588 results about "Trajectory optimization" patented technology

The invention discloses an air traffic control system for four-dimensional (4D)-trajectory-based operation. The air traffic control system comprises a data communication module, a monitoring data fusion module, an airborne terminal module and a control terminal module, wherein the monitoring data fusion module is used for fusing the monitoring data of an air traffic control radar and automatic dependent monitoring data, and providing real-time trajectory information for the control terminal module; and the control terminal module comprises a preflight conflict-free 4D trajectory generation sub-module, an in-flight short-term 4D trajectory generation sub-module, a real-time flight conflict monitoring and alarming sub-module and a flight conflict resolution 4D trajectory optimization sub-module. The invention also discloses an air traffic control method for the system. The control terminal module processes flight plan data, generates 4D trajectories, analyzes potential traffic conflicts of air traffic conditions and provides an optimal resolution scheme. By the system and the method, flight conflicts can be effectively prevented, and the safety of air traffic can be improved.

The present invention provides computer implemented methodology that permits the safe landing and recovery of rotorcraft following engine failure. With this invention successful autorotations may be performed from well within the unsafe operating area of the height-velocity profile of a helicopter by employing the fast and robust real-time trajectory optimization algorithm that commands control motion through an intuitive pilot display, or directly in the case of autonomous rotorcraft. The algorithm generates optimal trajectories and control commands via the direct-collocation optimization method, solved using a nonlinear programming problem solver. The control inputs computed are collective pitch and aircraft pitch, which are easily tracked and manipulated by the pilot or converted to control actuator commands for automated operation during autorotation in the case of an autonomous rotorcraft. The formulation of the optimal control problem has been carefully tailored so the solutions resemble those of an expert pilot, accounting for the performance limitations of the rotorcraft and safety concerns.

The invention discloses an unmanned aerial vehicle trajectory optimization method and device based on deep reinforcement learning and an unmanned aerial vehicle. The method comprises the steps: constructing a reinforcement learning network in advance, and generating state data and action decision data in real time in a flight process of an unmanned aerial vehicle; and taking the state data as input, the action decision data as output and the instantaneous energy efficiency as reward return, optimizing strategy parameters by utilizing a PPO algorithm, and outputting an optimal strategy. The device comprises a construction module, a training data collection module and a training module. The unmanned aerial vehicle comprises a processor, and the processor is used for executing the unmanned aerial vehicle trajectory optimization method based on deep reinforcement learning. The method has the capability of carrying out autonomous learning from accumulated flight data, can intelligently determine the optimal flight speed, acceleration, flight direction and return time in an unknown communication scene, concludes a flight strategy with the optimal energy efficiency, and is higher in environment adaptability and generalization capability.

The invention relates to a genetic-algorithm-based trajectory planning optimization method for a mobile mechanical arm. According to the technical scheme, the method comprises the following steps of first establishing a forward kinematic model and an inverse kinematic model of a multi-degree-of-freedom mobile mechanical arm; then fitting a joint trajectory by adopting a composite curve of a quartic polynomial mathematical model and a quintic polynomial mathematical model, and calculating solutions of the corresponding mathematical models according to a linear constraint equation; next selecting a trajectory optimization target according to the principles of shortest motion time, minimum spatial motion distance and less than or equal to maximum set joint torque of the mobile mechanical arm; and finally globally optimizing the optimization target by utilizing a genetic algorithm to obtain an optimal trajectory curve of an end actuator of the mechanical arm. According to the method, the trajectory planning efficiency and the tracking accuracy of the mechanical arm are improved, and the problems of real-time trajectory planning of the mobile mechanical arm and trajectory planning optimization and control of the mechanical arm in an uncertain environment are also solved; and the trajectory planning optimization method for the mobile mechanical arm is effective.

A method for controlling an autonomous vehicle includes obtaining information describing a roadway; defining a plurality of layers along the roadway between a starting position and a goal position, each layer having a first width, and each layer having a plurality of nodes that are spaced from one another transversely with respect to the roadway within the first width; and determining a first trajectory from the starting position to the goal position, by minimizing a cost value associated with traversing the layers. Determining the first trajectory includes, for each layer, determining layer-specific weighting factors for each of a plurality of cost components, based on information associated with the respective layer, and determining, for each node of the respective layer, a cost for travelling to one or more of the nodes in a subsequent layer based on the plurality of cost components and the layer-specific weighting factors.

The invention discloses spray gun locus optimization method of a spray robot on a complex curve surface, comprising: slicing the complex surface, considering each slice as a plane, designing locus of each slice by using plane spray gun locus optimization method; according to relative position relationship between two slices boundary and juncture locus, discussing juncture spray locus optimization according to different condition, optimizing the juncture locus by using spray locus subsection method; considering spray gun locus optimization composition problem as country mail carrier problem (ORPP), representing ORPP by using Hamiltonian graphic method, performing optimum combination of spray gun locus of each slice by using modified genetic algorithm, and realizing spray locus optimization on a large area curve surface. The invented method is provided with practicability, and is a robot auto spray method for workpieces with a surface of complex curve surface. By using the invented method, the work efficiency of the spray robot is improved, the spray quality is promised, and the paint is saved.

The invention discloses an automatic driving lane changing preparation and execution integrated trajectory planning method. The method comprises the following steps: establishing a motion trajectory model of a lane changing vehicle in a lane changing preparation process; introducing a cubic polynomial to establish a trajectory equation of the lane changing vehicle in a lane changing execution process; establishing a safe distance model and a safe speed model in the lane changing preparation and lane changing execution processes; and establishing an integrated trajectory optimization model, andoptimizing the time and the acceleration in the lane changing preparation and execution processes to obtain a most trajectory meeting safety, efficiency and comfort requirements. An integrated lane changing trajectory set is established according to the vehicle motion characteristics, a safe lane changing trajectory set meeting lane changing safety requirements is chosen by using safety constraints, and finally the trajectories are optimized by considering the lane changing comfort and efficiency to obtain the optimal integrated trajectory meeting safety, comfort and efficiency requirements.The optimal lane changing trajectory planned in the invention has a high service level, and ensures that passengers have high comfort experiences and high efficiency experiences.

The invention relates to an unmanned aerial vehicle trajectory optimization and resource allocation method. The method comprises the following steps: S1, modeling an unmanned aerial vehicle trajectoryoptimization and resource allocation problem based on an unmanned aerial vehicle base station system; S2, planning an unmanned aerial vehicle trajectory optimization and resource allocation problem to ensure the fairness of unmanned aerial vehicle service for each user; S3, jointly optimizing the bandwidth and the power of the unmanned aerial vehicle under the condition of giving the track of theunmanned aerial vehicle; S4, optimizing the trajectory of the unmanned aerial vehicle under the condition of given bandwidth and unmanned aerial vehicle power; S5, comprehensively considering the S3and S4, and solving the problems of unmanned aerial vehicle trajectory optimization and resource allocation. According to the invention, the service quality of edge users, users blocked by obstacles and the like can be improved; bandwidth, power distribution and flight path of the unmanned aerial vehicle are optimized at the same time, so that the bandwidth, the power distribution and the flight path of the unmanned aerial vehicle are matched with one another, and communication efficiency of a communication system is greatly improved under limited communication resources.

An target vertical trajectory for a flight plan is produced using aircraft performance characteristics taking into account only the altitude constraints, but ignoring any speed and time constraints. The target vertical trajectory is evaluated for violations of altitude, speed, and time constraints and on the basis of other criteria. An alternative vertical trajectory is generated by randomly changing parts of the target vertical trajectory, and this alternative is likewise evaluated. If the child vertical trajectory has a more robust evaluation, it becomes to new target vertical trajectory; otherwise the previous target vertical trajectory remains in place. The alternative vertical trajectory generation process is performed repeatedly and over time the target vertical trajectory evolves toward an optimum trajectory solution.

The invention discloses a borehole stability evaluation method for a highly-deviated well. The borehole stability evaluation method includes steps of adopting interval transit time and density logging information to obtain formation pressure Pp, and determining the magnitude and direction of ground stress and formation rock strength parameters; converting the obtained ground stress into borehole stress of deviated well coordinates; determining the criterion of borehole instability judgment of the highly-deviated well; establishing a variation rule between borehole instability and deviation and azimuth angles thereof, and formulating borehole stability countermeasures of the highly-deviated well. In the borehole stability evaluation method, a set of complete and assorted mechanical evaluation methods combined with geology, well drilling, logging, core, laboratory tests and mechanics analysis methods takes shape, mechanical mechanism of borehole stability of the highly-deviated well can be evaluated, so that reliable basis is provided for determination of platform displacement optimization, borehole track optimization and a safe drilling fluid density window determination of the highly-deviated well.

The invention provides a multi-intelligent-vehicle intersection traffic coordination control method in a vehicle-road coordination environment. The method comprises the following steps: 1, establishing a traffic right division model; 2, establishing a vehicle trajectory and signal timing overall optimization model; 3, establishing an overall control model according to the passage right division model and the vehicle track and signal timing overall optimization model. According to the multi-intelligent-vehicle intersection traffic coordination control method in a vehicle-road coordination environment, through establishing traffic right distribution model, a signal timing model and a vehicle track optimization model, a set of theoretical algorithm used for intersection overall control in thevehicle-road cooperation environment is established, quantitative analysis is further carried out on the control effects of different control algorithms under different conditions by setting four sets of simulation experiments, and the significant effect of the algorithm provided by the invention on intersection overall control in the vehicle-road cooperation environment is verified.

A goal programming based hypersonic flight vehicle re-entry trajectory online optimization method comprises the steps of giving a kinetic model of hypersonic flight vehicle re-entry process, including height, latitude, longitude, course angle and trajectory angle kinetic equations; calculating a re-entry corridor within a speed-height plane, setting an attack angle alpha as a segmented linear function and using two speed values V1and V2 as a segmentation points to obtain the attack angle alpha; respectively designing a longitudinal trajectory and a transverse trajectory. The goal programming based hypersonic flight vehicle re-entry trajectory online optimization method is applicable to online trajectory generation of the hypersonic flight vehicle re-entry process, is feasible and effective for solving the problem of the re-entry trajectory optimization under the condition that a terminal point position is known, can generate a feasible trajectory within short time, meets quick and real-time trajectory optimization, can further make the obtained trajectory to meet all constraint conditions within a certain error accuracy range and ensures trajectory feasibility.

The invention discloses a reentry vehicle trajectory optimization method based on a variable-centroid rolling control mode. The reentry vehicle trajectory optimization method based on the variable-centroid rolling control mode is used for solving the technical problem that the robustness of an existing reentry vehicle trajectory control method is poor. According to the technical scheme, by establishing a one-dimensional variable-centroid rolling control reentry vehicle mathematical model, a one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model is established, and the one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model is solved. According to the method, all kinds of constraints in the reentry process of a reentry vehicle are taken into consideration, by introducing control constraints and one-dimensional variable-centroid control ability constraints, the one-dimensional variable-centroid rolling control reentry vehicle trajectory optimization model with a guidance system matched with a control system is established, meanwhile, the trajectory optimization model is solved through a simulated annealing algorithm, and thus the local convergence defect of a classic optimization method is overcome, a nominal trajectory suitable for the one-dimensional variable-centroid rolling control mode is acquired while process constraint and boundary constraint conditions are met, and the robustness of the guidance and control systems is improved.

The invention discloses a cooperative optimization and control method for a mixed traffic flow of an expressway. The cooperative optimization and control method for the mixed traffic flow of the expressway is applied to vehicle optimal control under a merging scene of a ramp of the expressway. The cooperative optimization and control method for the mixed traffic flow of the expressway comprises the steps of predicting a vehicle track by using a microscopic vehicle following model; determining an optimization and control target vehicle; determining an optimization track section of a controllable vehicle; controlling a decision point and an admissible state set under each time; and carrying out optimization and control on the vehicle track. The cooperative optimization and control method forthe mixed traffic flow of the expressway has the beneficial effects that a microscopic traffic flow simulation environment based on the microscopic vehicle following model is established, and trafficeffects of different traffic states and different automatic driving vehicle permeability are analyzed; a brand-new cooperative merging model is proposed on the basis of the microscopic following model, traffic characteristics, geometric constraint and security constraint of the expressway are considered, and a cooperative merging problem is concluded into an optimization and control problem aboutdiscrete time state constraint; and a solving method based on dynamic programming is proposed to effectively solve the problem.

The invention discloses an unmanned aerial vehicle flight time optimal real-time trajectory optimization method capable of ensuring convergence, and belongs to the field of trajectory optimization. According to the method, an unmanned aerial vehicle kinematics model is established under the consideration of gravity action, speed and acceleration factors, and a three-dimensional dimensionless motion equation is established. Constraint conditions of speed and control quantity are established according to specific requirements of obstacle avoidance flight of the unmanned aerial vehicle, and the minimum time is selected as an optimization target to establish an optimal control problem P0 of flight path planning of the unmanned aerial vehicle. Nonlinear dynamics in the problem P0 is transformedinto linear dynamics to obtain a fixed initial and end time trajectory optimization problem P1; and the P1 problem is relaxed into an approximate convex optimization problem P2 through convex relaxation, so that the robustness and robustness of real-time solving of the unmanned aerial vehicle are improved. And the problem P2 is discretized to form a second-order cone programming problem P3, and asecond-order cone programming problem P3 is solved iteratively for finite times to obtain an optimal solution, namely the optimal flight time trajectory of the unmanned aerial vehicle. The task response capability of the unmanned aerial vehicle can be further improved.

Disclosed is a wirelessly-controlled six-degree-of-freedom mechanical arm teaching system. An APP at the PC end is installed on a Windows computer of a user. The APP at the PC end comprises an interactive interface module, an APP master control module, a trajectory optimization module and a control file generation module which are sequentially connected with one another. The control file generation module downloads control code files into one or more working mechanical arms through a file transfer protocol (FTP), and the working mechanical arms are used for completing optimized teaching work. A data acquisition unit is connected with an MCU master control module, and the MCU master control module is in wireless connection with the PC end through WiFi. The data acquisition unit is in both-way communication connection with six absolute type encoders of a teaching mechanical arm joint through an RS485 circuit, and the six absolute type encoders correspond to the six degrees of freedom of each mechanical arm separately. The data acquisition unit outputs data to the MCU master control module, and the MCU master control module outputs the data to the PC end. The PC end outputs operational instructions to the MCU master control module, and the MCU master control module outputs the operational instructions to the data acquisition unit. The data acquisition unit, the teaching mechanical arms and the MCU master control module are all connected with an external power module.

The invention discloses a mechanical arm space trajectory optimization method for optimal time under multiple constraint conditions. The mechanical arm space trajectory optimization method comprises the steps that firstly, path points of a joint space are generated according to path points in a Cartesian coordinate system of a mechanical arm; secondly, multiple spline interpolation functions of all joints from a task start point to an end point are generated according to the path points of the joint space, and adaptability functions of all the joints are generated according to the constraint conditions; and thirdly, the movement time of all the joints is optimized through an improved Chaos particle swarm algorithm, and an optimal solution is finally obtained. According to the mechanical arm space trajectory optimization method for the optimal time under multiple constraint conditions, multiple constraint conditions such as the velocity and the acceleration of all the joints of the mechanical arm are comprehensively taken into account, improvement is conducted on the basis of the particle swarm algorithm, a particle swarm can be switched between a chaos state and a stable state, thestates of all particles are detected, the particles can achieve separation in time when the particles reach the local extremum, and then the diversity of the whole particle swarm is improved. By means of the method, the movement time of the mechanical arm can be effectively shortened under the multiple constraint conditions, and the working efficiency is improved.

The invention is applicable to the technical field of robot polishing, and provides a robot polishing control system. The system comprises a linear laser sensor, a three-dimensional model constructionmodule, a to-be-polished area generation module, a trajectory generation module, a simulation module and a trajectory optimization module; the linear laser sensor scans a to-be-polished workpiece andobtains structural parameters of the to-be-polished workpiece; the three-dimensional model construction module constructs a three-dimensional model of the to-be-polished workpiece; the polishing areageneration module obtains a three-dimensional model of a to-be-polished area on the basis of a CAD model; the trajectory generation module generates a polishing trajectory of the to-be-polished areaand polishing force of corresponding trajectory points; a three-dimensional robot conducts polishing simulation on the basis of the generated polishing trajectory and the generated polishing force ofthe corresponding trajectory points; the trajectory optimization module optimizes the generated polishing trajectory and the generated polishing force of the corresponding trajectory points, and a robot controller controls the robot to conduct polishing on the basis of the optimized polishing trajectory and the optimized polishing force of the corresponding trajectory points. The polishing trajectory is automatically planned based on the automatically-obtained model of the to-be-polished area, the end position of the robot is corrected based on force control in the process of planning the polishing trajectory, the polishing precision can be improved, and the system can be suitable for polishing of complex workpieces.

The invention belongs to the technical field of vehicle obstacle avoidance control methods, and discloses a vehicle obstacle avoidance trajectory planning and tracking control method. The vehicle obstacle avoidance trajectory planning and tracking control method comprises the steps of: decomposing an obstacle avoidance process into trajectory planning based on optimization and trajectory trackingcontrol based on model predictive control, establishing a trajectory optimization problem aiming at time optimum and comprising a plurality of constraints based on a three-section sinusoidal curve oflateral acceleration, and acquiring the optimal trajectory of obstacle avoidance through optimization solution; and establishing a two-degree-of-freedom vehicle control model, taking path tracking performance and the optimal steering angle as cost functions, and designing the optimal trajectory tracking controller based on a model predictive control idea, so as to achieve effective obstacle avoidance.

The invention discloses a horizontal drilling real-time seismogeology comprehensive guiding method. The method comprises the following steps that (1) three-dimensional prestack time deepened seismic data are explained in a known oil and gas field work zone, and an initial guiding model of a well to be drilled is obtained; (2) lithological, electrical and seismic reflection characteristics of marker beds, a target oil and gas layer and adjacent stratums in the oil and gas field work zone are determined; (3) before a forward drilled well enters the target, the velocity field is updated in real time, and an improved guiding model of the forward drilled well is obtained; (4) when the forward drilled well encounters one marker bed and is about to enter the tarter, the altitude depth of a target-entering point of the forward drilled well is predicted, and trajectory optimization before target entering is conducted; (5) after the forward drilled well enters the target, the velocity field is updated again, and thus the newest guiding model is obtained; and (6) under the guidance of the newest guiding model, a horizontal section guiding is conducted by combining with practical drilling analysis. According to the seismogeology comprehensive guiding method capable of correcting the guiding model in real time, the effects that the horizontal well enters the target layer accurately and efficiently penetrates through the target layer can be guaranteed.

The invention discloses a cutter track generating method based on a potential energy field and energy functional optimization. The cutter track generating method based on the potential energy field and the energy functional optimization comprises an energy functional, boundary conditions and line width constraint conditions. A method of finite elements is used to obtain a numerical approximation computational formula of a cutting track optimization calculating model, wherein the numerical approximation computational formula is based on a triangular discrete grid. An approximate value phi Phi on each node I where the potential energy field template Phi exists is obtained according to the cutter track calculating model. Contour lines of a volcanic vent are sectioned and images are cast on a machining zone omega Omega. Approximate tracks of equipotential contours are formed and smoothing and sampling are performed on the approximate tracks of the equipotential contours. Cutter track contour datum lines which are arranged from the exterior to the interior in an inclined mode are obtained. Linear interpolation is performed among the cutter track contour datum lines and a segment of a spiral cutter track is formed. All spiral cutter tracks are connected to form a spiral track. Curve fitting is performed on the spiral track to form a geometry second order continuous B spline cutter track. The cutter track generating method based on the potential energy field and the energy functional optimization achieves high-speed machining, optimizes cutting force distribution and improves quality of surface machining.

The invention relates to a small celestial body attachment detection descending trajectory optimization method, and belongs to the field of aviation and aerospace. According to the method, an internal spherical harmonic gravitational field model is adopted for estimating gravitational acceleration near a target small celestial body, and a convex optimization algorithm is adopted for solving the optimal control problem. By adopting the internal spherical harmonic gravitational field model for estimating the gravitational acceleration near the target small celestial body, the advantage of being high in computational efficiency is achieved. By adopting the convex optimization algorithm for solving the optimal fuel control problem, the problems that derivation of a indirection method is complicated, and co-state variables are free of physical meaning and not likely to guess are avoided, the derivation step is simple, the computing time is saved, the estimation optimization method is rapid and high in precision, and the obtained result conforms to initial and end state constraint, dynamic constraint and control constraint.