398 results about "Inverse kinematics" patented technology

The embodiment of the invention provides an unhooking robot control method based on multi-source visual fusion, which is applied to the technical field of robot control and comprises the following steps: acquiring an RGB image, a depth image, an infrared image and IMU data through a multi-source sensing system mounted at the tail end of a robot; carrying out feature fusion identification by adopting a double-branch neural network, and outputting the boundary contour of the lifting hook and the three-dimensional coordinates of the optimal grabbing point; the visual coordinates are unified to a robot base coordinate system through a registration correction mechanism; a Transform prediction model is constructed based on the visual and inertial signals, and future pose changes of the lifting hook are estimated; a feedforward control track is generated to counteract swing of the lifting hook, and track correction is carried out in combination with visual servo feedback; and a joint instruction is generated through path planning and inverse kinematics solution, and the mechanical arm is driven to complete precise unhooking operation. According to the method, the recognition precision, the anti-interference capability and the operation success rate of unhooking operation in complex illumination and dynamic environments are effectively improved.

The invention provides a five-axis series-parallel numerical control machine tool machining process virtual monitoring simulation method and system based on digital twinning, and the method comprises the steps: building an information interaction mechanism between a physical machine tool and a digital twinning model, enabling a server side to collect sensor data, and transmitting the real-time data to a client side through a communication protocol; the client processes the data and drives the digital twin model. And aiming at potential errors of twin system forecast, tool setting error compensation can be carried out in real time, so that the machining precision is improved. Meanwhile, the system supports an offline simulation function, combines an inverse kinematics algorithm and an NC code, fuses a material removal model, simulates a machining process, evaluates machining performance and errors, and provides an optimization basis for machining strategies of workpieces with different geometrical shapes and materials. According to the method, bidirectional interaction between the physical entity and the virtual model is achieved, the real-time monitoring and visualization capability of the machining process is enhanced, a reliable simulation evaluation and optimization means is provided for machining of complex parts, and the method has wide industrial application prospects.

The invention relates to the technical field of image data processing and intelligent control, and discloses a patch board spot welding track intelligent control method and system based on visual perception. According to the method, synchronous image streams are collected through a binocular vision sensor, and epipolar correction image pairs are generated through timestamp synchronization, ROI extraction and epipolar correction processing; calculating a disparity map by adopting a stereo matching algorithm, and constructing a compensated three-dimensional point cloud model based on deformation vector field fusion multi-frame point cloud data of a radial basis kernel function; welding spot position error vectors are generated by extracting welding spot feature points and performing spatial filtering optimization; and carrying out inverse kinematics calculation on the mechanical arm by adopting a damping least square method, carrying out safety constraint optimization in combination with prospective collision risk assessment and real-time pose data, and generating a trajectory compensation instruction. According to the method, the problems of dynamic deformation compensation and motion safety in patch plate welding are solved, the submillimeter welding spot positioning precision is achieved, and the welding quality stability and the system robustness are improved.

The invention provides a real-time monitoring system and method for sorting of a digital twin-driven Delta mechanical arm. According to the system, firstly, a physical experiment platform is built, and a virtual model is built through SolidWorks, 3DMAX and Unity 3D. A communication framework is designed, and wireless communication of the PLC, the sensor, the mechanical arm, the conveying belt and the digital twin system is achieved. Positive and inverse kinematics analysis and Cartesian space trajectory planning are carried out on a Delta robot, and a related algorithm is packaged into an MATLAB function and compiled into a DLL library for C # calling. The system collects joint angle data in real time based on a rotary encoder, transmits the joint angle data to a digital twin system through an OPC UA protocol, and drives a virtual mechanical arm model after resolving, so that high-precision and low-delay virtual-real synchronous pose reconstruction is realized. In addition, the system also develops a collision detection function based on a bounding box algorithm, and performs visual detection by using camera calibration and a YOLO model.

The invention relates to the technical field of cooperative control, and discloses an anti-corrosion pipe winding angle and linear speed cooperative control method and system. The method comprises the following steps: collecting winding angle and linear speed time sequence data, and constructing a three-layer scale feature vector and a real track deviation; inputting a three-branch LSTM model to output a prediction deviation sequence; calculating a feed-forward compensation amount through an inverse kinematics model; and performing model increment updating based on the prediction error, calculating a feedback compensation amount, and adaptively fusing feedforward and feedback compensation to obtain a cooperative control instruction. The technical problems that in traditional fixed parameter control, dynamic cooperation of the angle and the speed is lacked, compensation response lags behind, feedforward and feedback conflicts exist, and a prediction model cannot conduct self-adaptive evolution are solved.

The invention discloses a seven-degree-of-freedom mechanical arm trajectory planning method based on null space optimization, relates to the technical field of mechanical arm intelligent control, and aims to solve the problems that an existing mechanical arm trajectory planning method easily causes sudden posture change and affects trajectory continuity and motion stability when Euler angle velocity is adopted for posture planning. According to the method, the Jacobian matrix is adopted for operation without depending on a complex inverse kinematics calculation process, and the method can be suitable for redundant mechanical arms of any configuration; according to the method, the tail end trajectory is planned in a pose matrix mode, joint layer optimization is achieved through a null space formed by redundant freedom degrees, pose sudden change easily caused when the Euler angle velocity is adopted for pose planning is avoided, and the continuity and motion stability of trajectory planning of the mechanical arm are improved.

The invention provides an autonomous navigation and intelligent obstacle avoidance method of a biomimetic robot, and relates to the technical field of biomimetic robots, which realizes real-time estimation of six-degree-of-freedom poses by collecting environmental data; visual features are extracted by using a convolutional network, an enhanced memory unit is constructed in combination with pose information, a triple index path memory library is maintained through a dynamic memory updating mechanism, and feature similarity retrieval and navigation instruction generation in a backtracking mode are supported; defining a state vector based on a resultant force of a robot pose, a target direction and an artificial potential field, training a strategy network through deep reinforcement learning, and outputting a motion instruction according to Q value maximization; fusing an artificial potential field and a dynamic window method, and optimizing an objective function to obtain optimal linear velocity and angular velocity; and solving a joint angle through inverse kinematics, and combining attitude error feedback to realize body attitude maintenance and foot end trajectory tracking.

The invention discloses an underwater multi-mode mobile robot equipped with a flexible bionic gripper, which integrates three operation modes of propeller propulsion, six-foot crawling and target object grabbing, and realizes'movement-attachment-operation 'integrated collaboration. The robot main body adopts a five-thruster vector layout and has a five-degree-of-freedom motion capability; and six groups of three-degree-of-freedom mechanical feet and two groups of three-degree-of-freedom mechanical arms are arranged outside, and a cruising mode, a crawling mode or a grabbing mode can be automatically switched according to tasks. A coordination dual-network hydrogel bionic sucker and a flexible gripper are integrated at the foot end and the arm end, and controllable adsorption and desorption are achieved through a diaphragm pump. The control system generates a rhythm signal based on the central mode generator, and coordinates multi-module actions of paddles, legs and arms in combination with inverse kinematics solution. The robot is suitable for tasks such as wide water area cruising, complex terrain exploration, environment maintenance and seabed sampling, has high maneuverability and high integration degree, and provides an innovative platform for underwater fine operation.

The invention provides a wearable exercise and rehabilitation monitoring system based on multi-modal AI, which relates to the field of electrical digital data processing and comprises a distributed multi-modal sensing acquisition module, a hierarchical wireless data aggregation and transmission module, a 3D human body dynamics reconstruction and modeling module and an intelligent action evaluation and feedback module. The distributed multi-modal sensing acquisition module is responsible for realizing multi-dimensional cooperative sensing of human body motion through heterogeneous sensors, and the hierarchical wireless data aggregation and transmission module adopts a master-slave base station architecture to realize efficient aggregation and low-delay transmission of heterogeneous sensor data. The 3D human body dynamics reconstruction and modeling module is used for realizing high-fidelity 3D skeleton model reconstruction based on inverse kinematics solution of multi-sensor fusion; the intelligent action evaluation and feedback module is used for providing personalized training guidance by constructing a standard action library and realizing multi-dimensional similarity quantitative scoring; according to the system, deep fusion of the multi-modal sensor can be realized, and accurate motion monitoring is provided.

The invention discloses a mechanical arm teleoperation control method and system based on incremental mapping, and the method comprises the steps: carrying out the noise reduction processing of the position and posture of a handle through adaptive low-pass filtering, and achieving the position and posture consistency mapping from a handle space to a mechanical arm working space after coordinate system axis rearrangement and similar transformation mapping; the system provides two kinds of control output of a pose tracking mode and a speed tracking mode, real-time inverse kinematics solution is carried out through a Jacobian matrix and a damping least square method in the speed mode, and resolution scaling and exponential moving average / spherical linear interpolation smooth filtering are carried out on a target pose in the pose mode. And then the handle motion instruction is mapped into a Cartesian instruction or a joint space instruction at the tail end of the mechanical arm, closed-loop execution is conducted through a real-time state feedback link, and the method can be used for scenes such as robot service, teaching, remote operation and data collection.

The invention provides a mechanical arm inverse kinematics iteration solving method and mechanical arm motion control equipment, and relates to the technical field of robot control. According to the method, in the process of realizing inverse kinematics iterative solution for the redundant degree-of-freedom mechanical arm by utilizing the damping least square framework, the limiting risk closeness degree of each solid joint is assessed prospectively, and damping coefficient self-adaptive solution is performed in combination with the pose error of the tail end of the mechanical arm; the finally solved damping coefficient responds to the external task requirement and the internal body state of the mechanical arm at the same time so as to be deeply combined with Jacobian matrix sensitivity self-adaptive attenuation operation, and joint impact limiting is actively and softly avoided from the source; therefore, the real-time performance, the settlement precision, the stability and the robustness of inverse kinematics solving operation of the mechanical arm are remarkably improved, and the phenomena that the mechanical arm shakes in motion, the torque impact of the mechanical arm or the mechanical arm falls into oscillation near joint limiting and the like are avoided as much as possible.

The invention discloses a singularity-avoiding trajectory planning method for a free floating space mechanical arm, and belongs to the technical field of robot trajectory planning. The method comprises the steps that the expected whole-course tail end position track and posture track of the mechanical arm are obtained; setting a control period and circularly executing; at each control moment, a generalized Jacobian matrix and system singularity measurement are calculated, and whether the system is close to singularity or not is judged; traversing all the possible values of the base postures if the base postures are close to singularity, calculating joint angle states and corresponding singularity measurement which do not change the tail end postures, and searching a system configuration corresponding to the maximum singularity measurement; then, the state of the mechanical arm is reconstructed, and the mechanical arm is made to move to the maximum singularity measurement configuration to be separated from singularity; and calculating the inverse of the generalized Jacobian matrix to obtain velocity inverse kinematics, and further calculating the joint angular velocity and the joint angle at the next moment. According to the method, an accurate trajectory planning effect without introducing any theoretical error is realized while the singularity avoidance capability is ensured.

The invention relates to the technical field of numerical control machine tool control, and discloses a numerical control rotary table precision compensation method and system based on digital twinning. The method comprises the following steps: constructing a digital twin model of the numerical control rotary table for simulating a deformation behavior under a thermal-mechanical coupling effect; multi-source physical field sensing data such as bearing temperature, servo motor current and rotary table angular displacement are collected in real time; the digital twin model is driven by the sensing data to perform thermal-mechanical coupling simulation, and a comprehensive error prediction value is obtained; generating a compensation trigger signal based on a comparison result of the error prediction value and a preset threshold value; in response to the trigger signal, generating an axis motion feed-forward compensation instruction through inverse kinematics calculation; and the compensation instruction and the original machining instruction are executed after being superposed. Dynamic prediction and active compensation of the precision of the numerical control rotary table are achieved, and the machining precision and stability are effectively improved.

The invention belongs to the technical field of industrial robot motion control, and discloses an industrial robot precise path generation system based on three-dimensional visual reconstruction, comprising an environment sensing device which is composed of a multi-baseline structured light projector and a multi-view camera array and obtains point cloud data through light interference suppression and spectrum correction; the three-dimensional reconstruction processing unit generates a three-dimensional model through rigid transformation and deep learning correction; the geometric feature analysis unit performs curvature analysis and boundary recognition to form region description; the trajectory planning device adopts a weighted B spline to generate a trajectory under curvature constraint and energy optimization; the dynamic correction unit is switched between vision feedback and force feedback according to an error threshold value; the control conversion processor combines inverse kinematics and dynamics compensation and predicts deviation to output a control instruction; and the execution driving mechanism utilizes a servo motor and closed loop feedback to execute actions, so that high-precision generation and stable execution of a track under a complex working condition are realized.

The invention discloses an on-site mixed loading explosive truck hole searching and accurate hole aligning method which comprises the following steps: acquiring a design coordinate set of each blast hole in a to-be-loaded area, acquiring a tail end coordinate of the tail end of a mechanical arm under a geographic coordinate system, and establishing a mechanical arm base coordinate system by taking a base coordinate as an original point; the joint angle and the expansion and contraction amount of the mechanical arm are obtained through iterative inverse kinematics with constraints; controlling the mechanical arm to carry out coarse alignment iteration until the coarse deviation is smaller than a first threshold value; obtaining a fine positioning result of the hole center and the hole axis direction; calculating the fine deviation of the tail end hole aligning assembly relative to the hole center and the hole shaft; after a hole alignment completion signal is output, triggering insertion of a charging conduit and checking of a charging interlocking condition; and when the interlocking condition is met, the charging operation is executed. The GNSS RTK, the laser radar and the 3D structured light camera are fused, quick positioning and alignment of the blast hole are achieved, and the charging efficiency and safety are greatly improved.

The invention relates to an integrated control method for a chassis and a mechanical arm of a mobile robot in an unstructured environment, and belongs to the technical field of robot control, and the method comprises the following steps: S1, obtaining an RGB image, a depth image, the angle of each joint of the mechanical arm and the motion posture of the chassis; s2, extracting multi-modal features of vision, geometry and state, aligning the multi-modal features, and fusing the aligned multi-modal features to obtain fused features; s3, performing action sequence decoding on the fusion features by using an action sequence prediction network to generate a future multi-step coordination action sequence; s4, when the tail end is close to the target, the optimal grabbing pose is estimated, the angles of all joints of the mechanical arm are calculated through inverse kinematics, and the angles are embedded into the cooperative action sequence; and S5, the action sequence is smoothed, and a stable chassis and mechanical arm control instruction is output. The grabbing precision when the chassis inclines in a field scene can be improved, and the terrain adaptability of the robot is improved.

The embodiment of the invention provides a robot, an operation method and device of the robot, a storage medium and a program product. The method comprises the steps that sensing force data of a mechanical arm is received; the external force and the internal force are distributed based on the sensing force data of each mechanical arm in the at least two mechanical arms, so that the corresponding sensing external force and sensing internal force of each mechanical arm are determined; based on the sensing external force and the sensing internal force corresponding to each mechanical arm, the expected external force and the expected internal force of the target object and the expected position of the target object, calculating the force and the position so as to determine the expected position of each mechanical arm; and according to the expected position of each mechanical arm, inverse kinematics solution based on whole-body control is carried out on the robot, so that the joint positions of each mechanical arm and each joint in the waist are determined, and each mechanical arm is controlled to operate the target object based on the joint positions. According to the embodiment of the invention, a multi-arm force control framework based on whole-body control is constructed, the force control effect is good, and the operation stability of the robot can be improved.

The present disclosure provides a method for controlling a humanoid robot. The method comprises identifying a task for the humanoid robot to perform and establishing a safety-related limit. The method includes constructing a phantom inverse kinematics task mathematically derived from the identified task to regularize the robot's pose. The method formulates a combined inverse kinematics problem incorporating the task, phantom inverse kinematics task, and safety-related limit. The method solves the inverse kinematics problem to generate target joint parameters that satisfy the task while remaining within the safety-related limit. The method provides the target joint parameters to actuators to effect physical movement of the humanoid robot.

The invention relates to the technical field of motion capture and space positioning, in particular to an acoustic motion capture method and system based on a receiving end synchronization mechanism. The core innovation of the method lies in that a system structure with a receiving end as a unified time reference is constructed, and asynchronous errors of a traditional transmitting end synchronization architecture are thoroughly eliminated. In order to solve the problems that signals of multiple transmitting nodes are difficult to judge at the same moment, multi-source signals are aliasing and the like, a receiving end synchronous unified time calibration mechanism is adopted, and a mixed signal scheduling scheme combining packet time division multiplexing and intra-group code division multiplexing is adopted. The system comprises a coordinator, an ultrasonic transmitting terminal, an acoustic receiving array and the like, the coordinator provides a global clock through an IEEE 1588v2 protocol and a PPS signal, the transmitting terminal transmits an ultrasonic signal with a unique pseudo-random noise code, the receiving array separates the signal through parallel matched filtering and records an accurate timestamp, and the acoustic receiving array receives the signal through the IEEE 1588v2 protocol and the PPS signal. And finally, high-precision positioning and attitude restoration are realized through a time difference of arrival algorithm, environmental parameter correction and an inverse kinematics model.

According to the automatic measurement system and method for the double-view-field structured light turbine blade, the double-view-field structured light measurement system is constructed, automatic viewpoint planning is carried out based on a turbine blade CAD model, discretization processing is carried out on the turbine blade CAD model to obtain point cloud data, a normal vector clustering algorithm is used for carrying out region segmentation on point cloud, and the point cloud data are subjected to region segmentation; estimating a scanning visual angle direction and a viewpoint position based on a clustering result, calculating displacement of each axis by combining an inverse kinematics model of the three-axis motion platform, and controlling the three-axis motion platform to move to a preset pose; double-view-field structured light hybrid measurement and coordinate system unification are executed, point cloud data obtained through multiple times of measurement are subjected to precise registration, point clouds are unified into an approximate global coordinate system through pose information of a three-axis motion platform, precise registration is conducted on the point clouds through an iterative nearest point algorithm, the splicing precision is improved, and accumulative errors are reduced.

The invention relates to a method and device for a biped robot to wear common sports shoes, and belongs to the technical field of robots. The method comprises the steps that a pre-planned gait track is initialized and generated; calculating the actual centroid position of the robot at each moment; a Kalman filtering algorithm is adopted to fuse multi-source data to update the normal stiffness and the friction coefficient of the sole in real time, and the rate is updated through adaptive gain adjustment parameters; adjusting a zero moment point constraint range, and generating a centroid reference position of a preset step number; establishing a sole characteristic database, training a machine learning model, inputting shoe parameters into the machine learning model, and outputting step length, step frequency and ankle joint rigidity by the machine learning model; an ankle joint target angle and a knee joint target angle are solved through inverse kinematics, and a joint motor is driven in combination with a PD control algorithm and a self-adaptive item; when the vertical acceleration of the IMU sensor is larger than a preset acceleration threshold value, the time period before grounding is judged, and a compliant mode is triggered to control the ankle joint rigidity and the torque borne by the joint.

The invention discloses a mechanical arm self-adaptive variable impedance constant force control system which comprises an inverse kinematics unit, a fractional order active disturbance rejection controller unit, a mechanical arm and a self-adaptive variable impedance controller unit, and the input of the system is a tail end expected position and expected contact force. According to the method, the force overshoot is remarkably reduced, the steady-state error approaches zero, and the force tracking precision and robustness are improved.

The invention discloses a cooperative control method and system for a man-machine cooperative assembly robot based on digital twinning. According to the method, firstly, a digital twinborn simulation environment is constructed in a Unity engine, and mapping of a physical cooperation assembly scene and a virtual scene is achieved; personnel actions and assembled workpiece states are collected in real time through a multi-modal sensing technology, and virtual-real mapping is introduced to realize intention recognition. And then based on a reinforcement learning algorithm, performing path planning on the collaborative robot in a digital twin environment to generate an optimal collaborative path sequence. And finally, mapping the planned path to a real robot control instruction through coordinate transformation and an inverse kinematics algorithm, and dynamically optimizing a motion track by adopting an online self-adaptive strategy. Through the combination of digital twinning and reinforcement learning, the intelligent and flexible scheduling capability of a man-machine cooperation assembly system is improved, the rapid adaptability and assembly precision of the system to unstructured changes are enhanced, and the problems that task programming is tedious and the adaptability is poor in a traditional method are solved.

The invention discloses a humanoid robot two-arm follow-up cooperative control method based on self-adaptive force control, which comprises the following steps of: 1, acquiring three-dimensional models of two arms of a humanoid robot, and establishing forward and inverse kinematics models of the two arms of the humanoid robot; 2, the initial positions of the two arms of the humanoid robot and the target position of a control object are determined, the initial positions and the target positions of the joints and the tail end of the two arms of the humanoid robot are determined, and the positions of joint connecting rods of the two mechanical arms under respective target joint angles in a world coordinate system are calculated; step 3, motion planning of human-shaped two-arm coordination control: carrying out motion planning on the target object in a task space, and then converting the motion into motion of human-shaped two arms; 4, a tight coupling or loose coupling dynamic model of the humanoid double arms and the target object is established, 5, a humanoid double arm controller calculates force and torque of contact points of the tail ends of the humanoid robot double arms and the operation object, and self-adaptive bilateral collaborative admittance control is completed; and step 6, completing double-arm adaptive follow-up cooperative control.

The invention discloses a mechanical arm teleoperation training method based on force feedback, and the method comprises the steps: constructing a hot chamber virtual environment containing a mechanical arm model and an operation object through a scene simulation platform Unity, and configuring a joint position according to a real mechanical arm DH parameter; the dynamics simulation platform AppeliaSim builds a corresponding dynamics model, and an inverse kinematics solution and collision detection function is configured; integrating a force feedback device, and constructing a working space mapping model to convert hand motion into an expected pose of the tail end of the mechanical arm; the double platforms synchronize data through a dynamic link library, and the object control and force sense calculation module calculates collision force and bolt assembling and disassembling torque and transmits the collision force and the bolt assembling and disassembling torque to force feedback equipment. The method does not need to depend on a real mechanical arm, safety risks and high cost are avoided, training repeatability and pertinence are improved, immersion and operation precision are enhanced through force sense and visual sense synchronous feedback, the training period is shortened, and the method is suitable for fine operation training of the mechanical arm in a dangerous environment.

Implementations described herein relate to methods, systems, and computer-readable media to display a virtual character within a virtual environment on a display device. In some implementations, a method can include obtaining an input pose of the virtual character, wherein the virtual character is based on a rig that comprises a plurality of joints, receiving an indication of one or more of a position and an orientation of a target end effector located on the rig, determining an output pose for the rig wherein the determining comprises calculating a respective orientation and position of one or more joints of the plurality of joints of the rig based on the position of the target end effector and rotation constraints of a plurality of joints of a reference rig, and displaying the virtual character in the output pose on the display device.

Implementations described herein relate to methods, systems, and computer-readable media to display a virtual character within a virtual environment on a display device. In some implementations, a method can include obtaining an input pose of the virtual character, wherein the virtual character is based on a rig that comprises a plurality of joints, receiving an indication of one or more of a position and an orientation of a target end effector located on the rig, determining an output pose for the rig wherein the determining comprises calculating a respective orientation and position of one or more joints of the plurality of joints of the rig based on the position of the target end effector and rotation constraints of a plurality of joints of a reference rig, and displaying the virtual character in the output pose on the display device.

The invention discloses a boarding ladder follow-up control method based on multi-visual perception and model optimization, and relates to the technical field of marine equipment, and the method mainly comprises the steps: constructing a feature vector containing real-time motion state information of a ship body; inputting the feature vectors into a hybrid prediction model of which hyper-parameters are optimized through PSO, and obtaining a multi-step six-degree-of-freedom pose sequence and corresponding prediction uncertainty of the ship body; dynamically carrying out weighted fusion on the multi-step six-degree-of-freedom pose sequence and actually measured data based on prediction uncertainty, and carrying out continuous fitting on a track in the window after fusion to generate an end part smooth reference track and a derivative thereof; a feedforward joint torque is obtained through inverse kinematics calculation; feedback joint torque is calculated based on the error between the current pose measured data and the end smooth reference trajectory, and the feedback joint torque and the feedforward joint torque are synthesized and then output to an actuator to drive the boarding ladder to conduct follow-up control. The problem of phase lag caused by traditional pure feedback control is solved.

The invention provides a mechanical arm control method and device, computer equipment and a storage medium, and the method comprises the steps that the target tail end pose and the initial joint angle of a mechanical arm are obtained; based on the target tail end pose, self-motion variables are introduced to parameterize the joint space of the mechanical arm, and multiple sets of candidate joint angles are obtained; constructing a joint motion cost function, and determining the total cost of moving from the initial joint angle to each group of candidate joint angles based on the joint motion cost function; traversing the value range of the self-motion variable, and screening out a solution with the minimum total cost from the multiple groups of candidate joint angles according to the joint motion cost function to serve as an optimal inverse kinematics solution; and a control signal is generated based on the optimal inverse kinematics solution, all joints of the mechanical arm are driven to move, and therefore the tail end of the mechanical arm reaches the target tail end pose. By the adoption of the method, the accuracy, economical efficiency and reliability of mechanical arm control can be improved.

The invention discloses a virtual sensory integration training method based on force feedback, and the method comprises the steps: constructing a hot chamber virtual environment containing a mechanical arm model and an operation object through a scene simulation platform, and configuring a joint position according to a real mechanical arm parameter; the dynamics simulation platform builds a corresponding dynamics model and configures inverse kinematics solution and collision detection functions; force feedback equipment is integrated, and a working space mapping model is constructed to convert hand motion into the expected pose of the tail end of the mechanical arm; the double platforms synchronize data through a dynamic link library, and a force sense calculation module calculates collision force and bolt assembling and disassembling torque and transmits the collision force and the bolt assembling and disassembling torque to force feedback equipment. The method does not need to depend on a real mechanical arm, safety risks and high cost are avoided, training repeatability and pertinence are improved, immersion and operation precision are enhanced through force sense and visual sense synchronous feedback, the training period is shortened, and the method is suitable for fine operation training of the mechanical arm in a dangerous environment.