600 results about "Robot locomotion" patented technology

The invention discloses a robot obstacle avoidance method and system based on millimeter wave radar sparse point cloud, and relates to the technical field of obstacle avoidance recognition. A robot obstacle avoidance system based on millimeter wave radar sparse point cloud comprises a point cloud acquisition module, a negative obstacle identification module, a weak obstacle identification module, a point cluster identification module, a risk map module, a tentative verification module and an obstacle avoidance decision module. According to the invention, suspected obstacle point clusters are extracted based on a reflection intensity threshold and a spatial proximity relation in an enhanced point cloud, a theoretical parallax model of a real static obstacle is constructed under the constraint of a robot motion trajectory, and Doppler velocity distribution of each frame is combined with a static obstacle Doppler physical law for comparison. And classifying the point clusters which do not meet the multi-view geometric consistency or Doppler physical law, and distinguishing multipath false point clusters from dynamic point clusters.

The invention discloses a visual prediction method for space-time manifold and implicit state deduction of a robot, and relates to the technical field of robot space visual perception. The motion state and the visual image of the robot are collected; calculating carrier pose offset and generating a reverse compensation matrix; modeling an image target into a visual cone probability manifold, and extracting an explicit manifold observation vector; monitoring the confidence coefficient in real time through an observation quality evaluation network, and activating an implicit deduction mode during observation degradation; reading historical time sequence characteristics by using an improved Transform model, and performing prediction and deduction on a future nonlinear motion state of the target; performing coordinate correction and probability field decoding on a prediction result in combination with the reverse compensation matrix, and outputting a three-dimensional prediction trajectory and a spatial covariance ellipsoid; according to the method, the problem that traditional visual tracking fails under the conditions of violent shaking of a carrier and target shielding is solved, and continuous and foresight physical scale positioning and safety decision making of a robot on a dynamic target are achieved.

The invention discloses a robot trajectory planning method for a spraying production line, a robot spraying control method and a robot trajectory planning device.The trajectory planning method comprises the steps that model surface information is extracted, an extracted surface geometric figure is processed, and a surface spraying path and a connection transition path between surfaces are generated; and finally, generating a collision-free and full-coverage complete spraying motion path. According to the robot spraying control method, an optimal solution is selected by using an optimization algorithm to plan and control robot movement, so that the robot spraying quality is improved while the stability of a robot movement track is ensured; the robot trajectory planning device provides a workpiece conveying module and a robot and is used for applying the robot trajectory planning method to real spraying production line hardware.

The invention discloses a robot hand-eye calibration method, control equipment and a robot system, and relates to the technical field of robots. The robot hand-eye calibration method comprises the following steps: uniformly correcting a plurality of pixel coordinates obtained by dynamic shooting to a reference pixel coordinate system which is consistent with a camera coordinate system at a reference position in direction; and meanwhile, the world coordinates of the end effector corresponding to each sampling position are localized relative to the world coordinates of the end effector at the reference position, so that interference caused by global coordinate offset and camera orientation difference is eliminated, and the application range of the hand-eye calibration method is expanded. Besides, a singular value decomposition algorithm is adopted to solve a mapping relation between pixel coordinates and local world coordinates under a reference pixel coordinate system, so that a solved rotation matrix can meet orthogonality constraints, the hand-eye transformation process strictly conforms to a robot motion model with translation and rotation motion, and the calibration precision is improved. The calibration process can be automatically calculated and completed, and the calibration efficiency is high.

The invention discloses a position and posture compensation method for guiding installation of a contact network cantilever based on 3D vision and an automatic installation system. The position and posture compensation method comprises the steps that the spatial transformation relation between a 3D vision sensor coordinate system and a robot coordinate system is determined; the robot is controlled to move, and the three-dimensional point cloud data of the to-be-installed cantilever component and the three-dimensional point cloud data of the field installation foundation are collected; the collected three-dimensional point cloud data is registered with a corresponding preset CAD model, and a first real-time pose of the cantilever component in a robot coordinate system and a second real-time pose of the installation foundation in the robot coordinate system are obtained through calculation; calculating a pose compensation transformation quantity based on a pre-stored theoretical mounting pose of the cantilever, the first real-time pose and the second real-time pose; and according to the pose compensation transformation amount, planning and executing a motion track of the robot, and completing butt joint installation. The method is high in compensation precision, robustness and adaptability and high in construction efficiency, and the problem of uncertainty in automatic installation is fundamentally solved.

The invention discloses a double-foot wheel-legged robot pose control method and device based on hierarchical cooperative control, a medium and a product, and relates to the field of robot control, and the method comprises the steps that a hierarchical cooperative control framework is constructed; the layered cooperative control framework comprises a balance controller and a whole body attitude controller; the balance controller determines a reference wheel joint driving torque based on a simplified inverted pendulum dynamic model according to the pose information of the upper mass center of the biped wheel-leg robot; the whole-body attitude controller performs optimization control on all joints of the biped wheel-leg robot by adopting an incremental model prediction control algorithm combined with a reference wheel joint driving moment based on a whole-body dynamic model; state information of the biped wheel-legged robot is obtained; according to the state information, a driving torque instruction of each joint is obtained based on a hierarchical cooperative control framework; and driving the double-foot wheel-leg robot to move according to the driving torque instruction of each joint. The precision, robustness and real-time performance of robot motion control can be improved.

The invention provides a movement control method, system and device for adaptively following a target object and a medium, and belongs to the field of robot automatic control, and the method comprises the steps: obtaining the motion state information of a robot, the obstacle information of the surrounding environment and the position information of the target object; generating a prediction track of the dynamic obstacle based on the dynamic obstacle information, and constructing a risk area according to the static obstacle information and the prediction track; sampling by adopting a dynamic window algorithm to obtain a plurality of groups of candidate speed pairs and generating a plurality of candidate tracks; on the basis of candidate trajectories, the risk area and the predicted trajectory of the dynamic obstacle, a trajectory risk evaluation value is obtained through calculation; and based on a preset evaluation index, scoring the candidate trajectory, selecting an optimal speed pair according to a scoring result, and based on the optimal speed pair and the current actual speed of the robot, generating a control instruction to drive the robot to move. The autonomous following performance and the user experience of the robot in the dynamic environment are improved.

The invention discloses a dual-drive self-switching strong-adaptability quadruped robot motion control method, which comprises the following steps of: estimating current topographic features by using sensing signals such as body state feedback, IMU (Inertial Measurement Unit) and sole force, and predicting a falling probability according to the topographic features, so that a quadruped robot is intelligently switched between two driving modes of MPC (Moving Picture Control) independent control and MPC-DRL (Moving Picture Control-Digital Regulation Language) cooperative control; dynamic behavior parameters are introduced to influence the gait and step height of robot movement, the optimization efficiency and smoothness of MPC and the disturbance adaptive capacity of DRL are efficiently fused, and the high-robustness, high-efficiency and self-adaptive movement capacity of the quadruped robot in various terrains under the condition that external sensing information is not relied on is enhanced.

The invention provides a ship active stabilization control method and system, and relates to the field of ships. The ship active stabilization control system comprises a stabilization execution mechanism which comprises an upper platform constructed according to a ship body of a ship and a lower platform constructed according to multiple sets of water pressing plate execution mechanisms, and the multiple sets of water pressing plate execution mechanisms are arranged at any positions below waterlines of the two sides of the ship correspondingly; each water pressing plate executing mechanism comprises a water pressing plate assembly and a driving cylinder connected with the water pressing plate assembly; the data acquisition unit is configured to acquire ship body attitude and motion state information and environment data of the ship; the stabilization controller is configured to calculate and generate correction torque according to the parallel robot kinematic mechanics mechanism model, the ship posture and motion state information and the environment data, and distribute the correction torque to an execution instruction corresponding to each driving cylinder; and the driving cylinders drive the corresponding water pressing plate assemblies to execute water pressing movement or return movement according to the execution instructions.

The invention discloses a GIS in-place robot coordination control method with a posture correction function, and belongs to the technical field of robot coordination control. The method comprises the following steps: establishing a 2D-3D coordinate mapping corresponding relation; fusing the corresponding relation with an operation state predicted by an IMU-based inertial measurement and system dynamics model; performing error calculation on the obtained 6D pose information and target pose information; constructing a nonlinear kinetic equation of the robot, and converting a control target into an optimization problem of various constraints; and converting the obtained control instruction into a torque signal for actually driving the robot to move. According to the method, the influence of mismatching on pose estimation is effectively inhibited by establishing the 2D-3D coordinate mapping relation; through a joint torque PID control algorithm, the torque required by each joint is calculated in real time, and high-precision tracking of an expected trajectory is realized; an MPC optimization control framework with multiple constraints is constructed, and precise, smooth and safe coordination control over the GIS in-place process is achieved.

The invention discloses a robot obstacle avoidance method and device for a dynamic unstructured environment, equipment and a medium, is applied to a target robot, and relates to the technical field of computers, and the method comprises the steps: carrying out the feature fusion of collected multi-modal environment data of the dynamic unstructured environment, so as to obtain an environment perception data set; analyzing the environment perception data set through a pre-training semantic model to generate an environment evaluation report corresponding to the environment perception data set; generating an initial path reaching the target point based on the current pose information of the target robot and the environment evaluation report, and performing obstacle avoidance optimization on the initial path through the environment evaluation report to obtain an optimized path; and the optimized path is converted into a robot motion instruction, and a target point is reached by executing the robot motion instruction. Therefore, synergy of semantic-level obstacle understanding and path optimization in a dynamic unstructured environment can be realized, and the scene adaptation limitation of the traditional technology is broken through.

The invention relates to the technical field of robot control, in particular to a robot autonomous navigation method and device, a robot and a computer readable storage medium, and the method comprises the following steps: obtaining real-time body state information, a current position, a target position and depth perception information of an external environment of the robot; encoding the depth perception information, and splicing the encoded depth perception information with the real-time body state information to obtain unified features representing the external environment and the state of the robot; inputting the unified feature and the target position into a preset navigation decision model to generate a preliminary movement speed of the robot; the linear distance between the current position and the target position is calculated in real time, the initial movement speed is adjusted based on the linear distance, and a stable expected speed parameter is obtained; and according to the stable expected speed parameter and the real-time body state information, generating an execution instruction for driving the robot to move and controlling execution, and navigating to a target position to realize autonomous navigation of the robot in a map-free scene.

The leg device comprises a leg structure, a joint assembly, a heat conduction strip and / or a heat dissipation protection sheath wrapping a thigh shell, the joint assembly comprises a knee joint driving mechanism, and the knee joint driving mechanism is provided with a knee joint driving output end arranged in a joint connecting channel; the heat conduction strip is of a sealed cavity structure and is filled with heat conduction liquid, the heat conduction strip comprises a first heat conduction section and a second heat conduction section which are connected with each other, and the first heat conduction section is attached to the side, close to the thigh shell, of the knee joint driving mechanism; the second heat conduction section is attached to the inner side wall of the thigh shell and extends from the first heat conduction section to the shank component. According to the leg device, heat dissipation is achieved through the combination of the heat conduction strips and the leg shell, so that the overall structural arrangement of the leg device is more compact and smaller, the weight is lighter, the energy consumption of the robot can be reduced, and the movement flexibility and the response speed of the robot are ensured.

The invention relates to the technical field of robot motion control and trajectory planning, in particular to a robot motion trajectory planning method based on AI reinforcement learning. The method comprises the following steps: acquiring robot workspace layout information and an environment sensing probe candidate list, performing probe configuration planning, calibration and planning session index generation, and generating a planning session primary key recording structure; executing multi-source observation acquisition scheduling, data alignment and three-dimensional grid modeling, and generating a reinforcement learning state basic structure; state vector construction and continuous action strategy inference are carried out, and a candidate motion track set structure is generated; and track rolling simulation, grid collision risk assessment, multi-target reward calculation, target track selection and strategy parameter updating are carried out to generate a strategy network parameter set structure. Through combination of multi-source perception and reinforcement learning, intelligent planning of the motion trail of the robot is realized, the safety and efficiency of the trail are improved, and the adaptability and robustness in a dynamic environment are enhanced.

The invention belongs to the technical field related to robot motion control, and provides a robot motion control method and system in a microgravity environment in order to solve the problems of stability and sand blowing of robot motion under existing microgravity. A robot swing stage is divided into three sub-stage motions, and a robot foot end expected track is generated for each sub-stage motion; the robot state information, the historical track and the environment information are input into a pre-constructed joint control model, and a joint control instruction of the robot in the microgravity environment is obtained through prediction; the joint control model is a strategy network model trained in a reinforcement learning mode; the trajectory tracking reward is determined by the actual position of the robot and the expected position of the foot end of the robot. Stable, low-disturbance and high-efficiency movement of the robot in the microgravity environment is achieved, and meanwhile the sand blowing phenomenon is effectively restrained.

The invention provides a humanoid robot motion test platform, which comprises a base, a belt-type motion mechanism, a height adjusting device and a control system, and is characterized in that the height adjusting device comprises a linear driving mechanism of which the bottom is hinged to the base; the first sliding mechanism is connected with the output end of the linear driving mechanism; the second sliding mechanism is in sliding fit with the first sliding mechanism and is connected with the test platform; and the brake mechanism is used for limiting relative movement of the two. During slope changing, the two sliding mechanisms slide relatively to automatically compensate the space horizontal displacement difference, and lateral stress interference is eliminated; the high-frequency large-load stepping impact of the robot can be effectively resisted, the step loss of the system is prevented, and the unification of smooth slope change and high-rigidity and high-precision testing is realized.

The invention provides a motion control method and device of a foot type robot, equipment and a medium. The method comprises the steps that state information, coding information and historical actions of the foot type robot at the previous moment and first sensing information at the current moment are obtained; inputting the state information of the previous moment, the coding information and the historical actions into a world model to obtain the state information of the current moment output by the world model; inputting the state information at the current moment and the first sensing information into a motion strategy model to obtain a target action at the current moment output by the motion strategy model; and controlling the movement of the foot type robot according to the target action at the current moment. Any terrain environment can be accurately sensed, so that the stability of the foot type robot in the movement process is ensured, the problems of falling or movement faults and the like are avoided, and the movement control effect of the foot type robot is improved.

The invention provides a quadruped robot wet-slippery rugged terrain motion control method based on explicit and implicit estimation, and aims to solve the problem that the motion ability of a quadruped robot under the wet-slippery rugged terrain is limited due to the fact that the existing method cannot fully extract environment and robot motion state information. Historical observation information and a current action are utilized to explicitly estimate an environment friction factor, a four-foot contact state and a robot centroid velocity, and current motion model information of the robot is implicitly estimated through a method of predicting a motion state at a next moment. Environmental information, robot motion information and implicit vectors containing robot motion model information are introduced into input of a motion strategy, higher sensing capacity for the motion state and the environment is provided for a motion network, and a novel control method suitable for the quadruped robot to move in the slippery terrain is obtained.

The invention discloses an automatic laying and forming process for a reinforcing ring of a carbon fiber fully-wound gas cylinder end socket, and relates to the technical field of carbon fiber wound gas cylinders. Technological parameters are simulated and optimized; the laying line type is imported into software to plan the motion track of the robot; carbon fiber prepreg is adopted, single-layer prepreg laying is conducted between every two spiral layers of the gas cylinder according to the optimal process parameters, and the laminating state of the prepreg is monitored in real time. Full-automatic precise laying can be achieved, and the production efficiency and consistency are improved; the material utilization rate is improved; the manufacturing cost is reduced; the laying wrinkle defect is eliminated, and the gas cylinder bearing safety is improved; process parameters are quantified and optimized, and the performance of the carbon fibers is fully released.

The embodiment of the invention provides a robot process path data processing method and device based on geometrical characteristics, and the method comprises the steps: obtaining a process template according to the geometrical characteristics of a workpiece and a set process association rule base, and the process template comprises a process sequence and associated process parameters; extracting process sequence keywords, performing algorithm matching with a process path algorithm library to obtain a path generation algorithm, generating an initial robot motion path according to the path generation algorithm and geometric features, and performing path constraint based on process parameters; constructing a hierarchical bounding box tree structure of an obstacle, performing route interference condition detection on an initial robot motion path and the hierarchical bounding box tree according to a ray projection method, if a collision condition occurs, iteratively calculating an obstacle avoidance path offset based on a gradient descent algorithm, and recording a normal vector at a collision point to obtain a correction direction; and correcting the initial robot motion path according to the obstacle avoidance path offset and the correction direction. The robot process path planning method and device can improve the efficiency and accuracy of robot process path planning.

The invention relates to the technical field of humanoid robots, and discloses a humanoid robot waist and crotch structure which comprises a waist support and a crotch connecting frame and further comprises a first motor and a second motor, the first motor is symmetrically installed on the waist support, and the second motor is installed on the crotch connecting frame. The second motor is used for driving the waist support and the crotch connecting frame to rotate relatively; the waist swinging assembly is arranged between the output ends of the first motors and the output ends of the second motors, when the two first motors synchronously rotate in the same direction, the waist support swings left and right along the crotch connecting frame, and when the two first motors asynchronously or reversely rotate, the waist support swings front and back along the crotch connecting frame; the number of driving units can be reduced, the control coordination difficulty can be reduced, the transmission efficiency loss can be reduced, the motion precision of the robot can be ensured, the weight and cost of the structure can be reduced, and multi-directional fast and smooth switching and combination can be realized.

The invention provides a teleoperation method and a robot. The method comprises the following steps: receiving operator attitude data sent by an inertial measurement unit IMU system; according to the operator attitude data, target attitude data of the humanoid robot are determined, and the target attitude data comprise the tail end target pose and the target arm angle of the seven-degree-of-freedom mechanical arm; the arm angle is a dihedral angle between a plane where the shoulder part, the elbow part and the wrist part of the seven-degree-of-freedom mechanical arm are located and a target pose and a target arm angle surface of a reference flat tail end; according to the target posture data, motion parameters of all joints of the humanoid robot are determined; and generating a control instruction according to the motion parameters. By means of the method, the uncertainty of null-space motion can be effectively eliminated, and the robot motion is more personified.

The invention relates to the technical field of robot control, and provides an underwater robot motion active-disturbance-rejection control method and system, a medium and equipment, and the method comprises the steps: estimating the total disturbance of an underwater robot through a dynamic gain adaptive extended state observer based on motion state data and environment disturbance data, and generating a disturbance compensation amount according to the total disturbance; in combination with the control target value and the disturbance compensation amount, a control signal of each propeller is calculated through an active-disturbance-rejection control law; on the basis of the control signal, driving each propeller of the underwater robot to act so as to realize posture adjustment and position control of the underwater robot; the working current of the propeller and the water flow speed of the environment are obtained, the current movement working condition of the robot is judged, and the observation gain and the control law feedback coefficient of the expansion state observer are automatically adjusted. The response speed is increased while the control stability is ensured, and different motion working conditions are adapted.

The invention relates to a robot positioning method, device and equipment, a readable storage medium and a program product, and relates to the technical field of robot control. Comprising the following steps: acquiring environment observation data in a motion process of a target robot, first motion observation data representing an inertial motion increment of the target robot and second motion observation data representing a displacement increment of the target robot; performing joint initialization processing on the environment observation data with the first motion observation data and the second motion observation data to obtain a first environment scale parameter and a second environment scale parameter; fusing the first environment scale parameter and the second environment scale parameter to obtain a physical environment scale parameter; based on the physical environment scale parameters, converting the environment observation data into target environment observation data with physical size attributes; and fusing the target environment observation data, the first motion observation data and the second motion observation data to obtain a robot positioning result. The method can improve the positioning precision of the electric power inspection robot.

The invention discloses a vibration suppression and stability control method in the movement process of an industrial robot, and relates to the field. The method comprises the following steps of S1, constructing a robot motion digital twinborn body, S2, performing offline simulation optimization and parameter library construction, S3, performing online real-time data acquisition and transmission, S4, performing digital twinborn body comparison and parameter calling, and S5, performing closed-loop control execution and parameter iterative updating. According to the method, the digital twinborn body comprising the robot body model, the load model and the environment model is constructed, accurate optimization of control parameters under different working conditions is achieved by combining off-line simulation optimization and parameter library construction, the online real-time data acquisition and transmission system performs noise reduction processing on heterogeneous data through a multi-source information fusion algorithm, and the real-time performance of the system is improved. According to the method, the accuracy of data is ensured, a digital twin comparison and parameter calling mechanism can quickly call or generate an adaptive optimal control parameter when the vibration of the physical robot exceeds a threshold value, and the vibration is effectively inhibited.

Approaches presented herein provide for predictive control of a robot or automated assembly in performing a specific task. A task to be performed may depend on the location and orientation of the robot performing that task. A predictive control system can determine a state of a physical environment at each of a series of time steps, and can select an appropriate location and orientation at each of those time steps. At individual time steps, an optimization process can determine a sequence of future motions or accelerations to be taken that comply with one or more constraints on that motion. For example, at individual time steps, a respective action in the sequence may be performed, then another motion sequence predicted for a next time step, which can help drive robot motion based upon predicted future motion and allow for quick reactions.

The invention relates to a robot path planning method and system based on optical vision. The robot path planning method comprises the following steps: acquiring an environment image of an environment where a robot is located and robot motion information; based on the environment image, a dense three-dimensional point cloud map is obtained through contrast enhancement, signal extraction, decoding and interpolation optimization; based on the dense three-dimensional point cloud map and the color RGB visible light environment image, generating a three-dimensional point cloud map with semantic tags through background elimination, image tracking, semantic recognition and clustering; estimating the motion state of the robot based on the three-dimensional point cloud map with the semantic tag and the motion information of the robot, carrying out global and local path planning, and obtaining a local path through track smoothing; and converting the local path into the actual action of the robot in combination with the motion state of the robot. According to the invention, through the collaborative design of the active optical visual perception architecture and multiple algorithms, the balance between cost control and performance improvement is effectively realized.

The invention belongs to the technical field of path planning and robot motion planning, and particularly relates to a multi-strategy fusion improved RRT * sampling planning method and device and a storage medium, and the method comprises the steps: constructing a dual-search tree through a starting point and a target point in a three-dimensional working space, and selecting a to-be-expanded search tree through a random mode; halton-Bridge mixed sampling is adopted to generate sampling points, so that the global coverage uniformity is improved, and the narrow channel sampling capability is enhanced; calculating the dynamic step length of the exponential decay based on the local obstacle proportion; adopting a hierarchical guidance expansion strategy, preferentially expanding towards a target, introducing an improved artificial potential field to guide expansion when the expansion fails, and taking the bottom with random expansion; performing RRT * neighborhood father node reselection and reconnection optimization on the new node; greedy pruning, self-adaptive interpolation and cubic B-spline smoothing are carried out on a path after the double trees are connected, and an executable smoothing track is output; according to the scheme, planning efficiency, success rate and path quality are improved.

The invention discloses an intelligent robot trajectory planning method and system based on visual inspection. The method comprises the following steps: acquiring obstacle motion state data through a sensor array, performing time alignment and multi-modal fusion, and constructing an initial state vector; iteratively updating the state by adopting a particle filter algorithm, and generating a smooth trajectory sequence through continuity correction and time sequence integration; determining a potential collision area based on polynomial fitting, and performing extension to obtain a predicted collision boundary; extracting passable grids to construct a dynamic risk map, screening low-risk routes, and sequencing to determine an optimized path; performing correction according to deviation feedback by simulating a forward verification path to generate a final execution instruction; state deviation is continuously monitored in the execution process, and the control scheme is dynamically adjusted. According to the invention, real-time trajectory planning and intelligent path optimization of the robot in a dynamic obstacle environment are realized, and the movement safety of the robot is remarkably improved.

The present application belongs to the technical field of robot control, and particularly relates to a stability judgment method of a robot system variable impedance model using a variable augmented matrix, which enables the robot to verify its stability offline when the stiffness changes. Impedance control is a general force control scheme suitable for various manipulator tasks, one of which is human-robot collaboration: the manipulator performs force-position hybrid control on the object according to the impedance control law, while the operator applies control force to the object or the robot to realize human-robot collaboration and complete work such as assembly, carrying, etc. According to different manipulator tasks, variable stiffness parameters can be used to reflect flexibility and compliance. Not only can the dynamic relationship between external force and robot motion be controlled, but also these dynamic behaviors can be flexibly changed in a continuous manner during the task. Impedance control can be implemented in joint coordinates, Cartesian coordinates or other task-specific coordinates. Impedance targets can be achieved in different ways.