1838 results about "Trajectory planning" patented technology

A temporal controller for mobile robot path planning includes a sensor module for receiving data corresponding to spatial locations of at least one object, and a temporal control module operatively coupled to the sensor module, the temporal control module configured to predict future locations of the at least one object based on data received by the sensor module. The controller further includes a temporal simulation module operatively coupled to the temporal control module, wherein the temporal simulation module configured to use the predicted future locations of the at least one object to simulate multiple robot motion hypothesis for object avoidance and trajectory planning.

The invention discloses a dynamic automatic drive lane-changing trajectory planning method based on real-time environment information. A rollover limitation trajectory vertical coordinate, an optimal trajectory and a collision avoidance trajectory terminus security area are calculated; the relation between the rollover limitation trajectory vertical coordinate and the security area is compared, the positional relation between the optimal trajectory vertical coordinate and the security area is further compared, and then lane-changing decision-making is conducted. According to the dynamic automatic drive lane-changing trajectory planning method based on the real-time environment information, and a polynomial trajectory equation which dose not depend on time is adopted to represent a lane-changing trajectory curve, so that the problem that hypotheses of a speed and an accelerated speed are too strong is avoided; furthermore, collision avoidance algorithm and rollover prevention algorithm which are based on reaction time are introduced to guarantee security of lane-changing; then the optimal trajectory in a safe trajectory cluster is determined through real-time speed adjusting; and finally, an optimal lane-changing trajectory of real-time dynamic state is output through a trajectory generation module to guide an autonomous vehicle to complete a lane-changing behavior, and therefore a set of complete dynamic autonomous vehicle lane-changing trajectory planning module is built.

A data-driven prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment includes: generating a first suggested trajectory for an autonomous vehicle; generating predicted resulting trajectories of proximate agents using a prediction module; scoring the first suggested trajectory based on the predicted resulting trajectories of the proximate agents; generating a second suggested trajectory for the autonomous vehicle and generating corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and outputting a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

The invention discloses a method for manufacturing a five-axle linkage control three-dimensional printing device. The device is used for realizing an ink printing function on the surface of any three dimensional entity. The device mainly comprises a control system, a mechanical motion structure and a printing system, wherein the control system is based on five-axle linkage for motion control, which realizes motion control and printing control synchronously and the functions of three-dimensional computer-aided design and computer-aided process, and also realizes the functions of five-axle linkage motion trajectory planning and synchronous color resolution required by three-dimensional printing; the mechanical motion structure adopts a five-axle linkage mechanical structure, which realizes the functions of linkage of three linear motions and two rotary motions; and the printing system adopts four spray nozzles with independent telescopic function, which partly realizes the CMYK (Cyan, Magenta, Yellow and Black) four-color ink printing function.

The invention provides a composite three-dimensional point laser measurement system and a measurement method, comprising three-dimensional scanning and three-dimensional detection. Normal optical scanning is adopted so as to obtain the profile information of the article quickly and establish a three-dimensional model; motion trajectory planning is carried out by the profile data; and a point laser probe is guided to carry out more precise measurement so as to obtain the three-dimensional point cloud data of higher precision and higher quality. The three-dimensional non-contact detection to the characteristic position, appointed section line and integer of the workpiece is obtained further on the basis of comparing the point cloud and model data. The system and the method have the advantages that the non-contact measurement can obtain the point cloud of good quality and high precision, the article can be positioned freely, precise clamping devices are not needed, the measurement speed is quick, the process is automatic and the measured article has wide applicable range.

The invention provides an automatic spraying system based on point cloud and image matching. The automatic spraying system comprises a three-dimensional scanning module, an automatic trajectory planning module, a visual matching module and a spraying module. The three-dimensional scanning module is used for scanning a spraying object and acquiring a point cloud model according to scanned three-dimensional point cloud data; the automatic trajectory planning module is used for planning spraying trajectories in a point cloud space; the visual matching module is used for acquiring a transformational relation between a point cloud coordinate system and a spraying robot coordinate system; the spraying module is used for automatically spraying the spraying object. The automatic spraying system has the advantages that an algorithm is planned automatically according to a robot spraying path of the point cloud coordinate system, the point cloud coordinate system is correlated with the robot coordinate system according to the cloud point and image matching algorithm, and accordingly, automatic spraying of the spraying object is realized; on the basis of guaranteeing spraying efficiency, the spraying quality is improved greatly, calculation quantity for trajectory planning is reduced, and trajectory planning quality is improved.

The parallel kinematic machine (PKM) trajectory planning method is operable via a data-driven neuro-fuzzy multistage-based system. Offline planning based on robot kinematic and dynamic models, including actuators, is performed to generate a large dataset of trajectories, covering most of the robot workspace and minimizing time and energy, while avoiding singularities and limits on joint angles, rates, accelerations and torques. The method implements an augmented Lagrangian solver on a decoupled form of the PKM dynamics in order to solve the resulting non-linear constrained optimal control problem. Using outcomes of the offline-planning, the data-driven neuro-fuzzy inference system is built to learn, capture to and optimize the desired dynamic behavior of the PKM. The optimized system is used to achieve near-optimal online planning with a reasonable time complexity. The effectiveness of the method is illustrated through a set of simulation experiments proving the technique on a 2-degrees of freedom planar PKM.

A prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment is configured to: receive training data and ground truth data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, generating a proposed trajectory for the host vehicle, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle based on the proposed host vehicle trajectory, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.

The invention provides an unmanned aerial vehicle trajectory planning method based on EB-RRT. The method comprises the steps that grid partitioning is carried out on a map environment; a node xnearst nearest to a random point in existing nodes is found; an insertion point xnew is calculated according to the step length; if the sum of the distance between a root node to xnew and the Euclidean distance between xnew and the end is not greater than the length of the current optimal path, whether the xnew point is in an obstacle is detected; if not, the surrounding environment information of xnearst is collected, and a new insertion point xnew is randomly sampled in the surrounding free area; xnew is inserted into a tree; the nearby node set of xnew is traversed and found in the corresponding grid, and the path of the nearby nodes is optimized; connection detection is carried out on two trees into which the xnew point is inserted; if not, two trees are exchanged, and random points continue to be sampled; if so, a feasible path is found, and downsampling is carried out; and a Bessel cubic interpolation algorithm is used to optimize the new path. The unmanned aerial vehicle trajectory planning method provided by the invention has the advantages of high convergence speed, good flexibility, high running efficiency and good practicability.

The invention discloses a robot cartesian space trajectory planning method. The method includes establishing a connecting rod coordinate system and obtaining a forward kinematic equation through a kinetic modeling analysis method; solving the rotating angles of a master control joint and a middle joint according to the vector geometric property and trajectory planning requirement of the robot; seeking a relation equation including introduced variables and solving the rotating angle of the corresponding joint by means of the kinetic modeling analysis method and the solved joint rotating angle; determining whether the pose position can be reached through a vector geometric method when the trajectory planning is carried out in a task space with obstacles; and planning the continuous time variant attitudes of coupled position information to complete the planning tasks. According to the method, extraneous roots can be prevented, efficient solutions can be screened and matched, strange paths can be effectively avoided, and meanwhile, the defects of complex end trajectory planned by the joint space can be prevented and optimized.

The invention provides a trajectory planning method, system and equipment and a storage medium. The method includes the following steps of: analyzing environmental information corresponding to the environment where a vehicle is located, and obtaining a driving scene where the vehicle is located; according to the driving scene where the vehicle is located, correspondingly selecting a trajectory planning mode with performance priority or efficiency priority as a target trajectory planning mode; according to the target trajectory planning mode, determining a path from the starting position of thevehicle to a target position, and determining a speed curve from the starting position of the vehicle to the target position; and combining the determined path and speed curve to obtain a trajectoryused by the vehicle from the starting position to the target position. The scheme of the invention can be adapted to planning the trajectory of automatic driving of the vehicle in different driving scenes.

The present invention provides an intersection condition-orientated unmanned vehicle trajectory planning method based on the Bezier curve and the VFH algorithm. The method includes the following steps that: 1) the starting point pose P0 (x0,y0,theta0) and destination point pose P3 (x3,y3,theta3) of current trajectory planning are acquired; 2) a trajectory cluster A1 from the starting point pose P0 (x0,y0,theta0) to the destination point pose P3 (x3,y3,theta3) is generated through adopting a three-order Bezier curve model; 3) the trajectory cluster A1 is screened according to a maximum curvature constraint, so that a trajectory cluster A2 is obtained, collision detection is performed on A2, so that a collision-free trajectory cluster A3 is obtained; 4) if A3 is not empty, an optimal trajectory is selected from A3 according to a trajectory smoothest principle and is outputted to a control layer, and the method is terminated, otherwise, the method shifts to step 5; 5) a movement region in the original VFH algorithm is improved, so that a fan-shaped movement region is built; 6) obstacle information is utilized to establish a grid map; 7) the fan-shaped movement region is divided into a plurality of fan-shaped regions, and whether an obstacle exists is judged; 8) the Bezier curve is used in combination, and optimal trajectory points are selected; and 9) with a discrete point set generated in the step 8 adopted as control points, a B-spline curve is generated, and the B-spline curve is adopted as the final trajectory of an unmanned vehicle.

The invention discloses a gait planning method for walking of a biped robot along a slope, and belongs to the technical field of robots. The method contains two core theories, namely, non-orthogonal decomposition and synthesis of a three-dimensional linear inverted pendulum and gait planning based on a biped long linear inverted pendulum. The method comprises the steps of gait parameter configuration, non-orthogonal decomposition of a three-dimensional linear inverted pendulum, foot trajectory planning based on three times of spline interpolation, centroid trajectory planning of a sagittal plane and a coronal plane based on a biped long linear inverted pendulum, non-orthogonal synthesis of the centroid trajectories of the sagittal plane and the coronal plane, and solving of joint trajectories of a robot based on inverse kinematics. By adopting the method of the invention, stable walking of a biped robot along all directions of a slope can be effectively achieved. The method is universal, simple in algorithm and high in practicality.

Disclosed is a method for constructing a multi-mode environmental map in a three-dimensional environment. An unmanned vehicle is operated for many times in a mapping pattern, and different key frame coordinate sequences are obtained during each operation. Geographical proximity between different key frame coordinates is calculated on the basis of a Euclidean distance so as to identify cross joints of key frame sequences during different operations, these cross joints serve as nodes of a topological map, and multiple trajectories are connected together to form a whole map. By executing route planning based on a heuristic map search algorithm on the topological map, a route cross joint sequence can be obtained, original dense key frame coordinates can be obtained by indexing through the route cross joint sequence, and these coordinates serving as trajectory planning results are input to an unmanned vehicle control execution system, so as to realize position tracking of the unmanned vehicle.

The invention belongs to the field of intelligent transportation, and provides an automatic driving lane change trajectory planning method based on quadratic form planning and a neural network. The method provided by the invention comprises the steps of: obtaining driving information of a lane change vehicle and surrounding vehicles by using an information sensing module; providing, by a lateral deviation recommendation module, a lateral deviation value based on the vehicle driving information so as to determine starting point and ending point position information of the lane change vehicle; calculating, by a path planning module, a static lane change path in a plane coordinate system of the lane change vehicle by using the vehicle driving information and the lateral deviation as input; and finally, providing, by a trajectory planning module, a time varying change law of the lane change vehicle and the surrounding vehicles to complete the target of lane change process planning. By adopting the automatic driving lane change trajectory planning method provided by the invention, under the premise of ensuring the safety of the lane change vehicle, the movement trajectories of the lanechange vehicle and the surrounding vehicles are comprehensively considered, and fast solution is achieved by using the quadratic form planning to improve the speed and comfort of the lane change process, thereby satisfying the requirements of automatic driving for the lane change sub-task optimization solution fastness.

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 discloses a track teaching and planning method of a master-slave mode multi-robot cooperative system. The method comprises the steps of: classifying the cooperative movement of the multi-robot system into a coupling movement and a superposition movement according to the relative movement modes between the tail end poses of the cooperative robots, and deducing the constraint relation between the tail end poses of the robots according to the two relative movement modes; and determining the track teaching steps and teaching information of the multi-robot cooperation according to the constraint relation, and converting the cooperative movement tack planning problem of the multi-robot cooperative system into Cartesian space track planning problem of a plurality of single robots so as to finish the track teaching and planning task of the multi-robot cooperative system. The track teaching and planning method disclosed by the invention can be applied in multiple service processes meeting the movement constrain, for example, partial cooperative movement in complex assembly task, carrying of large-size workpiece and non-fixture welding process, and the like, so that the track teaching and planning method has an extensive application prospect.

In the control method for mobile parallel manipulators, kinematic singularity and redundancy are solved through joint limits avoidance and manipulability criteria. By taking the MPM self-motion into consideration due to its redundancy, the inverse kinematic is derived using a hybrid neuro-fuzzy system, such as NeFIK. The discrete augmented Lagrangian (AL) technique is used to solve the highly nonlinear constrained multi-objective optimal control problem. An adaptive neuro-fuzzy inference system (ANFIS)-based structure (based on the result of the AL solution) is used to solve the online trajectory planning of the MPM.

An intelligent control method for vertical recovery of carrier rockets based on deep reinforcement learning is disclosed. A method of autonomous intelligent control for carrier rockets is studied. Theinvention mainly studies how to realize attitude control and path planning for vertical recovery of carrier rockets by using intelligent control. For the aerospace industry, the autonomous intellectualization of spacecrafts is undoubtedly of great significance whether in the saving of labor cost or in the reduction of human errors. A carrier rocket vertical recovery simulation model is established, and a corresponding Markov decision-making process, including a state space, an action space, a state transition equation and a return function, is established. The mapping relationship between environment and agent behavior is fitted by using a neural network, and the neural network is trained so that a carrier rocket can be recovered autonomously and controllably by using the trained neural network. The project not only can provide technical support for the spacecraft orbit intelligent planning technology, but also can provide a simulation and verification platform for attack-defense confrontation between spacecrafts based on deep reinforcement learning.

The invention provides a motion trajectory planning method of mechanical arms of a humanoid robot for preventing collision. In the prior art, the collision problem is not solved fundamentally. The method adopts a joint space-based interpolation method to solve the collision problem between the mechanical arms and a table caused by motion trajectory generation of the mechanical arms, and mainly aims at operation of humanoid arms of the humanoid robot oriented to tabletops or objects similar to tabletops. The mechanical arm freedom degree includes three freedom degrees of the shoulder, two freedom degrees of the elbow and two freedom degrees of the wrist. The concrete implementation method comprises under the premise of ensuring completion of target operation at a fixed moment, properly bending the elbow at the collision occurring moment during the motion of the mechanical arms to prevent collision. With such scheme, the mechanical arms can move without collision while realizing high flexibility and large operation space.