41 results about "Motion optimization" patented technology

The invention discloses a jumping robot and a motion optimization method adopting inertia matching. The jumping robot consists of a matrix operation controller, an aluminum plate body, a joint drive motor and a motion control algorithm with inertia matching. The system uses the jumping robot as a research object; the jumping motion is divided into three phases of a standing phase, a soaring phase and a falling collision phase; on the basis of variable constraint dynamics, the system establishes a standing phase dynamics equation by using a space floating base, performs optimization research on jumping gesture and load matching by using the inertia matching and direction manipulability and uses five polynomial to plan jumping motions. The simulation and experiment show that when the inertia matching of the jumping robot is maximal, the reaction impulse of the ground is maximal, and the jumping performance is optimal; the jumping height and the inertia matching are in direct proportion; and when the inertia matching is maximal, the jumping gesture of the robot and the load matching are optimal. The inertia matching is an effective jumping motion optimization method.

The invention relates to a moving posture monitoring and guiding method and device based on multiple cameras. The method comprises the following steps: acquiring moving images and/or video data of atleast one target sporter through a plurality of cameras; recognizing a target sporter from the moving image and/or the video data through a posture recognition algorithm, and outputting a human body posture graph required by moving posture monitoring; reconstructing human body three-dimensional posture information of the target sporter through a three-dimensional reconstruction algorithm based onthe human body posture diagram; carrying out skeleton registration on the target sporter and the reference person by utilizing the posture key nodes in the three-dimensional space; comparing the humanbody three-dimensional posture information of the target exerciser after bone registration with the human body three-dimensional posture information of the reference exerciser at a certain moment orwithin a preset time period; evaluating the action completion degree and quality of the target sporter based on the comparison result; and providing feedback to the target sporter based on the evaluation result, the feedback including whether the action reaches the standard and/or a motion optimization suggestion.

The invention provides a seven-degree-of-freedom mechanical arm limiting optimization method based on position-level inverse kinematics, and relates to a seven-degree-of-freedom mechanical arm limiting optimization method. The method aims to solve the problems that an existing numerical solution cannot obtain a closed solution, and final-state self-motion exists; and an analytical solution cannotbe used for offset configuration, and motion optimization cannot be realized. The method comprises the steps that firstly, an analytical solution of seven-degree-of-freedom mechanical arm inverse kinematics is obtained based on a parametric solving method for fixing a certain joint angle; then, the fixed joint angle parameter is used as input, joint limiting is used as an optimization index, and an optimal control problem is established; then, a constrained problem is converted into an unconstrained problem based on a Lagrangian multiplier method; and finally, the optimal joint angle parameteris solved based on a Newton iteration method, and seven joint space trajectories considering joint limiting optimization are obtained by giving an initial configuration, an expected tail end pose anda Cartesian path planning. The method is used for limiting optimization of a seven-degree-of-freedom mechanical arm.

The invention provides a biped walking simulation evaluation system and method of a robot based on six-degree-of-freedom legs. The system comprises a biped robot model and a gait planning algorithm, the biped robot model-1 and the gait planning algorithm-2 are input of the simulation evaluation system, the biped robot model contains the shape and dynamics parameters of the robot, and the gait planning algorithm can be used for planning motion trajectories of more than 20 joints of the whole body according to expected staying footprints; the simulation evaluation system outputs a simulation evaluation result used for evaluating the robot structure and the performance of the gait planning algorithm. Through a computer simulation mode, the purpose of omnidirectional walking motion optimization with more complex parameters and more involved factors is achieved.

A compiler can perform aggressive code motion optimization by respecting value dependence of safety values inserted into the intermediate representation of a computer program. In one embodiment, the present invention includes converting a computer program into an intermediate representation, the intermediate representation containing at least one safety check ensuring the safety of at least one dangerous instruction. In one embodiment, the invention further includes defining a safety value in the intermediate representation as the safety check and including the safety value as a safety argument of the dangerous instruction. In one embodiment, it is determined that the safety check is redundant. In response, in one embodiment, the invention includes updating the safety argument of the dangerous instruction, and eliminating the safety check from the intermediate representation during the safety check elimination optimization. Other embodiments are described and claimed.

Disclosed herein are a humanoid robot and a control method thereof. The humanoid robot controls robot parts performing main motions having high relevance with respect to a commanded action to the humanoid robot such that these robot parts move along optimized motion trajectories generated through motion optimization in consideration of robot dynamics, and controls robot parts performing remaining motions having low relevance with respect to the commanded action such that these robot parts move along predetermined motion trajectories corresponding to the commanded action, thereby simplifying optimization of whole body motions of the humanoid robot while performing the commanded action maximally similarly to a real human action.

The invention discloses a general method for machining the complex curved surface of a non-spherical cutter in the multi-axis-linkage CNC manner. The method comprises the steps of (1) designing the curved-surface generating motion of a cutter relative to a workpiece: firstly, the curved surface of the cutter is described based on a vector function having continuous third-order partial derivatives, and then an envelope surface equation formula for the curved surface of the cutter is obtained with boundary conditions taken into consideration; secondly, a motion optimization functional extremum model formula of the cutter relative to the workpiece and having a minimum machining error, and a motion optimization functional extremum model formula of the cutter relative to the workpiece and having a maximum machining line width are obtained; finally, the above functional extremum model formulas are solved to respectively obtain a motion of the cutter relative to the workpiece at a given machining line width and a minimum curved-surface machining error, and a motion of the cutter relative to the workpiece at a maximum machining line width and a given limit error; (2) realizing the curved-surface generating motion of the cutter relative to the workpiece on a specific machine tool. According to the technical scheme of the invention, the machining accuracy and the machining efficiency of the curved surface are improved through fully developing the machining potential of the multi-axis-linkage CNC.

A robot collision avoidance motion optimization technique using a distance field constraint function. CAD or sensor data depicting obstacles in a robot workspace are converted to voxels, and a three-dimensional binary matrix of voxel occupancy is created. A corresponding distance map matrix is then computed, where each cell in the distance map matrix contains a distance to a nearest occupied cell. The distance map matrix is used as a constraint function in a motion planning optimization problem, where the optimization problem is convexified and then iteratively solved to yield a robot motion profile which avoids the obstacles and minimizes an objective function such as distance traveled. The distance field optimization technique is quickly computed and has a computation time which is independent of the number of obstacles. The disclosed optimization technique is easy to set up, as it requires no creation of geometry primitives to approximate robot and obstacle shapes.

The invention relates to the field of redundant robot motion control research, in particular to a motion optimizing method for a redundant degree-of-freedom robot. The motion optimizing method comprises the steps that a gradient projection method is adopted as the basis, and a joint angle limiting position index and an operability index are adopted for optimizing the gradient projection method. The technical problems that in the prior art, existing gradient projection methods are poor in redundant degree-of-freedom robot inverse kinematics solution optimizing effect, and accumulated errors canbe generated are solved. The problem that the redundant degree-of-freedom robot inverse kinematics solution optimizing effect is poor is solved. The motion optimizing method has higher practicabilityfor the redundant mechanism inverse kinematics solution method, and the robot can obtain the more ideal joint space optimizing effect, the higher position resolving precision and smaller motion tracking errors.

The invention discloses a motion optimization based self-instruction generating method for imaging satellite, a method of converting multiple meta-tasks into on-satellite manipulation-level instructions. According to the method, firstly, based on the motion information equipped to the meta-tasks and the timing sequence relationships among the meta-tasks and through the use of the greedy algorithm, the same type of motions of opening and closing the machine between two adjacent meta-tasks are maximized. Therefore, the execution complexity of software is reduced; the motion sequence of the satellites is effectively planned. And according to the motion sequence and the working state of the current satellite's equipment (for instance, sequestration uses backup to save, digital transmission servo uses the original, and etc.), the corresponding manipulation-level instructions are specified so as to effectively make the satellites more operational, achieve better efficiency and provide technical support to enable the single orbit of agile satellites to complete multiple tasks. In addition, according to the method, abstract definitions are made between the meta-tasks and their corresponding motion information as well as between the timing sequence relationships of the meta-tasks, which allows a user to define themselves. Therefore, the method is very flexible and universal and can be applied to various remote sensing satellites.

The invention discloses a non-contact emotional recognition method based on a dual-mode sensor, wherein the non-contact emotional recognition method comprises the following steps: obtaining vital signsignals from echo signals collected by radar sensors, and extracting breathing signals and heartbeat signals from the signals; selecting a human face region from video images collected by video sensors, and obtaining the heartbeat signals and optical flow vector signals according to the human face region; for the heartbeat signals, carrying out heartbeat optimization treatment based on a light intensity method; based on the optical flow vector signals, carrying out body motion optimization treatment on the breathing signals obtained by the radar sensors; for the optimized heartbeat and breathing signals, carrying out characteristic extraction; carrying out characteristic selection on heartbeat characteristics and breathing characteristics, and establishing an emotion recognition model according to the screened characteristics; and according to the emotion recognition model, recognizing the emotion to be recognized. The non-contact measurement not only cannot introduce discomfort, butalso can reduce measurement error, and has the advantages of high recognition accuracy, good robustness and wider applicability.

A method of analyzing data obtained from sensors 200 worn on the body of an athlete. The sensors 200 provide both location and physiological data. The sensors 200 provide data to a server that can analyze the movement of the athlete and compare it to prior movement or optimal movements. The computer program can determine better motions 300 to optimize performance based on the motion 300 data from the sensors 200. The program can also determine physiological changes for the athlete, such as for example increasing leg strength, to optimize the performance. The program can also analyze and predict the trajectory 805 an object based on the data obtained regarding the athlete's movements and capabilities.

The invention provides a terminal state restricted planet type hybrid power system global optimization method, and belongs to the technical field of new energy vehicles. The method comprises the stepsthat before DP backward motion optimization, system boundary calculation is carried out, an dboundary restriction of a state variable of every moment is obtained, so that the boundary restriction isconsidered in the backward iterative optimization process, and electric quantity balance of the system is achieved. By means of a solution of the boundary restriction, no penalty function is needed, and a large amount of debugging work conducted in order to achieve the electric quantity balance is avoided; meanwhile, robustness of an algorithm is no longer affected by model parameters and operation conditions, the amount of calculation and the time cost are lowered, and the efficiency of optimizing the algorithm is significantly improved.

The invention is suitable for the technical field of a computer, and provides a robot motion optimization method and device, computer equipment and a storage medium. The method concretely comprises the following steps: responding to a motion optimization request of a robot, and constructing the initial motion of the robot according to a method of key frame interpolation; according to the initial motion of the robot, constructing an evaluation function; and according to the evaluation function, optimizing the initial motion of the robot by the adaptive evolutionary strategy algorithm of a covariance matrix. The method solves the technical problem of complex motion optimization of the robot, meanwhile the rate of convergence of the used algorithm is high, and the motion optimization effect is significant. The method is applied to robot kicking, and the kicking distance of the robot can be greatly increased.

The invention is suitable for the technical field of motion control and provides a shaft motion control method and device, terminal equipment and a computer readable storage medium. The method comprises steps of a control instruction of a target shaft of shaft motion equipment being acquired; analyzing the control instruction, and determining a motion mode instruction corresponding to the control instruction; and controlling the target axis of the axis motion equipment to move according to the motion mode instruction. According to the method, the terminal equipment analyzes the control instruction and divides the control instruction according to the motion mode instruction in the axis motion control process, and controls the target axis motion according to the corresponding motion mode instruction, and thereby the control logic of the axis motion is optimized, efficiency of the motion control process is improved, and the probability of dangerous faults in the motion control process is reduced.

The invention provides a joint locking failure space manipulator halt optimizing method which comprises the following steps: according to all exercise capacity indicators after standardized processingof a joint locking failure space manipulator, and based on an improved analytic hierarchy process and an entropy method, solving the weight of all exercise capacity indicators to realize comprehensive characterization of exercise capacity of the manipulator, constructing a preferable model of a joint locking failure space manipulator halt configuration, further solving a preferable model of the halt configuration based on the Monte Carlo numerical method, obtaining the optimal halt configuration of the joint locking failure manipulator, then, carrying out motion planning on the manipulator based on a sextic polynomial by taking the halt movement characteristics into consideration, further taking the safety and stability of the manipulator into consideration during the halt process, constructing and solving a space manipulator halt movement optimization model, and finishing halt optimization of the joint locking failure space manipulator. According to the technical scheme, safe and stable halt of the joint locking failure space manipulator can be realized.

The invention provides a passenger flow confluence walking behavior simulation method for a station facility combination part. The method comprises the steps that the layout structure, the geometric dimension and the passenger flow streamline characteristics of a station facility combination part are obtained, and the station facility combination part is divided into a channel straight-going area,a stair area, a confluence area and an exit straight-going area; a classic social force model is used to simulate the walking behaviors of the passenger flow in the passage straight-going area and the exit straight-going area; a three-dimensional social force is introduced to simulate the walking behavior of the passenger flow in the stair area; attraction is introduced, and a turning social force model is used for simulating walking behaviors of pedestrians in a confluence area. According to the method, walking parameters under different scenes are simulated and quantified, the walking stateand the facility area passing rate are constructed to serve as indexes of bottleneck recognition through the relation between time and the layout structure and the geometrical attribute of a channel,and improvement suggestions are provided for confluence area passenger flow motion optimization and facility combination part design.

The invention discloses a point cloud global motion optimization method, and the method comprises the steps that a motion matrix initial value of each visual angle is reconstructed into a low-rank sparse matrix, and then the matrix recovery is carried out; under the condition that any two visual angles are known to move, a universal constraint condition is put forward to be added into an iterationprocess, the iteration frequency is effectively limited, the algorithm efficiency is improved, and the influence caused by random noise is reduced; a Cauchy weight item is added to measure the reliability of pairwise visual angle measurement, the influence of outliers is effectively reduced, and the robustness of the algorithm is improved; the method is suitable for solving an accurate global motion problem of a known multi-view point cloud relative motion initial value and real values of any two view changes. The method aims to solve the problems that a multi-view point cloud global optimization method in dimensional reconstruction excessively depends on registration initial values, robustness is not high and efficiency is low, random noise and abnormal values in initial motion are eliminated, point cloud global motion recovery precision is improved, and a more accurate reconstruction model is obtained.