655 results about "Planning algorithms" patented technology

A method for automated lane centering and/or lane changing purposes for a vehicle traveling on a roadway that employs roadway points from a map database to determine a reference vehicle path and sensors on the vehicle for detecting static and moving objects to adjust the reference path. The method includes reducing the curvature of the reference path to generate a reduced curvature reference path that reduces the turning requirements of the vehicle and setting the speed of the vehicle from posted roadway speeds from the map database. The method also includes providing multiple candidate vehicle paths and vehicle speeds to avoid the static and moving objects in front of the vehicle.

Embodiments of the invention comprise a system and method that enable robotic harvesting of agricultural crops. One approach for automating the harvesting of fresh fruits and vegetables is to use a robot comprising a machine-vision system containing rugged solid-state digital cameras to identify and locate the fruit on each tree, coupled with a picking system to perform the picking. In one embodiment of the invention a robot moves through a field first to “map” the field to determine plant locations, the number and size of fruit on the plants and the approximate positions of the fruit on each plant. A robot employed in this embodiment may comprise a GPS sensor to simplify the mapping process. At least one camera on at least one arm of a robot may be mounted in appropriately shaped protective enclosure so that a camera can be physically moved into the canopy of the plant if necessary to map fruit locations from inside the canopy. Once the map of the fruit is complete for a field, the robot can plan and implement an efficient picking plan for itself or another robot. In one embodiment of the invention, a scout robot or harvest robot determines a picking plan in advance of picking a tree. This may be done if the map is finished hours, days or weeks before a robot is scheduled to harvest, or if the picking plan algorithm selected requires significant computational time and cannot be implemented in “real time” by the harvesting robot as it is picking the field. If the picking algorithm selected is less computationally intense, the harvester may calculate the plan as it is harvesting. The system harvests according to the selected picking plan. The picking plan may be generated in the scout robot, harvest robot or on a server. Each of the elements in the system may be configured to communicate with each other using wireless communications technologies.

The invention discloses a parking system path planning method based on dynamic time windows, and belongs to the technical field of path planning. The method is characterized by comprising the following steps: S1, building a work environment model of AGVs in an intelligent garage in a topological method; S2, setting priority for each AGV and each car parking/picking task according to different evaluation criteria; S3, using a Dijkstra algorithm to plan a shortest possible path for an AGV accepting a task; S4, arranging feasible path time windows; S5, designing conflict resolution strategies according to different types of conflicts; and S6, planning a conflict-free optimal path for the AGV using a parking system path planning algorithm based on dynamic time windows. A time-sharing use strategy is used, and the Dijkstra algorithm and a time window method are combined effectively, so that the problem that the existing multi-AGV path planning is of poor flexibility and is prone to deadlock or collision conflict is solved effectively, and a shortest conflict-free optimal path can be planned for an AGV accepting a task. In addition, the overall operation efficiency of an intelligent three-dimensional parking system can be improved effectively, and the car parking/picking waiting time can be reduced for social members.

A system and method for providing path planning and generation for automated lane centering and/or lane changing purposes for a vehicle traveling on a roadway, where the method employs roadway measurement values from a vision camera within an effective range of the camera and roadway measurement values from a map database beyond the range of the camera. The method uses the roadway measurement values from the camera to determine a desired path along a first segment of the roadway and identifies an end of the first segment based on how accurately the camera defines the roadway. The method then uses the roadway measurement values from the map database to determine the desired path along a second segment of the roadway that begins at the end of the first segment, where a transition from the first segment to the second segment is smooth.

The invention discloses a shortest path planning method for dynamic origins, and belongs to the technical field of dynamic path guidance in an intelligent traffic system. The shortest path planning method is used for optimizing vehicle traveling routes. The shortest path planning method always takes a current vehicle position as a starting point and predicts road condition information such as traffic flow of relevant road sections and road intersections, and the like for many times according to vehicle running time to calculate a shortest path according to a path planning algorithm in a no-request mode at regular time, thereby acquiring a shortest time path in accordance with the real-time conditions of a road network better and directly displaying the shortest time path on the screen of a vehicle navigation system; and meanwhile, by the method, the update operation amount is less so as to shorten calculation time.

The invention relates to a track planning method of a redundant space mechanical arm for on-track catching. The catching operation of the space mechanical arm is divided into a rough catching stage and a fine catching stage, so that problems are simplified. By aiming at outstanding problems of different stages, different planning algorithms are adopted. In the rough catching stage, a track searching algorithm based on configuration space is adopted, and the algorithm is based on the test in the configuration space; and in the fine catching stage, a pseudo-inverse algorithm based on kinematics is adopted, and the final precise catching is guaranteed by compensating the relative movement of a target.

A recommendation system exploits a repository of mashups to provide design-time assistance to the user through relevant suggestions as to what outputs can be generated along with the best plans to generate those outputs. An output ranker ranks the outputs of the system base on their popularity scores, and a planner uses metric planning algorithms and a configurable utility function. The system takes into account popularity and semantic similarity when recommending services and sources.

The invention claims for protection of a coordinated local path planning method based on V2X communication and binocular vision. An OBU acquires vehicle body information and environmental informationthrough a binocular preposed camera, OBD equipment and V2X communication and the information is transmitted to a coordinated local path planning controller; with a traffic object mixed state estimation model, state prediction is carried out on a traffic object state, spatio-temporal data fusion is carried out on the traffic object information and traffic rules after state estimation based on a multi-source data fusion algorithm, a traffic road map with high credibility is constructed by the fused traffic data according to a coordinate mapping model, an own vehicle state is calculated by combining own vehicle information according to an own vehicle state estimation model, and then an optimal smooth driving path of the current vehicle is calculated based on an improved local path planning algorithm; and then the path is transmitted to the OBU and the information is broadcasted to other vehicles through V2X. According to the invention, the accuracy of vehicle environment perception and local path planning is improved by combining visibility-range and non-visibility-range traffic object sense sensing.

The embodiment of the invention discloses a navigation route planning method and device. The method comprises the steps that an algorithm planning route is generated according to starting point and terminal point position information input by a user and a set route planning algorithm; a partial planning route matched with a partial experience route in a partial experience route set in the algorithm planning route is acquired according to the preset partial experience route set; the algorithm planning route is partially replaced according to the partial planning route and the partial experience route matched with the partial planning route, and a navigation route is generated and provided for the user. According to the navigation route planning method and device, by means of the technical scheme, the partial unreasonable route existing in the algorithm planning route is adjusted according to the pre-stored partial experience route, therefore, the defects existing in the navigation route acquired through a traditional algorithm can be overcome, the unreasonable route existing in the navigation route is corrected, the practicability and the precision of the navigation route are improved, and the time that the user consumes due to the unreasonable navigation route can be reduced.

An intelligent disaster prevention and escape method includes the steps of: sensing surrounding environment information of plural nodes of a region of a building to generate plural sensing signals of the nodes respectively; calculating a risk coefficient of each node according to the sensing signals; calculating a threat coefficient for plural paths according to the risk coefficients and the distances between the adjacent nodes, for executing an escape path planning algorithm to produce a safest path plan; and producing plural escape instructions for the nodes respectively according to the safest path plan. The invention has the effect of producing the safest path plan according to the risk coefficient and the distance between adjacent nodes, so as to provide safe and immediate escape instructions to guide people to escape and evacuate and reduce casualties.

The invention provides a route planning method for an autonomous vehicle based on a vector map and a grid map. The route planning method comprises: planning a global shortest route of the current position of the autonomous vehicle to a target point through a global vector map; obtaining a current partial grid map of the current position of the autonomous vehicle; and according to the global shortest route, calculating a partial motion route based on the partial grid map, and controlling the autonomous vehicle to travel to the target point according to the partial motion path. According to theroute planning method for the autonomous vehicle based on the vector map and the grid map, the vector map is used as an environment model in the global route planning layer, and the grid map is used as an environment model in the partial motion route planning layer, that is, different maps are used as environment models in different planning layers, and at the same time, different types of planning algorithms are used, so that the real-time performance and accuracy of the algorithm under an actual scene are met at the same time, and the algorithm combining the vector map and the grid map greatly reduces the occupation of system operation resources.

The invention relates to a path planning method, and specifically relates to a time window-based task segmentation multi-AGV path planning algorithm. The method comprises steps of first, generating anAGV working environment model; second, generating a task, and decomposing the task into multiple secondary stages according to different task types; and third, assigning the task by a task assigningmodule according to task priorities, picking the task out by a scheduling system from a high-priority queue, then determining which stage the task is in, if the task is not executed, assigning the task to closest AGV by using an improved A* algorithm, and setting the task state in first secondary stage; if the task is in the second or after stages, and planning a non-conflict shortest path for theAGV bound with the task by using the time widow algorithm by the scheduling system. Shortest and fastest paths are planned by using the improved A* algorithm and time window algorithm, so that the working efficiency is improved and calculation errors are reduced.

The invention provides a fire emergency evacuation simulation method. On the basis of establishing a real three-dimensional fire scene, researches are made around a vector-field-based global motion planning algorithm to navigate the escape of a plurality of individuals in the fire scene in real time. The method comprises the following steps of calculating a vector-field-based safety field in real time by virtue of the algorithm, constructing a fire-scene-based crowd behavior model in combination of a social force model-based local collision avoiding algorithm, and finally providing fire escape guidance for each escape individual in the scene according to the fire-scene-based crowd behavior model. According to the fire emergency evacuation simulation method, a theoretical basis is provided, the calculation accuracy can be ensured, and verification application is developed under various experimental conditions; the method has the characteristics of low calculation complexity, high simulation effect trueness and the like, and the real-time emergency evacuation of hundreds of escape individuals can be simulated during practical application.

An interactive method for radiation treatment planning is disclosed. The method applies to staged treatment planning algorithms, as used, for example, with arc therapy. It allows the user to hold the optimization algorithm at a stage in order to make adjustments to the objective function before advancing to the next stage. If adjustments are made, the user can revert to an earlier stage and re-run the optimization process using the adjusted objective function. While a hold is imposed, the treatment planning software may continue optimization at the current stage.

The invention discloses an intelligent cleaning robot and a path planning method thereof. A sensor module is used for analyzing and feeding back real-time cleaning environment information; an accuratepositioning module is used for acquiring the position of the current intelligent cleaning robot on the environment map which is established through a geometric-topological hybrid map technology, andthe environment map and the real-time position are combined, the optimal sweeping path is planned by using an advanced path planning algorithm, and the data is uploaded to a cloud platform for realizing the real-time analysis, recording, and control; a driving module is used for driving the intelligent cleaning robot to run according to the planned optimal path and carrying out cleaning operation;a man-machine interaction module can be used for displaying the working state and performance of the intelligent cleaning robot by combining the temperature and humidity sensor with the camera, and the remote control and reservation functions of the intelligent cleaning robot can be completed through wifi/Bluetooth technology. According to the invention, the labor intensity is reduced, the laborefficiency is improved, and the robot is suitable for hotels, libraries, office places and public families.

The invention discloses a lambda* path planning algorithm, which is improved aiming at solving the problems that contained nodes are many and consumed time is much in an open table in the existing A* algorithm. The algorithm comprises the steps of using visual images to establish a path planning environment, creating an open table and a close table, creating a node data structure, sealing a path, and adding a smooth process to smooth the path. The lambda* path planning algorithm disclosed by the invention is mainly used for quick path planning of robot two-dimensional and three-dimensional spaces.

The invention, which belongs to the field of intelligent algorithm optimization, provides a reinforced learning robot path planning algorithm based on a potential field in a complex environment, thereby realizing robot path planning in a complex dynamic environment under the environmental condition that a large number of movable obstacles exist in a scene. The method comprises the following steps:modeling environment space by utilizing the traditional artificial potential field method; defining a state function, a reward function and an action function in a Markov decision-making process according to a potential field model, and training the state function, the reward function and the action function in a simulation environment by utilizing a reinforcement learning algorithm of a depth deterministic strategy gradient; and thus enabling a robot to have the decision-making capability of performing collision-free path planning in a complex obstacle environment. Experimental results showthat the method has advantages of short decision-making time, low system resource occupation, and certain robustness; and robot path planning under complex environmental conditions can be realized.

The invention discloses an energy-saving real-time dynamic route planning method applicable to an intelligent networked automobile. The energy-saving real-time dynamic route planning method specifically comprises the following steps: establishing a three-dimensional road network model considering time dimension; acquiring the state of signal lamps at the tail end of each road section; searching all feasible routes in a road network by virtue of a full-feasible path search algorithm according to a starting point and a destination; according to traffic flow information, computing the shortest transit time and calculating the theoretical transit time on the road section; recommending a route with the shortest transit time as a real-time dynamic route; and considering an automobile potion change factor during the driving of an automobile, re-invoking a dynamic route planning algorithm while entering an effective range of the tail end of the road section, and further updating the optimal real-time dynamic route of the current automobile. The energy-saving real-time dynamic route planning method has the advantages that a trip route with the shortest full-process theoretical transit time in a three-dimensional space-time network can be searched; and the driving energy consumption of the automobile can be remarkably reduced, and the aim of energy-saving tripping is achieved.

The invention relates to a robot path planning algorithm based on an optimized ant colony algorithm. The algorithm comprises the following steps: S1, initializing an inspiring factor to construct thecomprehensive inspiring information for the movement of the robot according to a target gravitation generated by an artificial potential field and an ant colony algorithm; S2, updating pheromone in the art colony algorithm by adopting a wolves distribution rule; and S3, optimizing a planned path by utilizing a path optimization algorithm. By adopting the robot path planning algorithm, an optimum path can be rapidly and efficiently planned.

The invention discloses a multi-satellite cooperative observation business scheduling method and relates to satellite observation business planning and scheduling technology in a satellite operation control field. The multi-satellite cooperative observation business scheduling method is based on a satellite operation control system, builds a star land resource management model, a satellite orbit calculation model and a satellite access information calculation model, adopts a satellite observation business dynamic planning algorithm to regulate satellite observation business rapidly and dynamically, adopts an automatic processing mechanism to make a satellite load control plan and a data receiving plan immediately, adopts a satellite actual load control instruction compilation business trigger mechanism to compile satellite actual load control instructions in real time, and schedules an electronic signal detection satellite and an imaging observation satellite to complete cooperative observation business. The multi-satellite cooperative observation business scheduling method has the advantages of being rapid in response speed, accurate in calculation method, high in automation and the like and is particularly suitable for a marine moving target multi-satellite cooperative observation field.

The invention discloses an indoor area covering method suitable for a vehicle type mobile robot. The method includes the steps of firstly, building a two-dimensional static raster map based on information of sensors such as a laser range finder, completing raster cost distribution of the static map, and forming a dynamic cost map; secondly, completing area dividing of the cost map, and obtaining the information of sub-areas; finally, building a map according to the adjacency relationship between the sub-areas, applying a sub-area planning algorithm based on a minimum tree to the map to obtain a sub-area planning sequence, applying an area transferring algorithm based on a Dijkstra algorithm to obtain inter-area transferring routes, and using different covering strategies according to the specifications of the sub-areas to achieve complete area covering. Compared with a traditional method, the indoor area covering method suitable for the vehicle type mobile robot has the advantages that multi-strategy covering of the different areas is achieved, the covering efficiency of the robot can be improved, and the indoor area covering method conforms to the perceiving habits of people.

The invention discloses a movement subdivision control method of a wheeled mobile robot. The movement subdivision control method of the wheeled mobile robot comprises the steps that (1) three trajectory tracking movement control strategies based on a biologically inspired neural dynamic model, an energy optimization model and a model predictive control model are integrated; (2) a current posture error vector is worked out according to a current actual posture obtained through feedback and a reference posture given by a route planning algorithm; (3) the control strategy is selected according to the stage where the mobile robot is located, if it is in an early tracking period, the trajectory tracking movement control strategy based on the biologically inspired neural dynamic model is selected; if it is in a medium tracking period, the trajectory tracking movement control strategy based on the energy optimization model is selected; if it is in a later tracking period, the trajectory tracking movement control strategy based on the model predictive control model is selected. The movement subdivision control method of the wheeled mobile robot can achieve the best control over the whole process of the wheeled mobile robot, and achieve robustness, energy saving performance and stability while carrying out accurate trajectory tracking.

An embodiment of the invention provides an automatic compilation method for a passenger flow demand based train working diagram. The method mainly comprises the steps of establishing a train working diagram optimization model according to basic parameters and passenger flow information, wherein the train working diagram optimization model includes a train cyclic working model, a train arrival and departure moment calculation model, a train sequential constraint model, a train load factor calculation model and a target function model; and solving the train working diagram optimization model by adopting a dual-layer planning algorithm combining a heuristic algorithm with nonlinear planning to obtain the passenger flow demand based train working diagram. According to the embodiment of the invention, high and low-peak time periods and corresponding intervals do not need to be pre-specified and the train working interval is automatically changed along with the passenger flow demand; and the automatically compiled train working diagram can meet constraint conditions of turn-back time, an available vehicle number, a load factor and the like, the feasibility of the working diagram is ensured, and on the premise of meeting the passenger flow demand, the operation cost is reduced and the working diagram compilation efficiency can be greatly improved.

The invention relates to a model-constraint-based mechanical arm energy optimal trajectory planning control method and device. The model-constraint-based mechanical arm energy optimal trajectory planning control method comprises the steps that initial conditions are set and mechanical arm joint angle position description with respect to time is calculated and obtained through a cubic spline interpolation algorithm; on base of the mechanical arm joint angle position description and in combination with a dynamics model, a continuous function of moment with respect to time is obtained; a nonlinear constrained planning model taking mechanical arm movement energy consumption as the optimizing target is established, and in combination with the mechanical arm joint angle position description, thecontinuous function of the moment with respect to time and friction force energy consumption, energy consumption of a target function is solved; and on base of the nonlinear constrained planning model taking mechanical arm movement energy consumption as the optimizing target, the minimum value of energy optimal trajectory planning is iteratively solved adopting a sequential quadratic planning algorithm, and a mechanical arm optimal trajectory is obtained. Compared with the prior art, the model-constraint-based mechanical arm energy optimal trajectory planning control method and device do notneed a large number of complex calculation and have good real-time performance, and energy consumption is least.

The invention provides an unmanned aerial vehicle route planning method based on an improved bat algorithm. According to the method, the optimization success rate is introduced to change the speed updating mode of the individual bats based on the conventional bat algorithm; meanwhile, the chaotic method is applied to initialize the distribution of the individual bats in the search space and the concept of the artificial potential field is utilized to simulate the gravitational field of the ending point and the repulsive field of the starting point and the obstacle so as to accelerate the speedof the individual bats to the optimal solution; and finally the improved bat algorithm based on the chaotic artificial potential field is proposed. Compared with the conventional bat algorithm, the track length is shortened for 36.56%, the planning time is shortened for 56.05% and the obstacle avoidance fitness value is reduced for 49.53% by the method; and compared with the differential evolutionary bat algorithm, the track length is shortened for 27.16%, the planning time is shortened for 27.30% and the obstacle avoidance fitness value is reduced for 42.46% by the method in the unmanned aerial vehicle route planning task so that the method is a route planning algorithm with practical significance.