CN111524412B - System and method for realizing real motion sensing of forklift simulation driving - Google Patents
System and method for realizing real motion sensing of forklift simulation driving Download PDFInfo
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Abstract
The invention provides a system and a method for realizing real motion sensing of forklift simulated driving, which comprise a hardware platform and a software module. The method comprises the following steps: firstly, establishing a motion equation of the actual forklift mass center through the analysis of the forklift kinematics under the typical driving condition of the forklift, and acquiring main motion parameters; secondly, converting the motion parameters of the center of mass of the forklift truck to the driver seat through coordinate transformation; then, converting the motion parameters into motion parameters sensed by the human body through a human body perception model; then, converting the signals into space pose signals of a simulated driving motion platform through a somatosensory simulation algorithm; then, obtaining the elongation and the change equation of each linear driving rod according to the three-dimensional structure and the motion relation model of the platform; and finally, performing joint coupling control on the motion of the three linear driving rods to realize the simulated motion of the platform. The invention can simulate the motion feeling of the forklift in the limited stroke of the movable platform, and creates a vivid driving environment for the driver.
Description
Technical Field
The invention relates to a system and a method for realizing real motion sensing of forklift simulated driving, belongs to the technical field of driving simulation and simulation, and is mainly applied to simulation of real motion and dynamic fidelity in the process of forklift simulated driving.
Background
The forklift belongs to a special vehicle in a field (factory) in special equipment in China, and is widely applied to the carrying and transmission of goods in various industries. However, the forklift is a dangerous vehicle, and safety accidents of the forklift caused by misoperation of a forklift driver frequently occur. However, at present, the traditional master and slave carrying mode of the forklift training mechanism in China is still used for training, and the training mode has the following defects: (1) training efficiency and resource utilization rate are low, and people often operate one person and wait for a plurality of people. (2) The zero-base trainees have serious potential safety hazards in the first real vehicle operation. (3) Training is greatly limited and influenced by factors such as time, field and weather. (4) The real vehicle training cost is high, and the real vehicle training cost comprises forklift use cost, safety protection cost, field use cost, personnel cost and the like. (5) Training standardization is insufficient, and the teaching level and training standard of coaches are not uniform. Therefore, the forklift simulation driving training system with real forklift training experience is researched and developed, and has great social and economic values for standardizing the driving behaviors of a forklift driver, improving the driving safety awareness of the driver, promoting scientific and technological progress and realizing safe production. The key of the forklift simulated driving training system is the realization of on-site immersion in the forklift driving process, and the simulation of the forklift driving process is required to be realized from various senses such as vision, hearing, touch, balance sense, proprioception and the like. The simulation of the motion and dynamic fidelity of the forklift in the driving process is the key and difficult point of the forklift driving simulation training system.
At present, in the aspect of realizing driving simulation body feeling, representative researches mainly comprise two types:
one is a body feeling realization method based on a composite dynamic seat. Such as: in the optimization design, excitation and control of a simulated overload dynamic seat mechanism, Shaohua in 2010 proposes a method for realizing driving simulation by building a simulated overload dynamic seat, wherein the dynamic seat is composed of three motion units, namely a vertical linearly movable integral height adjustment box body, a vertical horizontally movable back plate and a vertical movable bottom plate, and dynamic simulation in the driving process is completed by independently controlling the three motion units and matching with the constraint action of a shoulder belt and a seat belt on a driver; patent application No. 201721210247.1 discloses a seat is felt to 4D body comprises last chair frame, lower chair frame, crank mechanism and drive arrangement, utilizes drive arrangement drive crank mechanism's connecting rod to drive chair frame motion on the seat in the direction of height to drive whole 4D body and feel the seat about from top to bottom random motion in the fore-and-aft direction, realize the simulation of active motion effect.
The two somatosensory simulation chair mechanisms are simple in design and easy to control, and can realize basic dynamic simulation. However, the simulated overload dynamic seat can only realize the simulation of two degrees of freedom of up-and-down vibration and front-and-back translation, and cannot realize the simulation of rotation such as pitching and side tilting, and the simulation is different from the motion feeling of a driver in the real driving process. The 4D motion sensing seat drives the seat through the crank mechanism to realize motion sensing simulation, but the system stability of the crank mechanism is poor, and only the motion and rotation simulation in a single plane can be realized, the motion sensing simulation in a space range can not be realized, and therefore the fidelity of a motion sensing model is not high.
The other type is a motion sensing realization method based on a multi-degree-of-freedom motion platform. Such as: patent application No. 201710015660.0 discloses a six-degree-of-freedom parallel motion platform flight simulator and a flight simulation method, wherein six identical hydraulic servo cylinders are adopted to drive a servo platform (cabin), the platform can complete the motion in six degrees-of-freedom directions under the driving of the hydraulic cylinders, and the three-dimensional scene dynamic flight driving simulation is realized through the accurate position closed-loop control of the hydraulic cylinders; patent application No. 201710108412.0 discloses a fork truck operation training simulator specially used for trainees training and examination, its hardware equipment comprises simulation cockpit, operation control system, instrument system, multimedia computer and sound system, teacher's control cabinet etc. software system includes the real-time animation of computer of operational environment and generates, fork truck goes module such as dynamic simulation, sound simulation, operation evaluation, data management, network control and operation platform, this training simulator operation platform is fixed, can't simulate the motion experience of driver's in-process of traveling, the dynamic fidelity is not enough.
In a word, the existing motion sensing realization method is mainly used for racing type racing games, 4D dynamic cinema seats and high-speed, high-pressure and high-load and high-time-consuming flight simulation in entertainment facilities, and the existing motion sensing realization method is not completely suitable for forklift driving simulation.
Disclosure of Invention
The invention aims to provide a system and a method for realizing real motion sensing of forklift simulated driving with higher simulated fidelity.
In order to achieve the purpose, the invention adopts the technical scheme that: the utility model provides a real body of fork truck simulation driving feels implementation system, includes the hardware platform, the hardware platform is including moving the platform, deciding platform, three linear drive member, servo motor driver, three the one end of linear drive member with it connects through the spherical hinge pair to move the platform, three the other one end of linear drive member with decide the platform revolute pair and connect, decide the platform and fix subaerial, every linear drive member includes internal thread member and lead screw, the internal thread member cover is in on the lead screw, the lead screw is by private servo motor drive, servo motor with servo motor driver signal connection, three the linear drive member passes through servo motor drive and realizes regular linear removal.
The invention also provides a method for realizing real body feeling of forklift driving simulation, which comprises the following steps:
s1: carrying out forklift kinematics analysis under a typical driving condition of the forklift, establishing a motion equation at the actual forklift mass center position, and acquiring motion parameters; s2: obtaining a motion equation and motion parameters of a driver through coordinate transformation; s3: establishing a human body perception model, and converting a motion equation and motion parameters of a driver into the motion equation and the motion parameters felt by the driver; s4: establishing a motion sensing simulation algorithm model, and converting motion parameters sensed by a driver into space pose signals of a driving simulation platform; s5: establishing a three-dimensional structure model and a motion relation model of the driving simulation platform, and solving through homogeneous coordinate transformation and inverse kinematics to obtain the elongation and the motion change equation of each linear driving rod; s6: the motion of the power-driven linear driving rod is coupled and controlled, so that the real motion simulation of the driving simulation platform is realized.
Further, in S1, the first step,
the resultant force experienced by the forklift while traveling is expressed as:
Fh＝Fq-Fk-Fj-Fp-Ff-Fz (1)
wherein, FhThe resultant force borne by the running is adopted; fqIs the driving force of the forklift; fkIs the air resistance; fjIs acceleration resistance; fpIs the ramp resistance; ffIs rolling resistance; fzIs the braking resistance;
introducing a torque characteristic, a driving force model, a braking resistance model, an air resistance model, a ramp resistance model, an acceleration resistance model and a rolling resistance model of a forklift engine to obtain a functional relation between forklift motion parameters and actual operation analog quantity of a driver:
wherein a is the acceleration of the whole vehicle; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; v. ofiThe rotating speeds of different gears of the engine; m is the mass of the whole vehicle; r is the radius of the driving wheel; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtThe current vehicle speed; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line; theta is a slope angle;
the torque characteristic equation of the forklift engine is as follows:
wherein M iseIs the fork truck engine torque; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; v is the running speed of the forklift;
the driving force model is:
wherein, FqIs the driving force of the forklift; meIs the fork truck engine torque; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; r is the radius of the driving wheel;
the braking resistance model is as follows:
Fz＝mg(c0+c1δ) (5)
wherein, FzIs the braking resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line;
the air resistance model is:
wherein, FkIs the air resistance; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtThe current vehicle speed;
the ramp resistance model is:
Fp＝mgsinθ (7)
wherein, FpIs the ramp resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; theta is the inclination angle of the ramp;
the rolling resistance model is:
Ff＝mgf (8)
wherein, FfIs rolling resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; f is a rolling resistance coefficient;
the acceleration resistance model is:
Fj＝σ×m×a (9)
wherein, FjIs acceleration resistance; m is the mass of the whole vehicle; a is the acceleration of the whole vehicle; and sigma is a conversion coefficient of the rotating mass of the forklift.
Further, in S1, the driver' S actual manipulation analog quantity includes: accelerator pedal travel, brake pedal travel, steering wheel angle.
Further, in S2, the first step,
respectively establishing a motion coordinate system O-xyz and O' -xyz at the mass center of the forklift and the position of a driver; according to the relation of a driver human body coordinate system relative to a forklift mass center inertial coordinate system, uniquely determining the motion condition of each part of the motion platform;
the position vector t between the origins of the two coordinate systems is used for describing the position relation and the motion relation between the two coordinate systems:
t＝[x y z]T (10)
wherein t is a position conversion vector; and x, y and z are position vectors of the human body coordinate system relative to the inertial coordinate system.
Further, in S3, the first step,
the human body senses the change of the motion state through a vestibular system of the inner ear of the human body; simplifying the human vestibular system into a semi-scale pipe model and an otolith model; the otolith is used for sensing linear acceleration change, and the semicircular canal is used for sensing angular acceleration change. The otolith and the semicircular canal adopt a transfer function form to establish a mathematical model;
the corresponding transfer function of the otolith model is as follows:
wherein, L [ f ]]Is the actual stress model function of the driver;
is a function of a stress model felt by a driver; f is specific force input in a certain direction at the center of the vestibule of the brain of the driver;
specific force in the direction felt by the driver; s is the input frequency; k is a gain coefficient; tau isα、τL、τsPhysical parameters of the otolith model;
the corresponding transfer function of the semi-gauge die is as follows:
wherein, L [ omega ]]As a function of the actual steering model of the driver;
a steering model function for the driver; omega is the angular speed input of a certain direction at the center of the brain vestibule of the driver;
the angular velocity of the direction felt by the driver; s is the input frequency; t isL、TS、TαIs a physical parameter of a semi-scale pipe model; delta is the semicircular bell type susceptor deviation;
further, in S4, the first step,
the somatosensory simulation algorithm is a classical washout algorithm;
the input of the classical washout algorithm is the proportion f at the vestibule of the head of the forklift driverAAAnd angular acceleration omega of forklift in three directionsAA(ii) a Firstly, motion amplitude limiting is carried out on a platform through a proportion link, then an acceleration high-frequency part, an acceleration low-frequency part and an angular acceleration high-frequency part are separated out through filtering processing, and the acceleration high-frequency part, the acceleration low-frequency part and the angular acceleration high-frequency part respectively enter an acceleration high-frequency channel, an acceleration low-frequency channel and an angular acceleration high-frequency channel; each channel independently simulates different motion modes of the platform, and each motion mode enables the platform to generate different motions; and finally, integrating the motion generated by the platform through each channel, wherein the integrated final motion state of the platform is the real motion state of the forklift felt by a driver. The output of the classical washout algorithm is kineticSpatial pose signals of the platform.
Further, in S5, the driving simulation platform three-dimensional structure model includes moving platform, fixed platform, three linear driving members, servo motor driver, three the one end of linear driving member with move the platform and pass through the vice connection of ball pivot, three the other one end of linear driving member with fixed platform revolute pair connects, fixed platform is fixed subaerial, every linear driving member includes internal thread member and lead screw, the internal thread member cover is in on the lead screw, the lead screw is by private servo motor drive, servo motor with servo motor driver signal connection, three linear driving member passes through servo motor drive and realizes regular linear movement.
The homogeneous coordinate transformation method comprises the following steps: establishing a fixed coordinate system by taking the mass center of the fixed platform as a fixed coordinate origin, establishing a movable coordinate system by taking the mass center of the movable platform as a movable coordinate system origin, and expressing the space pose state of the movable platform by using the displacement vector and the spiral vector of the mass center of the movable platform; the coordinates of each point of the platform can be represented;
according to the homogeneous coordinate transformation formula, the rotation transformation with the rotation angles theta corresponding to the axes x, y and z can be respectively obtained:
the translation transformation may be represented as:
wherein, a, b and c are respectively the displacement of the axes x, y and z;
the platform motion is synthesized by three motions, namely lifting motion of the mass center of the platform in the z-axis direction, platform pitching motion and platform rolling motion; thus, the motion of the platform can be uniformly expressed as:
wherein l is the length of the linear driving rod; thetapIs the platform pitch angle; thetarIs a platform roll angle; h is the displacement of the mass center of the platform in the z-axis direction;
the inverse kinematics is solved as: the process of solving the extension signal of the linear driving rod on the basis of the known space pose signal of the movable platform is called inverse kinematics solution;
the inverse kinematics solution procedure is as follows:
setting the world coordinates of three points of the platform a, b and c at the initial positions as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (18)
the world coordinates of the three points a, b and c of the transformed platform are as follows:
a(xa,ya,za)；b(xb,yb,zb)；c(xc,yc,zc) (19)
transformed platform coordinates
In the same way
Setting the world coordinates of three points of the platform bases a ', b ' and c ' as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (22)
therefore, the length variation of the three linear driving rods is respectively as follows:
wherein L isa、Lb、LcThe length variable quantities of the three linear driving rods are respectively; a. b and c are respectively the lengths of the three linear rod pieces before the platform changes; a ', b ' and c ' are respectively the lengths of the three linear rod pieces after the platform moves and changes.
Further, in S6, the first step,
the power device is a servo motor;
the joint coupling control device is a three-axis synchronous joint motion control module; the three-axis synchronous joint control module consists of a PC, a USB motion control card and a servo motor driver.
The invention has the beneficial effects that: the invention introduces the concept of dynamic simulation on the basis of the existing forklift driving simulation technology, and solves the problem of insufficient motion simulation in the traditional forklift driving simulation. Through establishing a forklift kinematic model, a human body perception model and a platform three-dimensional model and multi-model nesting combination, the motion simulation of a forklift driving movable platform is realized, the motion feeling in the forklift driving operation can be simulated in the limited stroke of the movable platform, the simulation fidelity of a forklift driving simulator is increased, and a more vivid driving environment is created for a driver from a dynamic angle.
Drawings
The following detailed description is to be read in connection with the accompanying drawings and the detailed description.
FIG. 1 is a hardware platform structure of a forklift real motion sensing simulation realization system according to the invention;
FIG. 2 is a schematic diagram of a three-axis joint synchronous motion control module according to the present invention;
FIG. 3 is a flow chart of a method for realizing forklift driving simulation body feeling in the invention
FIG. 4 is a force analysis diagram for analyzing the kinematics of the forklift
FIG. 5 is a schematic diagram of specific force of human body
FIG. 6 is a schematic diagram of a somatosensory simulation algorithm
FIG. 7 is a three-dimensional model diagram of a three-degree-of-freedom parallel motion platform
FIG. 8 is a mathematical model diagram of a parallel motion platform with three degrees of freedom
FIG. 9 is a mathematical model diagram of a three-degree-of-freedom parallel motion platform
FIG. 10 is a diagram of a mathematical model of a moving platform of a parallel motion platform with three degrees of freedom
In the figure: 1-moving platform 2-static platform 3-linear driving rod 4-servo motor 5-servo motor driver.
Detailed description of the preferred embodiments
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The invention relates to a forklift real body feeling simulation system, which comprises a hardware platform and a software module.
As shown in fig. 1, the real body feeling implementation system for simulating driving of a forklift truck comprises a movable platform 1, a fixed platform 2, three linear driving rods 3, a servo motor 4 and a servo motor driver 5.
Furthermore, the movable platform 1 is connected with the three linear driving rod pieces 3 through a spherical hinge pair, and the upper surface of the movable platform is connected with the seat and used for outputting the motion of the platform. The real acceleration, deceleration, turning and bumping feelings in the running process of the forklift are simulated through the pitching, tilting and up-and-down vibration of the movable platform 1.
Furthermore, the fixed platform 2 is fixed on the ground and is connected with the three linear driving rod pieces 3 through revolute pairs.
Furthermore, every linear driving rod piece 3 includes internal thread rod piece and lead screw, the internal thread rod piece cover is in on the lead screw, the lead screw is driven by private service motor 4, servo motor 4 with servo motor driver 5 signal connection, three linear driving rod pieces 3 realize regular linear movement through servo motor 4 drive.
As shown in fig. 2, the software module refers to a three-axis joint synchronous motion control module, and specifically includes sub-modules such as a computer, a data acquisition card, a servo motor driver, and an encoder.
As shown in fig. 3, the method for realizing real motion sensing of forklift simulation driving according to the present invention comprises the following steps: (1) carrying out kinematic analysis on the forklift to obtain a motion change rule and motion parameters of the actual forklift; (2) establishing a human body perception model, and converting the motion parameters of the vehicle centroid position to the driver position through coordinate transformation; (3) converting the motion parameters of the driver into space pose signals of the moving platform through a somatosensory simulation algorithm; (4) establishing a three-dimensional model of the platform, and solving an equation through homogeneous coordinate transformation and inverse kinematics to obtain an elongation signal of each linear driving rod; (5) the power drives the linear driving rod to regularly move to realize the motion of the platform, so that the driving simulation of the forklift is realized, and the real driving feeling is provided for a driver.
As shown in fig. 4, the force analysis diagram of the forklift kinematics analysis is shown. Through the stress analysis, the resultant force applied to the forklift during running can be expressed as:
Fh＝Fq-Fk-Fj-Fp-Ff-Fz (24)
wherein, FhThe resultant force borne by the running is adopted; fqIs the driving force of the forklift; fkIs the air resistance; fjIs acceleration resistance; fpIs the ramp resistance; ffIs rolling resistance; fzIs the braking resistance.
By introducing an engine torque characteristic, a driving force model, a braking resistance model, a ramp resistance model, an acceleration resistance model and a rolling resistance model, a functional relation between the spatial position posture of the forklift and actual operation analog quantities (an accelerator pedal stroke, a brake pedal stroke and a steering wheel rotation angle) of a driver can be obtained.
Wherein a is the acceleration of the whole vehicle; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; v. ofiThe rotating speeds of different gears of the engine; m is the mass of the whole vehicle; r is the radius of the driving wheel; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtThe current vehicle speed; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line; theta is the ramp inclination angle.
The torque characteristic equation of the forklift engine is as follows:
wherein M iseIs the fork truck engine torque; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; and v is the running speed of the forklift.
The driving force model is:
wherein, FqIs the driving force of the forklift; meIs the fork truck engine torque; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; r is mainlyRadius of the driving wheel.
The braking resistance model is as follows:
Fz＝mg(c0+c1δ) (28)
wherein, FzIs the braking resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line.
The air resistance model is:
wherein, FkIs the air resistance; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtIs the current vehicle speed.
The ramp resistance model is:
Fp＝mg sinθ (30)
wherein, FpIs the ramp resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; theta is the ramp inclination angle.
The rolling resistance model is:
Ff＝mgf (31)
wherein, FfIs rolling resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; f is a rolling resistance coefficient.
The acceleration resistance model is:
Fj＝σ×m×a (32)
wherein, FjIs acceleration resistance; m is the mass of the whole vehicle; a is the acceleration of the whole vehicle; and sigma is a conversion coefficient of the rotating mass of the forklift.
And obtaining original motion data according to the motion mode and the motion parameters of the real forklift, using the original motion data as a data source for solving the forklift driving simulation kinematics, and providing a basis for subsequent motion platform design. Table 1 shows the design parameters of the forklift driving simulation platform.
TABLE 1 Forklift driving simulation platform design parameters
| Parameter name | Design value |
| Moving platform lifting amplitude (vertical vibration amplitude) | ±100mm |
| Inclination of movable platform (Pitch angle, roll angle) | ±12°、±12° |
| Maximum linear velocity (lifting speed) | 300mm/s |
| Maximum angular velocity (Pitch angle, roll angle) | 12°/s\12°/s |
| Maximum linear acceleration (lifting acceleration) | 1.0g |
| Maximum load | 200kg |
| Maximum height of moving platform | ≤1m |
The human body perception motion change is realized through the human body inner ear vestibular system. The vestibule consists of three semicircular canals, a sacculus and an elliptical sac, wherein the elliptical sac and the sacculus are also called as otoliths. When a human body moves or a vehicle starts, accelerates, decelerates and turns, liquid in the vestibule flows to drive cilia of hair cells to correspondingly bend, bioelectricity is generated and is transmitted to a high-level nerve center inwards, and people feel the moving state. The semicircular canal is responsible for sensing angular acceleration, such as the stimulation of rotation activities in automobile turning, airplane rolling flight and various movements; the otolith is responsible for sensing linear acceleration, such as starting and braking, acceleration and deceleration, elevator lifting stimulation and the like of the automobile, and sensing acting force acting on joint positions and muscles. When the motion acceleration is lower than a certain threshold value, the motion cannot be perceived as a remarkable characteristic of a human body perception system, and the somatosensory simulation is realized by utilizing the characteristic. In order to simulate the body feeling of a human body on the forklift, the human body can generate the kinesthesis or body feeling provided by the actual forklift as long as the similar stimulation information similar to that generated by the forklift is input to the human body. Otoliths feel linear acceleration, such as three linear motion sensations of longitudinal, lateral and vertical, but otoliths have difficulty distinguishing whether acceleration is caused by motion or gravity. By utilizing the characteristic, the platform is inclined at a certain angle, and the continuous low-frequency acceleration is simulated by utilizing the component of the gravity acceleration. The perception of linear acceleration by the otolith is expressed in terms of specific force.
As shown in FIG. 5, the definition of the specific force f, i.e.
f＝a-g (33)
Wherein f is the specific force borne by the human body; a is the actual vehicle acceleration; g is the acceleration of gravity.
The otolith acts as a low pass filter and the high frequency specific force signal is hardly perceptible to the human body. The otolith also has a certain sensory threshold when the longitudinal or lateral acceleration of the moving body is lower than 0.17m/s2The vertical direction is less than 0.28m/s2When the user feels no movement. The transfer function of the otolith can be simplified as:
wherein, L [ f ]]Is the actual stress model function of the driver;
is felt by the driverA force model function; f is specific force input in a certain direction at the center of the vestibule of the brain of the driver;
specific force in the direction felt by the driver; s is the input frequency; k is a gain coefficient; tau isα、τL、τsIs the physical parameter of the otolith model.
The semicircular canal acts as a band-pass filter, and the human body can only sense the existence of rotational movement within a certain frequency band. Similarly, the semicircular canal has a certain sensing threshold, and when the pitch angle velocity, the roll angle velocity and the yaw angle velocity of the moving body are respectively lower than 3.6m/s, 3m/s and 2.6m/s, people cannot sense the rotating angular velocity. The transfer function of the semi-scale pipe model is simplified as follows:
wherein, L [ omega ]]As a function of the actual steering model of the driver;
a steering model function for the driver; omega is the angular speed input of a certain direction at the center of the brain vestibule of the driver;
the angular velocity of the direction felt by the driver; s is the input frequency; t isL、TS、TαIs a physical parameter of a semi-scale pipe model; delta is the semicircular bell susceptor deflection.
Through the human perception model, actual forklift motion parameters are transferred to human ears from the forklift mass center, so that the dynamic simulation of the platform is more in line with the actual feeling of a driver.
As shown in fig. 6, a schematic diagram of a somatosensory simulation algorithm is shown. The acceleration can be sensed by the vestibular organ of the human body, but the motion acceleration or the gravity acceleration of the vehicle cannot be distinguished, so the classic washout algorithm is designed by utilizing the acceleration. Washing outThe algorithm simply divides the complex motion state of the forklift into three modes: longitudinal mode, lateral mode, and up-down mode. The first two modes are such that the simulator is tilted by a certain pitch angle and a certain roll angle within a certain spatial limit, thereby generating a gravitational acceleration component, so that the driver feels a sense of continuous acceleration as in a real acceleration, for example, 1m/s in a longitudinal acceleration2. The movement process of duration 10s requires a stroke of 50m, however the space of the platform is limited and the simulator cannot be fully implemented, so that if the simulator is pitched 60The acceleration component g sin theta is made to provide 1m/s to the driver2So that the driver has a feeling of constant acceleration. The latter two modes may use the high pass filter alone to simulate the high frequency motion of the vehicle.
The somatosensory simulation algorithm is a classical washout algorithm. The working space of the motion simulator is limited, the motion simulator can not move infinitely in the space, the angle and the displacement of the motion simulator are limited, and only a certain algorithm is used for changing the control input to the platform, so that the platform can move in the motion range, and can return to the neutral position again after one motion, thereby providing space for the next motion and keeping higher motion fidelity feeling.
As shown in FIG. 6, the input to the classical washout algorithm is the specific force f at the vestibule of the head of the forklift driverAAAnd angular acceleration omega of forklift in three directionsAA. Firstly, motion amplitude limiting is carried out on the platform through a proportion link, then an acceleration high-frequency part, an acceleration low-frequency part and an angular acceleration high-frequency part are separated through filtering processing, and the acceleration high-frequency part, the acceleration low-frequency part and the angular acceleration high-frequency part respectively enter an acceleration high-frequency channel, an acceleration low-frequency channel and an angular acceleration high-frequency channel. Each channel individually simulates different motion patterns of the platform, each motion pattern causing a different motion of the platform. And finally, integrating the motion generated by the platform through each channel, wherein the integrated final motion state of the platform is the real motion state of the forklift felt by a driver. The output of the classical washout algorithm is a spatial pose signal of the moving platform.
The proportional link is used for limiting the motion range of the platform. Because the travel of the forklift driving simulation platform is limited, in order to prevent the platform from exceeding the limit caused by excessive acceleration and angular velocity input, a proportion link is required to be added in an algorithm to limit the magnitude of an input signal, so that the motion amplitude can be reduced, but in general, in order to enable the acceleration and the angular velocity sensed by a driver to be the same as those of a real transportation vehicle, the proportion smaller than 1 is added moderately only when no solution is available. Typically, the ratio constant takes 1.
f′AA＝Kf fAA (36)
Wherein, f'AAThe specific force at the vestibule of the head of the driver after the proportion limitation; kfIs an acceleration proportionality constant; f. ofAAIs the specific force at the vestibule of the head of the driver.
ω′AA＝KωωAA (37)
Wherein, omega'AAThe angular acceleration of the rear forklift in three directions is limited;
is an angular velocity proportionality constant; omegaAAAngular acceleration of the forklift in three directions.
The acceleration high-speed channel is used for simulating high-frequency vibration of the forklift in the vertical direction and can be simulated through sudden change of the platform. The acceleration high-speed channel algorithm adopts a second-order high-pass filter, and the expression is as follows:
wherein the content of the first and second substances,
simulating linear acceleration for the platform;
is the actual linear acceleration; s is the input frequency; xihxThe damping rate is a longitudinal acceleration high-pass filtering damping rate; omegahxHigh pass filtering cut-off for longitudinal accelerationFrequency.
The angular acceleration high-speed channel also uses a form of high-pass filtering, and the expression is as follows:
wherein the content of the first and second substances,
simulating angular acceleration for the platform;
actual angular acceleration; s is the input frequency; xihφThe damping rate is a longitudinal angular velocity high-pass filtering damping rate; omegahφThe cut-off frequency is high-pass filtered for longitudinal angular velocity.
The acceleration low speed channel, also known as the tilt coordination channel, is the key to the classical washout algorithm. Acceleration can be sensed by human vestibular organs, but the motion acceleration or the gravity acceleration of a vehicle cannot be distinguished, so a classical washout algorithm is designed by utilizing the point, low-frequency acceleration which cannot be simulated by a simulator is firstly filtered out by using a low-frequency filter and then converted into the inclination angle of a platform, and a part of component of the gravity acceleration is used as acceleration to enable a driver of the platform to sense continuous acceleration, which is called inclination coordination motion. Of course, the motion of the platform in tilting should not be felt by the driver, using human perception thresholds, below which the human perceives no rotational motion when the pitch, roll and yaw rates are below 3.6, 3 and 2.6m/s, respectively, so that the angular velocity of the platform rotation is controlled to be below such a threshold that the human perceives the resulting acceleration while not perceiving the presence of the human. The acceleration low-speed channel filtering algorithm comprises the following steps:
wherein the content of the first and second substances,
simulating acceleration for the platform; a isxIs the actual acceleration; s is the input frequency; xilxThe damping rate is a longitudinal acceleration high-pass filtering damping rate; omegalxThe cut-off frequency is high-pass filtered for the longitudinal acceleration.
Aiming at a longitudinal mode and a lateral mode, a classical washout algorithm decomposes specific force at the vestibule of the head of a simulated vehicle driver into a high-frequency signal and a low-frequency signal by using a high-pass filter and a low-pass filter, and because the high-frequency part cannot enable the motion of a platform to be out of limit, the high-frequency part can be directly used as the input of a system and becomes longitudinal displacement and transverse displacement in a pose signal of the platform through twice integration. The low frequency signals may cause the platform to overrun and therefore not be directly input to the system, and the low frequency signals are passed through the tilt platform to generate equivalent pitch and roll angles, relying on the components of gravitational acceleration to simulate sustained acceleration. The real forklift motion state sensed by a driver is converted into a space pose signal of the movable platform through a somatosensory simulation algorithm.
As shown in fig. 7, the three-degree-of-freedom parallel motion platform of the forklift is composed of a movable platform, a fixed platform, a linear moving rod, a servo motor and a motor driver. The platform for splicing the mechanisms is a circular base. Three supports are designed on the base, the motion input is realized by adopting a servo motor, and the upper platform is a motion platform to realize the motion output. One end of the spherical hinge pair is connected with the upper platform plate, and the other end of the spherical hinge pair is fixedly connected with the movable rod. The movable rod is an internal thread rod piece sleeved on a screw rod driven by a servo motor. When the motor rotates, the moving rod can move along the rod sleeve to form a moving pair. The optical axis for the servo motor is fixed on the bracket to form a revolute pair. The three-freedom-degree parallel mechanism is formed by splicing the kinematic pairs. And realizing the accurate motion control of the parallel platform by means of the three-axis synchronous motion control module.
As shown in fig. 8, a fixed coordinate system is established with the mass center of the fixed platform as the origin of the fixed coordinate, a moving coordinate system is established with the mass center of the moving platform as the origin of the moving coordinate system, and the spatial pose state of the moving platform is represented by the displacement vector and the spiral vector of the mass center of the moving platform.
Real motion parameters sensed by a driver are converted into space pose signals of the three-degree-of-freedom parallel platform moving platform through a somatosensory simulation algorithm, however, the platform is driven to move, and only a linear driving rod piece is pushed to move regularly through a motor, so that the platform can move. Therefore, a kinematic solution equation is needed to convert the space pose signal of the moving platform into a displacement signal of the linear driving rod.
As shown in fig. 8, according to the homogeneous coordinate transformation formula, it is possible to obtain rotation transformations corresponding to axes x, y, and z by a rotation angle θ:
the translation transformation may be represented as:
wherein, a, b, c are displacement amounts in the directions of axes x, y, z, respectively.
The platform motion can be synthesized by three motions, namely lifting motion of the mass center of the platform in the Z-axis direction, platform pitching motion and platform rolling motion. Thus, the motion of the platform can be uniformly expressed as:
wherein l is the length of the linear driving rod; thetapIs the platform pitch angle; thetarIs a platform roll angle; h is a platformDisplacement of the center of mass in the z-axis direction.
Setting the world coordinates of three points of the platform a, b and c at the initial positions as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (46)
the world coordinates of the three points a, b and c of the transformed platform are as follows:
a(xa,ya,za)；b(xb,yb,zb)；c(xc,yc,zc) (47)
transformed platform coordinates
In the same way
Setting the world coordinates of three points of the platform bases a ', b ' and c ' as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (50)
therefore, the length variation of the three linear driving rods is respectively as follows:
wherein L isa、Lb、LcThe length variable quantities of the three linear driving rods are respectively; a. b and c are respectively the lengths of the three linear rod pieces before the platform changes; a ', b ' and c ' are respectively the lengths of the three linear rod pieces after the platform moves and changes.
And converting the space pose signal of the movable platform into the elongation signals of the three linear driving rods through inverse kinematics solution.
And finally, the linear driving rod is driven by power to move according to a certain rule, so that the dynamic simulation of the platform is realized.
Claims (2)
1. The utility model provides a real body of fork truck simulation driving feels implementation method, includes the hardware platform, the hardware platform including move platform (1), decide platform (2), three linear drive member (3), servo motor (4), servo motor driver (5), three the one end of linear drive member (3) with move platform (1) and pass through the spherical hinge pair and be connected, three the other one end of linear drive member (3) with decide platform (2) revolute pair and be connected, decide platform (2) and fix subaerial, every linear drive member (3) include internal thread member and lead screw, the internal thread member cover is on the lead screw, the lead screw is driven by servo motor (4), servo motor (4) with servo motor driver (5) signal connection, three linear drive member (3) realize regular linear movement through servo motor (4) drive, the implementation method comprises the following steps:
s1: carrying out forklift kinematics analysis under a typical driving condition of the forklift, establishing a motion equation at the actual forklift mass center position, and acquiring motion parameters; in the step S1, the first step,
the resultant force experienced by the forklift while traveling is expressed as:
Fh＝Fq-Fk-Fj-Fp-Ff-Fz (1)
wherein, FhThe resultant force borne by the running is adopted; fqIs the driving force of the forklift; fkIs the air resistance; fjIs acceleration resistance; fpIs the ramp resistance; ffIs rolling resistance; fzIs the braking resistance;
introducing a torque characteristic, a driving force model, a braking resistance model, an air resistance model, a ramp resistance model, an acceleration resistance model and a rolling resistance model of a forklift engine to obtain a functional relation between forklift motion parameters and actual operation analog quantity of a driver:
wherein a is the acceleration of the whole vehicle; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; v. ofiThe rotating speeds of different gears of the engine; m is the mass of the whole vehicle; r is the radius of the driving wheel; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtThe current vehicle speed; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line; theta is a slope angle;
the torque characteristic equation of the forklift engine is as follows:
wherein M iseIs the fork truck engine torque; a is0、a1、a2、a3A third fitting coefficient of the torque of the forklift engine; biFitting coefficients under different gears; v is the running speed of the forklift;
the driving force model is:
wherein, FqIs the driving force of the forklift; meIs the fork truck engine torque; i.e. igIs the reduction ratio of the gearbox; i.e. i0Is the reduction ratio of the speed reducer; η is the transmission system efficiency; lmaxThe maximum travel of the clutch pedal; l is the current stroke of the clutch pedal; r is the radius of the driving wheel;
the braking resistance model is as follows:
Fz＝mg(c0+c1δ) (5)
wherein, FzIs the braking resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; delta is the slip ratio; c. C0Fitting coefficients of different sections of straight lines; c. C1Is the slope of the fitted line;
the air resistance model is:
wherein, FkIs the air resistance; c is the air resistance coefficient; ρ is the air density; s is the windward area; vtThe current vehicle speed;
the ramp resistance model is:
Fp＝mg sinθ (7)
wherein, FpIs the ramp resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; theta is the inclination angle of the ramp;
the rolling resistance model is:
Ff＝mgf (8)
wherein, FfIs rolling resistance; m is the mass of the whole vehicle; g is the acceleration of gravity; f is a rolling resistance coefficient;
the acceleration resistance model is:
Fj＝σ×m×a (9)
wherein, FjIs acceleration resistance; m is the mass of the whole vehicle; a is the acceleration of the whole vehicle; sigma is a conversion coefficient of the rotating mass of the forklift;
s2: obtaining a motion equation and motion parameters of a driver through coordinate transformation; in the step S2, the first step,
respectively establishing a motion coordinate system O-xyz and O' -xyz at the mass center of the forklift and the position of a driver; according to the relation of a driver human body coordinate system relative to a forklift mass center inertial coordinate system, uniquely determining the motion condition of each part of the motion platform;
the position vector t between the origins of the two coordinate systems is used for describing the position relation and the motion relation between the two coordinate systems:
t＝[x y z]T (10)
wherein t is a position conversion vector; x, y and z are position vectors of the human body coordinate system relative to the inertial coordinate system;
s3: establishing a human body perception model, and converting a motion equation and motion parameters of a driver into the motion equation and the motion parameters felt by the driver; in the step S3, the first step,
the human body senses the change of the motion state through a vestibular system of the inner ear of the human body; simplifying the human vestibular system into a semi-scale pipe model and an otolith model; the otolith is used for sensing the change of linear acceleration, and the semicircular canal is used for sensing the change of angular acceleration; the otolith and the semicircular canal adopt a transfer function form to establish a mathematical model;
the corresponding transfer function of the otolith model is as follows:
wherein, L [ f ]]Is the actual stress model function of the driver;
is a function of a stress model felt by a driver; f is specific force input in a certain direction at the center of the vestibule of the brain of the driver;
specific force in the direction felt by the driver; s is the input frequency; k is a gain coefficient; tau isα、τL、τsPhysical parameters of the otolith model;
the corresponding transfer function of the semi-gauge die is as follows:
wherein, L [ omega ]]As a function of the actual steering model of the driver;
a steering model function for the driver; omega is the angular speed input of a certain direction at the center of the brain vestibule of the driver;
the angular velocity of the direction felt by the driver; s is the input frequency; t isL、TS、TαIs a physical parameter of a semi-scale pipe model; delta is the semicircular bell type susceptor deviation;
s4: establishing a motion sensing simulation algorithm model, and converting motion parameters sensed by a driver into space pose signals of a driving simulation platform; in the step S4, the first step,
the somatosensory simulation algorithm is a classical washout algorithm;
the input of the classical washout algorithm is the proportion f at the vestibule of the head of the forklift driverAAAnd angular acceleration omega of forklift in three directionsAA(ii) a Firstly, motion amplitude limiting is carried out on a platform through a proportion link, then an acceleration high-frequency part, an acceleration low-frequency part and an angular acceleration high-frequency part are separated out through filtering processing, and the acceleration high-frequency part, the acceleration low-frequency part and the angular acceleration high-frequency part respectively enter an acceleration high-frequency channel, an acceleration low-frequency channel and an angular acceleration high-frequency channel; each channel independently simulates different motion modes of the platform, and each motion mode enables the platform to generate different motions; finally, integrating the motion generated by the platform by each channel, wherein the integrated final motion state of the platform is the real motion state of the forklift felt by a driver; the output of the classical washout algorithm is a space pose signal of the moving platform;
s5: establishing a three-dimensional structure model and a motion relation model of the driving simulation platform, and solving through homogeneous coordinate transformation and inverse kinematics to obtain the elongation and the motion change equation of each linear driving rod; in S5, the driving simulation platform three-dimensional structure model comprises a movable platform (1), a fixed platform (2), three linear driving rod pieces (3), a servo motor (4) and a servo motor driver (5), wherein one ends of the three linear driving rod pieces (3) are connected with the movable platform (1) through a spherical hinge pair, the other ends of the three linear driving rod pieces (3) are connected with a revolute pair of the fixed platform (2), the fixed platform (2) is fixed on the ground, each linear driving rod piece (3) comprises an internal thread rod piece and a screw rod, the internal thread rod piece is sleeved on the screw rod, the screw rod is driven by a personal clothing motor (4), the servo motor (4) is in signal connection with the servo motor driver (5), and the three linear driving rod pieces (3) are driven by the servo motor (4) to realize regular linear movement;
the homogeneous coordinate transformation method comprises the following steps: establishing a fixed coordinate system by taking the mass center of the fixed platform as a fixed coordinate origin, establishing a movable coordinate system by taking the mass center of the movable platform as a movable coordinate system origin, and expressing the space pose state of the movable platform by using the displacement vector and the spiral vector of the mass center of the movable platform; the coordinates of each point of the platform can be represented;
according to the homogeneous coordinate transformation formula, the rotation transformation with the rotation angles theta corresponding to the axes x, y and z can be respectively obtained:
the translation transformation may be represented as:
wherein, a, b and c are respectively the displacement of the axes x, y and z;
the platform motion is synthesized by three motions, namely lifting motion of the mass center of the platform in the z-axis direction, platform pitching motion and platform rolling motion; thus, the motion of the platform can be uniformly expressed as:
wherein l is the length of the linear driving rod; thetapIs the platform pitch angle; thetarIs a platform roll angle; h is the displacement of the mass center of the platform in the z-axis direction;
the inverse kinematics is solved as: the process of solving the extension signal of the linear driving rod on the basis of the known space pose signal of the movable platform is called inverse kinematics solution;
the inverse kinematics solution procedure is as follows:
setting the world coordinates of three points of the platform a, b and c at the initial positions as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (18)
the world coordinates of the three points a, b and c of the transformed platform are as follows:
a(xa,ya,za)；b(xb,yb,zb)；c(xc,yc,zc) (19)
transformed platform coordinates
In the same way
Setting the world coordinates of three points of the platform bases a ', b ' and c ' as follows:
a(xa0,ya0,zao)；b(xb0,ybo,zbo)；c(xco,yco,zco) (22)
therefore, the length variation of the three linear driving rods is respectively as follows:
wherein L isa、Lb、LcThe length variable quantities of the three linear driving rods are respectively; a. b and c are respectively the lengths of the three linear rod pieces before the platform changes; a ', b ' and c ' are respectively the lengths of the three linear rod pieces after the platform moves and changes;
s6: the motion of the power-driven linear driving rod is coupled and controlled, so that the real motion simulation of the driving simulation platform is realized; in the step S6, the first step,
the power device is a servo motor;
the joint coupling control device is a three-axis synchronous joint motion control module; the three-axis synchronous joint control module consists of a PC, a USB motion control card and a servo motor driver.
2. The method for realizing real motion sensing of the forklift truck simulated driving according to claim 1, wherein in S1, the simulation quantity of actual manipulation of the driver includes: accelerator pedal travel, brake pedal travel, steering wheel angle.
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