35results about How to "Efficient path planning" patented technology

The invention discloses a method and device for monitoring and clearing smart garbage based on edge computing. A cloud server and a plurality of edge servers are respectively set up; smart terminals are set at each garbage can, and the acquired sensor information is sent to the edge through a communication module on a regular basis. Server; set up a data monitoring module on the edge server, analyze the data sent by the smart terminal, obtain various data in the trash can, and store them in the local database of the edge server and the cloud server database respectively; On the human-computer interaction side, according to the delay requirements of the business, the business that needs to be processed in real time is set on the edge server, and other businesses are set on the cloud server; the edge server uses the received data to plan the path and send it to the garbage truck, the garbage The cleaning vehicle realizes the garbage removal according to the planned path. The invention can monitor various states of the trash can, which is not only beneficial to the planning of the cleaning and transportation path, but also can judge whether there is a fire hazard in the trash can; the system architecture is reasonably set to realize low delay.

The invention provides an electronic chart-based global path planning method for optimal energy consumption of unmanned ship ant colonies. 1. After processing the electronic chart and converting it into a processable file form, determine the feasible area and obstacle area of ​​the map, and use the visualization method to find out the set of feasible paths between the starting point, target point and obstacle vertices to ensure These routes do not pass through unfeasible areas to ensure the safety of navigation of unmanned surface vehicles. 2. Establish a mathematical model of motion, and establish a motion model of the unmanned ship, so as to realize the grasp of the propulsion and motion characteristics of the unmanned ship. 3. Unmanned boat data acquisition, when the unmanned boat sails on the water surface, it obtains information such as the course, hull position, and vertical acceleration of the ship; 4. Uses the ant colony algorithm to search for a track that meets the requirements. 5. Establish the energy consumption model of the unmanned surface vehicle under the interference of ocean currents, and improve the ant colony algorithm on the premise of optimal energy consumption to obtain the path that meets the safe navigation conditions and consumes the least energy.

The invention discloses a method for planning a local path of an unmanned vehicle based on model prediction. Step 1, establishing a kinematics model of an unmanned vehicle; Approximation of the driving environment; step 3, fitting the lane line and road edge curve; step 4, constructing the objective function J, the first and second items of the objective function represent the distance between the predicted value and the reference position of the center line of the main lane The deviation; the third item represents the deviation between the heading angle of the predicted output and the main lane centerline heading angle, so as to ensure that the vehicle heading angle is the same as the road heading angle, and the front wheel rotation angle will not change suddenly; the fourth item ensures that the vehicle follows the reference speed Carry out driving; The fifth item is to avoid the obstacles existing on the current lane and avoid collisions. Compared with the prior art, the present invention ensures fast and efficient path planning, and facilitates the calculation of the shortest distance between the main vehicle and surrounding vehicles and obstacles.

The invention discloses a method for allocating target points in robot formation. Step 1) calculate the set of path lengths from each robot to all target points according to the position coordinates of each robot and the target point; The extraction method selects elements in the path length set of the robot to form multiple formation matrices; step 3) calculates the norm of each formation matrix and sorts them, and the formation matrix corresponding to the smallest norm is the matrix of the formation forming the shortest path ; Step 4) Judging whether the formation-forming shortest path matrix is ​​the final target point distribution matrix, selecting the final target point distribution matrix, and the robot formation-forming target point distribution is completed. In an environment with obstacles, the present invention can realize high-efficiency formation formation with minimum time and path consumption, ie formation initialization, while avoiding obstacles, so as to achieve optimal path planning.

The invention discloses a road condition query and taxi appointment system based on a set top box. Real-time query of road conditions and planning of an optimal path can be achieved through network communication between the set top box and a large data center; besides, taxi appointment can be carried out through the set top box. The invention further discloses a road condition query method and a taxi appointment method based on the set top box. By the adoption of the system and method, the functions of the set top box are enriched, and travel of a user is also greatly facilitated.

The invention discloses a robot behavior control method based on virtual reality. The control method includes the steps of S1, after environmental data of a controlled robot is collected in real timeto obtain a robot environment map, constructing an environmental cost map of the robot according to the obtained robot environment map; S2, according to the constructed environmental cost map, planning an optimal path to an assigned target point, controlling the robot to move according to the planned path. The method has the advantages of being easy to control, small in demanded communication bandwidth, high in timeliness, control precision and efficiency, flexible to use and the like.

The invention discloses an indoor multi-mobile-robot cooperative system based on a fuzzy algorithm and two-dimensional code self correction. The system comprises multiple rotor bodies and two-dimensional codes distributed at different indoor positions. Each of the two-dimensional codes comprises a QR code which represents the position coordinate of each two-dimensional code in an indoor two-dimensional coordinate system. Each of the robot bodies is provided with a single chip microcomputer, an acceleration meter module, a gyroscope module, a two-dimensional code recognition module, a communication module, and an ultrasonic sensor. The system has the low cost, the efficient path planning can be realized, multiple robots are in cooperative operation and the conflict is avoided, and the working efficiency is high.

The invention provides a method and system for planning an internal road path, belonging to the field of traffic planning. The path planning method first constructs a road network according to internal road conditions, and adds the starting point and ending point of the current vehicle to the road network, constructs a path information set S, and adds the starting point of the vehicle to S; then takes all relevant road sections between the starting point and the ending point of the current vehicle , construct U and add all the edges corresponding to the relevant road sections and all nodes associated with the relevant road sections to U; take the newly added point in S as the key point, and mark all the candidate edges that can reach any point in U from the key point, And obtain the road condition information and road attribute information corresponding to the candidate edge; calculate the weight of the road section according to the road condition information and road attribute information, select the edge corresponding to the minimum weight value and the corresponding node to add to S; when S contains both the starting point and the ending point of the vehicle, output the plan path. The present invention simultaneously considers real-time traffic conditions and traffic rule constraints, avoids traffic jams as much as possible, and improves traffic transportation efficiency.