selectable interval with the destination direction of the unmanned aerial vehicle, the current movement direction of the unmanned aerial vehicle and the last movement direction of the unmanned aerial vehicle. The invention aims to screen the selectable flight interval of the unmanned aerial vehicle and improve the obstacle avoidance efficiency of the unmanned aerial vehicle.