5results about How to "Accurate planning" patented technology

The invention discloses an action instruction generation method, computing equipment and a machine readable storage medium, and relates to the technical field of intelligent equipment. The method comprises the steps of querying a preset scene knowledge base based on an input task instruction to obtain background knowledge corresponding to the task instruction; generating an enhancement instruction based on the background knowledge and the task instruction; and inputting the enhancement instruction and the body state of the controlled equipment into a pre-trained action planning model to obtain an action instruction for driving the controlled equipment to execute a task. By introducing a scene knowledge base and an instruction enhancement mechanism, precise understanding and reliable planning of fuzzy or complex instructions by the controlled equipment are realized, and the adaptability and task success rate of the controlled equipment under strange environments and complex tasks are improved. And the action sequence which is safe and efficient and conforms to the context situation is generated, so that the capability of continuously learning and executing tasks in the open world of the controlled equipment is realized at lower cost.

This invention discloses a collaborative scheduling system and method for driving and charging of connected heavy-duty vehicle clusters, relating to the technical field of intelligent management. The system includes the following steps: calculating the driving conversion coefficient and charging conversion coefficient of the vehicle cluster; calculating the vehicle cluster's transport capacity and transport efficiency; establishing a first mapping relationship and a second mapping relationship to obtain discrete transport capacity and discrete transport efficiency; matching collaborative vehicles; verifying the collaborative vehicles; and executing a first operation. This invention, by calculating the driving conversion coefficient and charging conversion coefficient of the vehicle cluster, more accurately predicts and plans the driving and charging needs of vehicles. Based on historical freight data and real-time order information, it allocates vehicle resources more rationally. Through collaborative scheduling, it reduces fuel consumption and electricity costs, reduces vehicle wear and maintenance costs, improves the response capability to emergencies by establishing mapping relationships and discretization analysis, and reduces idle time and improves vehicle utilization efficiency through intelligent scheduling.

This invention provides a method for creating a point-beam data transmission mission for a shipborne mobile receiving station to remote sensing satellites. The method includes: using the acquired approximate position and orbital element information of the shipborne receiving station, calculating a set of all approximate visible time windows for the entire day; then using this set to determine the approximate time window for the target data transmission mission; based on the approximate time window, sequentially calculating the ship's geocentric latitude, ship's travel distance, and spherical arc length; determining, based on the spherical arc length, whether the ship's course change exceeds a preset threshold; if so, performing segmented ship position prediction; otherwise, performing direct ship position prediction to obtain a precise predicted ship position; expanding the approximate time window based on the precise predicted ship position to obtain a precise time window; and then using the precise time window and the precise predicted ship position to construct the point-beam data transmission mission. This invention achieves precise planning of the satellite data transmission mission and ensures that the shipborne station antenna points towards the satellite to form a two-way closed link.

The application relates to a hypersonic vehicle trajectory planning method based on an N-K iterative convex optimization algorithm, and relates to the field of trajectory planning.The application is used to solve the problem that the existing vehicle trajectory planning method cannot accurately plan a vehicle trajectory.The application comprises the following steps: obtaining a dimensionless hypersonic gliding stage dynamics model;obtaining a linearized hypersonic gliding stage dynamics model;discretizing parameters in the linearized hypersonic gliding stage dynamics model to obtain a parameter-discretized hypersonic gliding stage dynamics model;obtaining control quantity constraints, process constraints and a trust region constraint in hypersonic vehicle trajectory optimization;constructing a trajectory planning problem based on iterative convex optimization by using the parameter-discretized hypersonic gliding stage dynamics model and the control quantity constraints, the process constraints and the trust region constraint;and solving the trajectory planning problem based on iterative convex optimization to obtain a hypersonic vehicle trajectory planning result.The application is used for planning a vehicle trajectory.

The application discloses a vehicle obstacle avoidance method and device, electronic equipment and a storage medium, and the method comprises the following steps: when detecting an obstacle object corresponding to a target vehicle, determining a first obstacle avoidance area and a second obstacle avoidance area corresponding to the target vehicle; determining a first obstacle avoidance path of the target vehicle in the first obstacle avoidance area according to at least one first obstacle avoidance point of the target vehicle in the first obstacle avoidance area; determining a second obstacle avoidance path of the target vehicle in the second obstacle avoidance area according to at least one second obstacle avoidance point of the target vehicle in the second obstacle avoidance area; and determining a target obstacle avoidance path corresponding to the target vehicle according to the first obstacle avoidance path and the second obstacle avoidance path. The target vehicle is more accurately planned to avoid the obstacle path, and the planned obstacle avoidance path is smoother.