803 results about "Landing point" patented technology

A control method and system for precise landing of an unmanned aerial vehicle. The method comprises the following steps: on the basis of a multi-sensor fusion technique, using a lidar and a stereo vision algorithm to collect environmental data and perform primary processing, and generating comprehensive environmental perception data (step S1); on the basis of the comprehensive environmental perception data, using a digital elevation model algorithm to re-construct a three-dimensional terrain of a landing area, and generating a three-dimensional terrain model (step S2); on the basis of the three-dimensional terrain model, using an A* search path-planning algorithm to perform risk assessment and plan a safe landing path, and generating an optimized landing path (step S3); on the basis of the optimized landing path, using an adaptive control algorithm to adjust a flight attitude in real time by means of a fuzzy logic controller, and generating flight parameter adjustment (step S4); on the basis of the flight parameter adjustment, using machine vision and a decision tree algorithm to execute autonomous obstacle avoidance and emergency response, and generating a safe landing execution scheme (step S5); and on the basis of the safe landing execution scheme, using an ultrasonic sensor and a ground feedback system to confirm and fine-adjust a landing point, and completing final landing confirmation (step S6).

The invention relates to the field of unmanned aerial vehicle automation, in particular to a three-dimensional modeling and unmanned aerial vehicle landing area address selection method based on laser point cloud data. The method comprises the steps of collection and dynamic compensation of laser radar point cloud data, multi-scale adaptive registration of three-dimensional point cloud, topographic feature extraction and evaluation, selection of an optimal landing point, path planning based on an improved A algorithm, and real-time environmental data updating and dynamic adjustment mechanism. According to the method, point cloud data is dynamically compensated through Kalman filtering, a 3D-NDT algorithm is utilized to perform high-precision three-dimensional environment modeling, key topographic features are extracted through an RANSAC algorithm to comprehensively evaluate topographic complexity and safety distance, an optimal landing point is selected, an optimal path of an unmanned aerial vehicle is planned in combination with an improved A algorithm, and path safety and flight energy efficiency are ensured. By updating environment data in real time and dynamically adjusting a flight path and a landing point, the unmanned aerial vehicle is adapted to sudden environment changes, and safe and stable autonomous landing of the unmanned aerial vehicle in a complex and changeable environment is ensured.

The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle parking apron dynamic landing point adjustment method and system based on environment awareness, and the method comprises the steps: obtaining environment data and flight parameters, constructing a three-dimensional terrain grid model, and analyzing the stability; loading obstacle data and path constraints to generate a comprehensive evaluation model, and simulating to obtain regulation and control data; training the model to generate initial adjustment parameters, and combining the parameters with the model to obtain dynamic adjustment simulation information; constructing a multi-path optimization model to obtain optimal parameters; and combining real-time sensing to generate a safety probability, and adjusting a landing strategy. The system comprises a data acquisition module, a terrain modeling module and the like. According to the scheme, intelligent optimization and real-time adjustment of a landing point are realized through multi-dimensional environment perception and dynamic modeling, the landing safety and reliability of the unmanned aerial vehicle in a complex environment are improved, and the method is suitable for an intelligent landing scene of the unmanned aerial vehicle.

The invention provides a mine hole inspection unmanned aerial vehicle based on a laser radar and UWB distance measurement and a positioning system, and relates to the technical field of mine hole unmanned aerial vehicle inspection. Through the 360 laser radar and UWB distance measurement, the system can adapt to unmanned aerial vehicle positioning in the mine hole environment, so that the unmanned aerial vehicle can safely fly in the mine hole environment in which the light is dark and flying dust spreads due to the fact that the unmanned aerial vehicle is closed all the year round, the unmanned aerial vehicle is accurately positioned and lands in the preset hangar when necessary, the key problem that the unmanned aerial vehicle autonomously inspects in the mine hole is solved, and the unmanned aerial vehicle safety is improved. And the application scene of the unmanned aerial vehicle system under the inspection task is expanded. According to the invention, the position and attitude of the unmanned aerial vehicle under the launching inertial system are obtained through the laser radar for feedback control of the position and speed control module, and the distance between the unmanned aerial vehicle and the UWB base station is obtained to obtain the approximate position of the unmanned aerial vehicle in a mine and obtain the relative position relation with the hangar, so that the unmanned aerial vehicle can preliminarily position a landing point, and the unmanned aerial vehicle can be accurately located. And the subsequent unmanned aerial vehicle can be accurately positioned and landed in the preset hangar.

The invention relates to a dynamic cooperative path planning and autonomous landing control method for an unmanned aerial vehicle and an unmanned ship, and the method comprises the following steps: collecting the state data of the unmanned ship and the unmanned aerial vehicle and the high sea condition environment data, and carrying out the data fusion processing; an improved fast extended random tree algorithm is adopted to plan a safe navigation path for the unmanned ship, the generated path of the unmanned ship is optimized based on an unmanned ship motion model considering environmental interference, and a model prediction control algorithm is adopted to plan a path for the unmanned ship to fly to a predicted landing point of the unmanned ship. Dynamic cooperation between the unmanned ship and the unmanned aerial vehicle is realized through information interaction between the unmanned ship and the unmanned aerial vehicle; the unmanned aerial vehicle recognizes an unmanned ship landing identifier through a visual servo guide system, calculates the position and attitude deviation relative to a landing point, adjusts flight control parameters according to interference conditions by using an adaptive control algorithm, and performs trajectory prediction compensation in combination with an unmanned ship motion model to realize autonomous landing. Compared with the prior art, safe landing of the unmanned aerial vehicle on the unmanned ship under the high sea condition is achieved.

The invention discloses an aircraft landing method and system and a vertical take-off and landing aircraft, and relates to the technical field of aircraft control, and the aircraft landing system comprises a landing path planning module which is used for responding to a landing instruction, determining a target landing point of the aircraft, and planning a landing path of the aircraft to obtain the landing path of the aircraft; the trajectory prediction module is used for predicting the flight trajectory of the aircraft based on the flight state information of the aircraft to obtain a predicted flight trajectory; the re-flight decision module is used for evaluating the flight state of the aircraft in the tilting transition stage based on the landing path and the predicted flight path; and according to the first evaluation result, carrying out re-flight decision processing on the aircraft, and determining whether to control the aircraft to carry out re-flight so as to guarantee safe landing of the aircraft. According to the scheme, the automatic landing capability of the aircraft can be effectively improved, and meanwhile, the landing safety of the aircraft is ensured through the re-flight decision module.

The invention discloses an unmanned aerial vehicle take-off and landing site selection method for urban end logistics, and relates to the technical field of facility site selection, and the method comprises the following steps: S1, obtaining a building contour of a region to be subjected to site selection, and constructing a customer buffer region according to the building contour; s2, based on the customer buffer area, performing noise analysis and safety analysis on the unmanned aerial vehicle, and constructing an overall restricted area; and S3, based on the overall restricted area, constructing a target function taking the lowest cost as an optimization target, a target function taking the highest satisfaction as an optimization target and a plurality of constraint conditions, and obtaining a site selection layout result. According to the method, the applicability of the grid map method in the complex urban environment is verified, and a new thought is provided for the layout of the urban logistics unmanned aerial vehicle take-off and landing points.

The embodiment of the invention provides an unmanned aerial vehicle landing system, an unmanned aerial vehicle landing control method and an unmanned aerial vehicle, the system comprises an unmanned aerial vehicle, a hangar monocular vision sensor and a hangar radar, the unmanned aerial vehicle comprises an unmanned aerial vehicle monocular vision sensor and a processor, and an unmanned aerial vehicle state machine runs on the processor. The hangar monocular vision sensor and the hangar radar are mounted on the hangar; a hangar two-dimensional code is arranged on the hangar, and a landing point is arranged on the hangar two-dimensional code; the unmanned aerial vehicle monocular vision sensor is used for determining a first pose of the unmanned aerial vehicle monocular vision sensor relative to the landing point; the hangar monocular vision sensor is used for determining a second pose of a marker on the unmanned aerial vehicle relative to the landing point; the hangar radar is used for determining the position of the unmanned aerial vehicle; and the unmanned aerial vehicle state machine is used for generating a control instruction according to the first pose, the unmanned aerial vehicle position and the second pose, and controlling the unmanned aerial vehicle to land to the landing point according to the control instruction. According to the invention, the problem that the unmanned aerial vehicle cannot land accurately is solved.

A legged robot motion control method includes: acquiring centroid state data of a spatial path start point and a spatial path end point of a motion path; determining a target landing point of afoot of the legged robot in the motion path based on the spatial path start point and the spatial path end point; determining a change relationship between a centroid position change coefficient and a foot contact force based on the centroid state data; selecting, under constraint of a constraint condition set, a target centroid position change coefficient that meets the change relationship; the constraint condition set including a spatial landing point constraint condition; determining a target motion control parameter according to the target centroid position change coefficient and the target landing point of the foot; and controlling, based on the target motion control parameter, the legged robot to perform motion according to the motion path.

The invention relates to an amphibious unmanned vehicle amphibious actuator cooperative control method, belongs to the technical field of amphibious unmanned vehicles, and solves the problem of poor adaptability of amphibious unmanned vehicles in different scenes in the prior art. The method comprises the following steps: acquiring suspension state data and attitude angle data of the amphibious unmanned vehicle at each moment; at the current moment, predicting the overwater model mismatch probability based on the trained recurrent neural network according to the suspension state data and the attitude angle data at the current moment and the historical moment; determining whether the current scene key point is a scene key point based on the predicted overwater model mismatch probability; the scene key points comprise a landing point, a water leaving point, a water entering point and a full floating point; and calculating an actuating mechanism action instruction of the amphibious unmanned vehicle according to whether the current key point is the scene key point or not and the predicted overwater model mismatch probability. And stable control of the amphibious unmanned vehicle under the land and water working conditions is realized.

The invention discloses an unmanned aerial vehicle autonomous address selection method based on terrain evaluation and approach cost analysis, and relates to the technical field of unmanned aerial vehicle autonomous address selection. After the unmanned aerial vehicle receives a landing instruction in an unknown environment, the geometric safety of the terrain and the cost problem of the approach path can be comprehensively considered, and the landing point selection strategy of the unmanned aerial vehicle is optimized from the global perspective. Firstly, semantic segmentation is performed on an RGB image acquired by a visual sensor through deep learning to acquire a semantic image, then point cloud data acquired by a laser radar and the semantic image are fused to acquire a three-dimensional semantic point cloud, and a terrain safety area conforming to terrain geometric feature constraints is screened out on the basis of considering semantic tags. And finally, calculating the cost of the linear approach path of each candidate landing point in the terrain safety area through traversal, and screening out the landing point with the optimal comprehensive cost, thereby improving the accuracy and practicability of terrain safety area identification. According to the method, an unreachable or high-risk area is avoided, and the global point selection optimization effect is improved.

An unloading control system accesses a weight / mass versus position fill profile for an identified container. The unloading control system generates control signals to position the material transfer vehicle so that an initial landing point of material in the container is at a desired positioned based upon the fill profile. The unloading control system generates control signals to unload material into the container according to the weight / mass versus position fill profile and obtains an indicated of the weight / mass of material transferred. The control system generates control signals to control the landing point of material in the container based upon the fill profile and the weight / mass of material transferred.

The invention discloses a low-altitude airspace planning method and system based on a micro-terminal area, and relates to the field of low-altitude airspace planning, and the method comprises the steps: generating a corresponding take-off and landing area for a low-altitude take-off and landing point or a take-off and landing field, and generating a take-off and landing hub area for an adjacent take-off and landing point or a take-off and landing field, so as to construct the micro-terminal area of the low-altitude airspace; constructing a risk area, and forming a restricted area of the low-altitude airline network together with the control area and the no-fly area; on the basis of the restricted area, generating alternative intermediate points connected with the take-off and landing points or the take-off and landing fields; based on the data of the alternative intermediate points and the data of the micro-terminal area, constructing an initial low-altitude airline network connected with all the points; calculating a weight corresponding to each side line in the initial low-altitude airline network, and optimizing the initial low-altitude airline network based on a weighted network; and removing redundant intermediate points based on the optimized network, constructing access points of the airline network and each micro-terminal area, and generating a final low-altitude airline network. According to the invention, a more reliable technical basis is provided for low-altitude route network planning.

An agricultural harvester has a frame and a spout that is mounted to the frame. A target landing point indicates a position in a receiving vehicle where material is intended to land. A control system detects an actual landing point and automatically controls the spout based on a difference between the actual landing point and the target landing point.

The invention discloses a projectile drop point detection method, system and equipment based on dual-light decision fusion, and a medium. The method comprises the following steps: collecting visible light and thermal infrared imaging data; preprocessing the data to obtain visible light and thermal infrared images of corresponding target region time-space registration; projecting a ground target area on the obtained image after space-time registration to a corresponding reference projection target surface; respectively inputting the registered images into a typical target detection model for target detection, judging whether an explosion phenomenon is detected in the images frame by frame, obtaining positioning information and category information in respective modes, dividing detection results into two categories of matched targets and unmatched targets, and outputting an explosion bounding box after secondary decision making; calculating and correcting the position of the drop point according to the explosion bounding box, and determining the image coordinate of the drop point; and mapping the coordinate of the drop point image to the reference projection target surface to obtain the position coordinate information of the drop point in the reference projection target surface. The method improves the detection precision, and better completes the target scoring task.

The invention discloses an unmanned aerial vehicle non-cooperative environment autonomous landing method and system based on three-dimensional visual semantic information, and relates to the technical field of unmanned aerial vehicle landing recognized.The method comprises the steps that during emergency landing, a semantic segmentation model is used for generating a two-dimensional semantic segmentation map and obtaining semantic tags, and a landing area is automatically screened and tracked; fusing vision and inertia information through an airborne binocular camera and an IMU (Inertial Measurement Unit), outputting an accurate pose and depth map, and inputting a map construction algorithm to reconstruct a landform map of a landing area; projecting the semantic tag to a three-dimensional space and fusing the semantic tag with a terrain map to generate an evaluation map; and finally, an optimal landing point is determined by a landing point selection algorithm, and autonomous landing is completed through a flight control system. The method has the characteristics of high precision and fast reasoning, gets rid of dependence on external signals, significantly improves the landing capability under complex terrains, and guarantees the safety and reliability of autonomous landing.

The invention discloses a logistics unmanned aerial vehicle take-off and landing point selection method, device and equipment, a medium and a product, and relates to the technical field of unmanned aerial vehicle take-off and landing point planning. According to the method, after a solution of a logistics unmanned aerial vehicle take-off and landing point selection problem under the condition of a given instance is obtained, the given instance serves as a model input item, the solution serves as a model output item, a model adopting a deep reinforcement learning method is imported for model training, and an unmanned aerial vehicle take-off and landing point selection model is obtained; and then, the coordinates of all logistics demand points of the target area and the logistics demand quantity are imported into an unmanned aerial vehicle take-off and landing point selection model, and the coordinates of the selected unmanned aerial vehicle take-off and landing points are output to serve as a logistics unmanned aerial vehicle take-off and landing point selection result of the target area, so that the problem of complex logistics unmanned aerial vehicle take-off and landing point site selection decision can be solved. Therefore, distribution with logistics requirements can be realized with low cost, and practical application and popularization are facilitated.

The invention provides a four-foot single-arm robot cooperative motion control method and system, and relates to the field of four-foot single-arm robot planning and control, and the method comprises the steps: building a multi-rigid-body dynamic model and a single-rigid-body reduced-order model as model constraints; screening out a feasible landing area; a safe landing area is generated; formulating a landing point cost function, and determining an optimal landing point; discretizing a state transition equation of the quadruped single-arm robot; taking steps capable of spanning as inequality constraints, taking the optimal landing point as elevation map equality constraints, and introducing the inequality constraints and the optimal landing point into a model prediction controller; based on a multi-rigid-body dynamic model, a multi-task planning method is optimized, control strategies are reasonably distributed, conflict tasks of four-foot movement and mechanical arm operation are dynamically coordinated, and cooperative control is conducted on multiple tasks. And fusing target data of a depth camera at the tail end of the mechanical arm, and autonomously planning a posture adjustment path of the robot body. The cooperative grabbing stability and accuracy of the robot are remarkably improved.

The invention discloses a quadruped robot landing planning method based on scene decoupling and risk avoidance. The quadruped robot landing planning method aims at solving the problems that in the prior art, perception is not precise in a complex environment, and the obstacle avoidance capacity is insufficient. The method comprises the following steps: acquiring and fusing multi-source sensor data, and segmenting an original point cloud; generating a scene decoupling elevation map of a multi-layer structure by using the segmentation point cloud; constructing a multi-objective optimization problem taking risk avoidance as a core based on the elevation map, wherein the multi-objective optimization problem comprises a comprehensive cost function and a strict obstacle avoidance constraint; utilizing a reaction formula adjusting module of a capturable region theory to cope with a dynamic instability risk; and solving the multi-target and multi-constraint optimization problem in real time by adopting a hierarchical solving strategy, and finally generating an optimal foot end drop point considering safety and stability. According to the method, the terrain adaptability, the motion stability and the decision intelligence of the quadruped robot in an unstructured environment are remarkably improved through fine decoupling of a scene and quantitative avoidance of multi-source risks.

The invention discloses an AI vision-based unmanned aerial vehicle landing control method, and relates to the technical field of computer vision, and the method comprises the steps: collecting ground comprehensive data and current attitude data of an unmanned aerial vehicle; inputting the collected ground comprehensive data into a deep learning model for ground feature analysis, and generating an optimal landing point path planning result; predicting the current position and the current attitude of the unmanned aerial vehicle based on the optimal landing point path planning result and the ground comprehensive data; calculating position information error and attitude error information according to the predicted current position and current attitude of the unmanned aerial vehicle; adjusting the attitude and descent speed of the unmanned aerial vehicle based on the position information error and attitude error information, and generating optimized attitude information and descent trajectory; and adjusting motor thrust distribution according to the optimized attitude information and the descending trajectory in combination with the optimal landing point. According to the invention, by combining the optimized attitude information with the descending trajectory, the overall landing process is ensured to be more stable and accurate, and the safe landing capability is improved.

A take-off and landing site monitoring device is configured to include: an image data acquiring unit that acquires, from an imaging device that images a take-off and landing site, image data indicating a captured image of the take-off and landing site; and an obstruction detecting unit that determines the type of obstruction that hinders take-off and landing of a vertical take-off and landing aircraft using the take-off and landing site on the basis of the image data acquired by the image data acquiring unit.

The invention provides an unmanned aerial vehicle route control method and related equipment. A standby landing point in an inspection route of a target unmanned aerial vehicle can be deployed according to a preset inspection route of the target unmanned aerial vehicle; when the electric quantity of the target unmanned aerial vehicle is not enough to complete all the inspection tasks in the inspection task execution process, safe standby drop is carried out at any time, and the battery remaining electric quantity of the target unmanned aerial vehicle is determined and recorded in real time according to the voltage of the battery of the target unmanned aerial vehicle; analyzing the total quantity of batteries required by the target unmanned aerial vehicle to complete the inspection route to be executed and the flight action; whether the current target unmanned aerial vehicle needs to be subjected to standby landing or not and whether standby landing conditions exist or not can be judged in real time according to the electric quantity consumption model and the remaining electric quantity of the unmanned aerial vehicle patrol inspection action; wherein the model can be dynamically adjusted according to external conditions, and if the model is dynamically adjusted according to external conditions, related alarm parameters of the target unmanned aerial vehicle are reported, so that a standby landing strategy of the target unmanned aerial vehicle can be determined based on the alarm parameters, and safe standby landing of the target unmanned aerial vehicle is realized.

The invention discloses a landscape object identification and explanation method and system, a medium and a product, and relates to the technical field of augmented reality. The method comprises the following steps: when the head motion state of a user is stable, triggering a camera to collect and recognize a single-frame image, matching a recognition result with a regional knowledge base, and generating a candidate object list and coarse-grained poses which are sorted according to spatial probability and historical popularity; performing feature point matching on a current frame and an ideal frame in the video stream, and calculating a fine-grained pose of a target landscape in the candidate object list relative to a camera coordinate system according to a matched target feature point; according to the fine-grained pose and the real-time eye movement data, determining a drop point part of the sight line of the user on the target landscape, forming a multi-dimensional query vector according to the drop point part, the intention of the user and the environment context parameters, and generating multimedia explanation content; and carrying out fusion rendering on the multimedia explanation content and the real-time video stream, and outputting and displaying. By implementing the technical scheme, the personalized multimedia explanation content can be generated.

The invention relates to a robot dog dynamic balance and fall self-recovery method and device for a complex terrain, and the method comprises the steps: building a robust local elevation map through fusing multi-sensor data and quantifying the motion uncertainty of a robot; and a safe foot region set defined by the convex polygon is extracted through geometric feature analysis and plane segmentation. Then, collaborative planning of the trunk and the landing point is carried out in combination with a user instruction and the region set. In a control layer, a nonlinear model predictive control algorithm is adopted, a safety area is used as a hard constraint, and incomplete speed constraint is applied to a wheel type foot end, so that an optimized trunk track and a foot end force reference are output. The whole-body controller converts an upper-layer instruction into an accurate joint torque through a multi-task optimization framework with a weight. When instability is detected, the system can autonomously plan and execute a recovery action sequence including curling, controllable rolling and cooperative supporting.

The invention relates to the technical field of artificial intelligence, in particular to a multi-dimensional tennis action analysis system, which comprises a data acquisition module, a data preprocessing module, an evaluation analysis module and a feedback interaction module, and is characterized in that the data acquisition module comprises a posture data acquisition unit, a ball path and walking tracking unit and a motion parameter acquisition unit; the data preprocessing module carries out space-time calibration on posture, track and motion parameters based on a timestamp synchronization mechanism, a fusion data set is formed through data cleaning and standardization processing, and the evaluation analysis module is used for distinguishing action types, integrating scores of posture dimensions, power generation dimensions and drop point dimensions and generating a comprehensive evaluation report; and the feedback interaction module displays an evaluation result in real time on an interface based on characters and visual icons and outputs historical analysis. According to the invention, the data validity is guaranteed, the error interference is eliminated, the analysis efficiency and the professionality of the evaluation result are improved, the use threshold is reduced, and the universality and practicability of the system are improved.

The invention relates to an aircraft air-dropped material recycling method and device and computer equipment. The method comprises the following steps: constructing a design variable of an optimal release point of the materials released by the aircraft; the design variables comprise release point coordinates and course angles; according to a motion equation of a material landing process and the design variable, establishing a relationship between the design variable and a landing point position vector; determining a drop point evaluation function according to a pre-acquired launching mode, simulating and calculating a drop point position vector corresponding to each course angle by adopting a course angle traversing mode, and selecting a corresponding course angle and a corresponding drop point position vector according to a drop point evaluation function optimization principle; and solving a traveling salesman problem by adopting a greedy algorithm, and traversing landing points of all the landing point position vectors to obtain an optimal path plan of material recovery. By adopting the method, the course angle can be dynamically adjusted according to the real-time environment data, and the material delivery requirement is met.

The invention discloses a landing method, system and equipment of an unmanned aerial vehicle and a medium, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: obtaining a video image and flight information of the unmanned aerial vehicle in real time, carrying out the landing point recognition of the video image based on a preset landing point template image, obtaining a landing point position, and carrying out the safety evaluation of the flight information; and determining safety evaluation data corresponding to the unmanned aerial vehicle, and controlling the unmanned aerial vehicle to land to the landing point position according to the safety evaluation data and the flight information. The technical problems that in the prior art, landing control is mainly performed on the unmanned aerial vehicle based on a landing method of reinforcement learning, but in actual flight, the unmanned aerial vehicle faces external interference of different working conditions, so that the unmanned aerial vehicle cannot land according to a preset track, and the operation safety of the unmanned aerial vehicle is reduced are solved.

The invention discloses a shipborne fixed-wing aircraft landing guidance law design method and system, and belongs to the field of aircraft guidance law design. The problems that the multi-coordinate system coupling effect of ship motion and aircraft dynamics is not fully decoupled and an existing method is weak in adaptability to non-stable sea conditions are solved. The method comprises the following steps: defining related coordinate systems including a world coordinate system, a landing coordinate system and a ship body coordinate system; calculating an ideal landing point height change value caused by ship deck movement in real time according to the position of the ideal position in the ship body coordinate system; utilizing a KOA-LSTM hybrid forecasting model to predict a motion heave value of a ship deck at a future critical moment; designing a compensation value for the longitudinal position deviation based on the predicted motion heave value, and carrying out dynamic compensation correction on the longitudinal guide instruction; and according to the compensated guide instruction and the real-time position of the aircraft, calculating the transverse and longitudinal deviation of the aircraft relative to the expected landing trajectory to form closed-loop control. The device is mainly used for offshore operation.

The invention provides a biped robot gait planning method and device for a step terrain, and belongs to the technical field of robot gait planning, the method comprises the following steps: based on a linear inverted pendulum model, respectively establishing walking modes of an upper step and a lower step of a biped robot; based on a walking mode, mapping the linear inverted pendulum model under the step terrain into a segmented virtual height linear inverted pendulum model under the plane terrain; based on a segmented virtual height linear inverted pendulum model, gait planning of the biped robot under the stepped terrain is achieved through model prediction control. According to the biped robot gait planning method and device for the step terrain, the linear inverted pendulum model with the virtual centroid height is used, the gait mode is established according to the terrain elevation information and the landing point information of the step environment, and the method and device can adapt to the irregular step terrain with the variable height and the variable length; and the gait has good terrain adaptability.

The invention discloses an emergency homeward voyage control method for an unmanned aerial vehicle under a power failure condition and a medium. The method comprises the following steps: constructing a cascade PID path tracking controller; constructing a cascade model prediction path tracking controller; constructing a model prediction path tracking controller based on the extended state observer; a controller is determined according to the unmanned aerial vehicle power fault condition of emergency return, the unmanned aerial vehicle flight state, forced landing point information and external environment factors, and emergency return control is achieved. The emergency return path tracking controller is determined according to the return route provided by the current flight state, and the return route is tracked.