Terrain sensing methods, devices, equipment, media and program products

Abstract

This application relates to the field of deep space exploration and legged robot control technology, and particularly to a terrain perception method, device, equipment, medium, and program product. The method includes: acquiring lunar surface terrain information and multimodal sensing data of the lunar surface terrain; generating fused terrain information based on the lunar surface terrain information and multimodal sensing data, and determining the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints; during the legged robot's walking based on the planned trajectory, collecting the actual contact state of the legged robot through foot sensors, determining a consistency risk value based on the actual contact state and the predicted contact state, and adjusting the current walking trajectory and / or replanning the current walking trajectory based on the fused terrain information when the consistency risk value reaches a preset risk threshold. This solves the problem of walking instability caused by the uncertainty of the terrain's mechanical properties in lunar legged robots.

Description

Technical Field

[0001] This application relates to the fields of deep space exploration and legged robot control technology, and in particular to a terrain perception method, device, equipment, medium and program product. Background Technology

[0002] With the development of legged robot technology, legged robots are increasingly being applied to lunar surface walking research. In Earth's environment, existing legged robot planning and control methods typically rely on geometric maps constructed using vision or laser sensors for decision-making, assuming the ground has relatively stable and predictable mechanical properties. Under these assumptions, walking planning methods based on geometric reachability and obstacle avoidance can meet most application requirements. However, in the lunar environment, due to the generally loose nature of lunar regolith, its presence of debris, and highly uneven mechanical properties, the surface bearing capacity and stability exhibit significant uncertainties. Simply relying on geometric information for decision-making cannot accurately reflect the true bearing capacity of the lunar surface, easily leading to safety problems such as slipping, sinking, or even overall instability during walking.

[0003] In related technologies, to compensate for the shortcomings of relying solely on geometric information, foot sensors are introduced to sense the contact state between the foot and the ground. These foot sensors are primarily used to determine the moment of contact, identify early or delayed contact, or serve as a control compensation method during the movement execution phase. Their sensing results mainly serve to locally correct the trajectory of a single leg movement.

[0004] However, while the relevant technologies have improved the stability of motion execution to some extent, they remain at the control level and have failed to elevate the physical information reflected by the direct mechanical interaction between the foot and the ground to the decision-making basis of the planning level, which urgently needs to be addressed. Summary of the Invention

[0005] This application provides a terrain perception method, device, equipment, medium, and program product to solve problems such as walking instability caused by uncertain terrain mechanics characteristics in lunar legged robots.

[0006] The first aspect of this application provides a terrain sensing method, including the following steps: The lunar surface topography information and multimodal sensing data of the lunar surface topography are acquired, wherein the multimodal sensing data is collected by foot sensors of a legged robot. Based on the lunar surface topography information and the multimodal sensing data, fused terrain information is generated, and based on the fused terrain information and preset robot dynamics constraints, the current walking trajectory of the legged robot is determined. During the walking process of the legged robot based on the walking plan trajectory, the actual contact state of the legged robot is collected by the foot end sensor, and a consistency risk value is determined based on the actual contact state and the predicted contact state. When the consistency risk value reaches a preset risk threshold, the current walking plan trajectory is adjusted and / or the current walking plan trajectory is replanned based on the fused terrain information.

[0007] Optionally, the fused terrain information includes terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

[0008] Optionally, the preset robot dynamics constraints are: ; in, For the first Normal bearing capacity at each foot end To optimize variables, For the first The maximum normal bearing capacity of each foot end For the first The equivalent indentation depth corresponding to each foot tip These are the terrain physical attribute parameters.

[0009] Optionally, before determining the consistency risk value based on the actual contact state and the predicted contact state, the method further includes: The predicted contact state is obtained by calculating based on the fused terrain information, the preset optimization objective function, and the preset robot dynamics constraints, wherein the preset optimization objective function is: ; in, To minimize the total cost, To optimize variables, For geometric reachability cost, The weighting coefficients for the geometric reachability cost term. As a cost term for overall stability, The weighting coefficients for the overall stability cost term. For terrain risk cost item, This refers to the weighting coefficient of the terrain risk cost term. For walking efficiency cost, This represents the weighting coefficient for the walking efficiency cost term.

[0010] Optionally, the formula for calculating the consistency risk value based on the actual contact state and the predicted contact state is as follows: ; in, For risk assessment function, For the first The measured normal load at each foot end For the first The planning and prediction of the normal load at each foot end, To determine the permissible equivalent subsidence depth, To determine the equivalent subsidence depth allowed by the plan, To reflect the characteristic function of microslip risk, For the first The amount of slippage at the foot end, These are the weighting coefficients.

[0011] A second aspect of this application provides a terrain sensing device, comprising: The acquisition module is used to acquire lunar surface topography information and multimodal sensing data of lunar surface topography, wherein the multimodal sensing data is acquired by foot sensors of the legged robot. The determination module is used to generate fused terrain information based on the lunar surface terrain information and the multimodal sensing data, and to determine the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. The adjustment module is used to collect the actual contact state of the legged robot through the foot end sensor during the walking process based on the walking planning trajectory, determine the consistency risk value according to the actual contact state and the predicted contact state, and adjust the current walking planning trajectory and / or replan the current walking planning trajectory based on the fused terrain information when the consistency risk value reaches a preset risk threshold.

[0012] Optionally, the fused terrain information includes terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

[0013] Optionally, the preset robot dynamics constraints are: ; in, For the first Normal bearing capacity at each foot end To optimize variables, For the first The maximum normal bearing capacity of each foot end For the first The equivalent indentation depth corresponding to each foot tip These are the terrain physical attribute parameters.

[0014] Optionally, before determining the consistency risk value based on the actual contact state and the predicted contact state, the adjustment module is further configured to: The predicted contact state is obtained by calculating based on the fused terrain information, the preset optimization objective function, and the preset robot dynamics constraints, wherein the preset optimization objective function is: ; in, To minimize the total cost, To optimize variables, For geometric reachability cost, The weighting coefficients for the geometric reachability cost term. As a cost term for overall stability, The weighting coefficients for the overall stability cost term. For terrain risk cost item, This refers to the weighting coefficient of the terrain risk cost term. For walking efficiency cost, This represents the weighting coefficient for the walking efficiency cost term.

[0015] Optionally, the formula for calculating the consistency risk value based on the actual contact state and the predicted contact state is as follows: ; in, For risk assessment function, For the first The measured normal load at each foot end For the first The planning and prediction of the normal load at each foot end, To determine the permissible equivalent subsidence depth, To determine the equivalent subsidence depth allowed by the plan, To reflect the characteristic function of microslip risk, For the first The amount of slippage at the foot end, These are the weighting coefficients.

[0016] A third aspect of this application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the terrain sensing method as described in the above embodiments.

[0017] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the terrain sensing method as described in the above embodiments.

[0018] A fifth aspect of this application provides a computer program product storing a computer program that, when executed by a processor, implements the terrain perception method as described in the above embodiments.

[0019] Therefore, this application embodiment acquires lunar surface terrain information and multimodal sensing data of the lunar surface terrain; generates fused terrain information based on the lunar surface terrain information and multimodal sensing data; and determines the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. During the walking process of the legged robot based on the walking trajectory, the actual contact state of the legged robot is collected through foot sensors, and a consistency risk value is determined based on the actual contact state and the predicted contact state. When the consistency risk value reaches a preset risk threshold, the current walking trajectory is adjusted and / or the current walking trajectory is re-planned based on the fused terrain information. This solves the problem of walking instability caused by the uncertainty of the terrain mechanics characteristics of lunar legged robots.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a terrain sensing method provided according to an embodiment of this application; Figure 2 This is a schematic diagram of the framework of a terrain sensing method according to an embodiment of this application; Figure 3 This is a schematic diagram of a terrain sensing device provided according to an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Detailed Implementation

[0022] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0023] The terrain perception method, apparatus, device, medium, and program product of this application are described below with reference to the accompanying drawings. Addressing the problem of walking instability in lunar legged robots due to uncertainties in the terrain's mechanical properties, as mentioned in the background art, this application provides a terrain perception method. In this method, embodiments of this application acquire lunar terrain information and multimodal sensing data of the lunar terrain; generate fused terrain information based on the lunar terrain information and multimodal sensing data; and determine the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. During the walking process of the legged robot based on the walking trajectory, the actual contact state of the legged robot is collected through foot sensors, and a consistency risk value is determined based on the actual contact state and the predicted contact state. When the consistency risk value reaches a preset risk threshold, the current walking trajectory is adjusted and / or the current walking trajectory is re-planned based on the fused terrain information. This solves the problem of walking instability in lunar legged robots caused by uncertainties in the terrain's mechanical properties.

[0024] Specifically, Figure 1 This is a schematic flowchart of a terrain sensing method provided in an embodiment of this application.

[0025] like Figure 1 As shown, the terrain perception method includes the following steps: In step S101, lunar surface topography information and multimodal sensing data of lunar surface topography are acquired, wherein the multimodal sensing data is collected by foot sensors of the legged robot.

[0026] Specifically, during the robot's walking process, this embodiment acquires the geometric structure and surface distribution information of the lunar terrain based on visual or lidar sensors, including three-dimensional point cloud data of the terrain, surface height distribution, slope and curvature characteristics, surface roughness, etc., and constructs a local terrain grid model and height map model on this basis to form an initial understanding of the spatial morphology of the terrain ahead and to make a preliminary judgment on walkable areas and candidate footing areas. On this basis, each foot continuously collects multimodal sensing data reflecting the physical characteristics of the ground at different stages of contact between the foot and the lunar terrain through integrated force, torque and displacement sensors. The multimodal sensing data includes changes in the normal and tangential forces of the foot, triaxial torque information, displacement or equivalent sinking depth evolution characteristics inferred from the relative pose and contact state of the foot, and micro-slip characteristic signals used to characterize the relative motion state between the foot and the ground.

[0027] In step S102, fused terrain information is generated based on lunar surface terrain information and multimodal sensing data, and the current walking trajectory of the legged robot is determined based on the fused terrain information and preset robot dynamics constraints.

[0028] Specifically, a time-series analysis is performed on the force changes, displacement evolution, sinking trend, and micro-slip characteristics (multimodal sensor data) during foot contact. Combined with the mechanical model under low lunar gravity conditions, the judgment results of the terrain geometry (lunar terrain information) obtained by radar perception are physically corrected and supplemented. This allows for a comprehensive judgment of the equivalent bearing capacity and risk level of the foot contact with the ground, generating fused terrain information that reflects the physical properties of the lunar terrain. After obtaining the terrain physical attribute information (fused terrain information), the walking planning module introduces the fused terrain information into the planning layer. Based on the fused terrain information and preset robot dynamics constraints, the current walking trajectory of the legged robot is determined.

[0029] Optionally, in some embodiments, the fused terrain information includes terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

[0030] Understandably, integrating terrain information expands terrain perception from a single geometric dimension to multiple physical and mechanical dimensions. On the one hand, it enables robots to predict the bearing capacity and instability risk of lunar soil during the planning stage, avoiding soft and slippery areas from the outset. On the other hand, it provides multi-dimensional predictive benchmarks for risk monitoring during the walking process, significantly improving the safety, stability, and autonomous adaptability of legged robots walking under complex and uncertain lunar terrain conditions, and providing a basis for the robot's subsequent motion planning.

[0031] Optionally, in some embodiments, the preset robot dynamics constraints are: ; in, For the first Normal bearing capacity at each foot end To optimize variables, For the first The maximum normal bearing capacity of each foot end For the first The equivalent indentation depth corresponding to each foot tip These are the terrain physical attribute parameters.

[0032] Understandably, the equivalent bearing capacity index from the fused terrain information is mapped to planning constraints (preset robot dynamics constraints) to limit the maximum bearing capacity of a single leg, control the allowable sinking depth, and adjust the duration of the support phase; among these, It can be represented as , The landing position of each foot. To correspond to the duration of the support phase, These are gait parameters.

[0033] In step S103, during the walking process of the legged robot based on the walking planning trajectory, the actual contact state of the legged robot is collected by the foot end sensor, and the consistency risk value is determined according to the actual contact state and the predicted contact state. When the consistency risk value reaches the preset risk threshold, the current walking planning trajectory is adjusted and / or the current walking planning trajectory is replanned based on the fused terrain information.

[0034] The preset risk threshold can be a threshold set by the user, a threshold obtained through a limited number of experiments, or a threshold obtained through a limited number of computer simulations; no specific limitation is made here.

[0035] Specifically, during the walking process, this embodiment continuously monitors the actual contact state fed back by the foot sensors and performs consistency judgment between it and the contact state predicted in the walking planning stage. The consistency judgment includes at least the judgment of the deviation between the planned predicted foot contact state and the actual contact state, the planned single-foot bearing capacity and the measured force distribution, and the planned allowable sinking depth and the actual equivalent sinking depth. When a significant deviation is detected between the foot force distribution, sinking degree, or slippage trend and the planning expectation, the system does not immediately determine the planning failure based on a single indicator, but calculates a consistency risk value by comprehensively considering various deviation indicators. When the risk value exceeds a preset risk threshold, it is determined that the current walking plan has a risk of failure. When the risk judgment reaches a preset trigger condition, a safety planning trigger mechanism is activated to adjust the current walking strategy (previous walking planning trajectory) or trigger a replanning process. Among them, the planning parameter adjustment includes increasing the stability-related cost weight, reducing the single-foot bearing capacity upper limit, extending the support phase duration, or reducing the stride range; when the replanning process is triggered, the current walking planning trajectory is regenerated based on the current fused terrain information.

[0036] It should be noted that the safety planning triggering mechanism does not involve the implementation details of the specific walking planning algorithm. Instead, it continuously verifies the validity of the planning assumptions through clear judgment conditions and triggering logic, ensuring that the system can promptly enter the safety processing flow when the planning assumptions are violated.

[0037] Optionally, in some embodiments, the formula for calculating the consistency risk value based on the actual contact state and the predicted contact state is as follows: ; in, For risk assessment function, For the first The measured normal load at each foot end For the first The planning and prediction of the normal load at each foot end, To determine the allowable equivalent subsidence depth, To determine the equivalent subsidence depth allowed by the plan, To reflect the characteristic function of microslip risk, For the first The amount of slippage at the foot end, These are the weighting coefficients.

[0038] Understandably, a risk assessment function for walking plan consistency is constructed based on multiple deviations to measure the risk level of the planning assumptions being violated under the current execution state.

[0039] Therefore, to address the shortcomings of relying solely on visual or geometric information in accurately reflecting the lunar regolith's bearing capacity, looseness, and contact stability, this invention acquires geometric structure and surface distribution information of the lunar surface terrain using visual or laser sensors, forming an initial terrain perception for walking planning. Based on this, multimodal sensor data such as force, torque, and displacement are collected from the foot of a legged robot. Temporal analysis is performed on the force changes, sinking trends, and micro-slip characteristics during the foot's contact with the lunar surface. Combined with a mechanical model under low lunar gravity conditions, the visual perception results are physically corrected and supplemented, thereby determining the equivalent bearing capacity and risk level of the current contact surface and generating fused terrain information reflecting the physical properties of the lunar terrain. To address the shortcomings of existing legged robot walking plans that are disconnected from actual contact states and unable to respond promptly to changes in terrain physical characteristics, this invention constructs a walking planning method based on foot-perception feedback. The walking planning layer no longer uses geometric reachability as the optimization objective but comprehensively considers terrain bearing capacity, sinking risk, and stability requirements, jointly planning the foot placement location, support sequence, and gait form. This invention proposes a safety planning triggering mechanism based on walking risk monitoring. By judging the consistency between the actual contact state fed back by foot sensors and the predicted contact state in the planning stage, when a significant deviation is detected in the force distribution, sinking degree, or slippage trend of the foot from the planning expectation, it is determined that the current walking plan has a risk of failure and triggers a preset adjustment or replanning process. This mechanism does not involve the specific walking planning algorithm process, but ensures that the system can promptly enter the safety processing process when the planning assumptions are violated through clear triggering conditions.

[0040] Optionally, in some embodiments, before determining the consistency risk value based on the actual contact state and the predicted contact state, the method further includes: calculating the predicted contact state based on fused terrain information, a preset optimization objective function, and preset robot dynamics constraints, wherein the preset optimization objective function is: ; in, To minimize the total cost, To optimize variables, For geometric reachability cost, The weighting coefficients for the geometric reachability cost term. As a cost term for overall stability, The weighting coefficients for the overall stability cost term. For terrain risk cost item, This refers to the weighting coefficient of the terrain risk cost term. For walking efficiency cost, This represents the weighting coefficient for the walking efficiency cost term.

[0041] Understandably, by using fused terrain information as input, guided by a pre-defined optimization objective function (comprehensively considering geometric accessibility, stability, terrain risk, and walking efficiency), and constrained by pre-defined robot dynamics constraints, the predicted contact state (i.e., the desired foot contact force, desired sinking depth, etc.) is ultimately obtained through optimization. In other words, an optimization-based walking planning method, under the premise of satisfying robot dynamics constraints (pre-defined robot dynamics constraints), formalizes the walking planning process into an optimization problem with one set of constraints (pre-defined robot dynamics constraints), jointly optimizing the foot placement, support timing, and gait form. The optimization variables can be expressed as follows: ,in The landing position of each foot. To correspond to the duration of the support phase, These are the gait parameters. The objective function of the optimization problem (the preset objective function) comprehensively considers geometric reachability, overall stability, terrain risk, and walking efficiency.

[0042] Therefore, this embodiment of the application, through the coordinated operation of foot-based multimodal perception, terrain physical attribute discrimination, walking planning, and walking risk monitoring, enables the direct mechanical interaction information between the foot and the lunar surface terrain to continuously influence the walking planning and execution process. During walking, the terrain perception results are continuously updated, and the planning strategy is dynamically adjusted based on risk monitoring, thereby achieving safe and autonomous walking under complex lunar terrain conditions.

[0043] To facilitate a better understanding of the terrain sensing method of the embodiments of this application by those skilled in the art, the following is combined with... Figure 2 The embodiments shown will be described in detail.

[0044] Specifically, such as Figure 2 As shown, Figure 2This is a schematic diagram of the framework of a terrain perception method according to an embodiment of this application. In order to realize the safe and autonomous walking of legged robots under complex and uncertain terrain conditions on the lunar surface, this invention proposes a terrain perception and safety planning method for legged robots on the lunar surface based on foot sensors. The system is deployed on the legged robot body and mainly includes a foot perception module, a terrain perception and discrimination module, a walking planning module, a walking risk monitoring module, and a motion execution module. Each module works together during the robot's walking process to form a closed-loop operation mechanism.

[0045] Furthermore, the sensing module acquires multimodal data in real time at a high frequency of 1000 Hz. This module deeply integrates information from foot sensors and visual sensors (LiDAR / visual cameras). The visual sensors are responsible for acquiring the macroscopic geometry of the lunar surface topography, while the foot sensors capture the mechanical response characteristics during the microscopic process of foot-to-ground contact. The multimodal terrain sensing data generated by the sensing module is transmitted to the terrain physical property discrimination module at a mid-frequency of 100 Hz. The core function of this module is to extract and fuse features from the raw sensing data, and combine it with a mechanical model under the low gravity environment of the lunar surface to comprehensively determine the equivalent bearing capacity of the terrain, the foot sinking trend, and the slip risk.

[0046] Furthermore, the terrain physical attribute information is then fed into the walking decision and terrain safety planning module. This module operates at a low frequency of 10 Hz and is responsible for generating the globally optimal walking strategy, specifically including foothold selection, gait switching, and fuselage attitude planning. The terrain physical attribute information obtained from the front end is directly incorporated into the optimization objective function and constraints, so that walking planning is no longer based solely on geometric reachability, but on the actual mechanical bearing characteristics of the terrain. This constructs a "terrain safety sandbox," meaning that any walking plan must first pass the safety verification of the terrain physical attributes to ensure that the planned foothold has sufficient bearing capacity and acceptable risks of subsidence and slippage before it can be allowed to be executed.

[0047] Furthermore, the planning results are sent to the motion control and execution module, which drives the robot's body movement at a high frequency of 1000 Hz to achieve high-frequency real-time control. During this process, the consistency judgment and risk monitoring module operates in parallel at a medium frequency of 100 Hz, continuously monitoring the real-time feedback from the foot sensors and comparing it with the predicted contact state (expected load-bearing capacity, expected sinking depth) given by the walking planning module to calculate the consistency risk value.

[0048] also, Figure 2The diagram clearly illustrates three data flow types. The blue solid line (forward data flow) forms the main link of "perception-discrimination-planning-execution," ensuring the forward transmission of terrain information and planning instructions. The white solid line (monitoring feedback flow) flows from the consistency discrimination module to the walking decision module, used for online parameter fine-tuning within a controllable risk range. The red dashed line (replanning trigger flow) is triggered directly by the monitoring module to the walking decision module for replanning when the consistency risk value exceeds a preset risk threshold, skipping the regular control and adjustment process to address sudden and significant planning assumption failures.

[0049] Therefore, this application embodiment extracts terrain semantic information reflecting the lunar surface terrain bearing capacity and stability by analyzing and physically modeling multimodal perception information of the feet, and introduces it into the planning layer. At the same time, combined with the execution consistency judgment mechanism, the effectiveness of the planning assumptions is continuously monitored, thereby achieving safe walking under complex lunar terrain conditions.

[0050] According to the terrain perception method proposed in this application, this application acquires lunar surface terrain information and multimodal sensing data of the lunar surface terrain; generates fused terrain information based on the lunar surface terrain information and multimodal sensing data, and determines the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints; during the walking process of the legged robot based on the walking trajectory, the actual contact state of the legged robot is collected through foot sensors, and a consistency risk value is determined based on the actual contact state and the predicted contact state; when the consistency risk value reaches a preset risk threshold, the current walking trajectory is adjusted and / or the current walking trajectory is replanned based on the fused terrain information. This solves the problem of walking instability caused by the uncertainty of the terrain mechanics characteristics of lunar legged robots.

[0051] Next, the terrain sensing device according to an embodiment of this application is described with reference to the accompanying drawings.

[0052] Figure 3 This is a block diagram of a terrain sensing device according to an embodiment of this application.

[0053] like Figure 3 As shown, the terrain sensing device 10 includes: an acquisition module 100, a determination module 200, and an adjustment module 300.

[0054] The acquisition module 100 is used to acquire lunar surface topography information and multimodal sensing data of lunar surface topography. The multimodal sensing data is collected by the foot sensors of the legged robot. The determination module 200 is used to generate fused terrain information based on lunar surface terrain information and multimodal sensing data, and to determine the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. The adjustment module 300 is used to collect the actual contact state of the legged robot through foot sensors during the walking process based on the walking planning trajectory, determine the consistency risk value based on the actual contact state and the predicted contact state, and adjust the current walking planning trajectory and / or replan the current walking planning trajectory based on the fused terrain information when the consistency risk value reaches the preset risk threshold.

[0055] Optionally, terrain information can be integrated, including terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

[0056] Optionally, the preset robot dynamics constraints are: ; in, For the first Normal bearing capacity at each foot end To optimize variables, For the first The maximum normal bearing capacity of each foot end For the first The equivalent indentation depth corresponding to each foot tip These are the terrain physical attribute parameters.

[0057] Optionally, before determining the consistency risk value based on the actual contact state and the predicted contact state, the adjustment module 300 is further configured to: calculate the predicted contact state based on the fused terrain information, a preset optimization objective function, and preset robot dynamics constraints, wherein the preset optimization objective function is: ; in, To minimize the total cost, To optimize variables, For geometric reachability cost, The weighting coefficients for the geometric reachability cost term. As a cost term for overall stability, The weighting coefficients for the overall stability cost term. For terrain risk cost item, This refers to the weighting coefficient of the terrain risk cost term. For walking efficiency cost, This represents the weighting coefficient for the walking efficiency cost term.

[0058] Optionally, the formula for calculating the consistency risk value based on the actual contact status and the predicted contact status is as follows: ; in, For risk assessment function, For the first The measured normal load at each foot end For the first The planning and prediction of the normal load at each foot end, To determine the allowable equivalent subsidence depth, To determine the equivalent subsidence depth allowed by the plan, To reflect the characteristic function of microslip risk, For the first The amount of slippage at the foot end, These are the weighting coefficients.

[0059] It should be noted that the foregoing explanation of the terrain sensing method embodiment also applies to the terrain sensing device of this embodiment, and will not be repeated here.

[0060] According to the terrain sensing device proposed in this application, the embodiment acquires lunar surface terrain information and multimodal sensing data of the lunar surface terrain; generates fused terrain information based on the lunar surface terrain information and multimodal sensing data; and determines the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. During the walking process of the legged robot based on the walking trajectory, the actual contact state of the legged robot is collected by foot sensors, and a consistency risk value is determined based on the actual contact state and the predicted contact state. When the consistency risk value reaches a preset risk threshold, the current walking trajectory is adjusted and / or the current walking trajectory is replanned based on the fused terrain information. This solves the problem of walking instability caused by the uncertainty of the terrain mechanics characteristics of the lunar legged robot.

[0061] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0062] When the processor 402 executes the program, it implements the terrain perception method provided in the above embodiments.

[0063] Furthermore, electronic devices also include: Communication interface 403 is used for communication between memory 401 and processor 402.

[0064] The memory 401 is used to store computer programs that can run on the processor 402.

[0065] Memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0066] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0067] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0068] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0069] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the terrain perception method described above.

[0070] This application also provides a computer program product that stores a computer program that, when executed by a processor, implements the terrain perception method described above.

[0071] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0072] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0073] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0074] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0075] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

Claims

1. A terrain sensing method, characterized in that, Includes the following steps: The lunar surface topography information and multimodal sensing data of the lunar surface topography are acquired, wherein the multimodal sensing data is collected by foot sensors of a legged robot. Based on the lunar surface topography information and the multimodal sensing data, fused terrain information is generated, and based on the fused terrain information and preset robot dynamics constraints, the current walking trajectory of the legged robot is determined. During the walking process of the legged robot based on the walking plan trajectory, the actual contact state of the legged robot is collected by the foot end sensor, and a consistency risk value is determined based on the actual contact state and the predicted contact state. When the consistency risk value reaches a preset risk threshold, the current walking plan trajectory is adjusted and / or the current walking plan trajectory is replanned based on the fused terrain information.

2. The method according to claim 1, characterized in that, The fused terrain information includes terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

3. The method according to claim 1, characterized in that, The preset robot dynamics constraints are as follows: ； in, For the first Normal bearing capacity at each foot end To optimize variables, For the first The maximum normal bearing capacity of each foot end For the first The equivalent depression depth corresponding to each foot tip These are the terrain physical attribute parameters.

4. The method according to claim 1, characterized in that, Before determining the consistency risk value based on the actual contact state and the predicted contact state, the method further includes: The predicted contact state is obtained by calculating based on the fused terrain information, the preset optimization objective function, and the preset robot dynamics constraints, wherein the preset optimization objective function is: ； in, To minimize the total cost, To optimize variables, For geometric reachability cost, The weighting coefficients for the geometric reachability cost term. As a cost term for overall stability, The weighting coefficients for the overall stability cost term. For terrain risk cost item, This refers to the weighting coefficient of the terrain risk cost term. For walking efficiency cost, This represents the weighting coefficient for the walking efficiency cost term.

5. The method according to claim 1, characterized in that, The formula for calculating the consistency risk value based on the actual contact state and the predicted contact state is as follows: ； in, For risk assessment function, For the first The measured normal load at each foot end For the first The planning and prediction of the normal load at each foot end, To determine the allowable equivalent subsidence depth, To determine the equivalent subsidence depth allowed by the plan, To reflect the characteristic function of microslip risk, For the first The amount of slippage at the foot end, These are the weighting coefficients.

6. A terrain sensing device, characterized in that, include: The acquisition module is used to acquire lunar surface topography information and multimodal sensing data of lunar surface topography, wherein the multimodal sensing data is acquired by foot sensors of the legged robot. The determination module is used to generate fused terrain information based on the lunar surface terrain information and the multimodal sensing data, and to determine the current walking trajectory of the legged robot based on the fused terrain information and preset robot dynamics constraints. The adjustment module is used to collect the actual contact state of the legged robot through the foot end sensor during the walking process based on the walking planning trajectory, determine the consistency risk value according to the actual contact state and the predicted contact state, and adjust the current walking planning trajectory and / or replan the current walking planning trajectory based on the fused terrain information when the consistency risk value reaches a preset risk threshold.

7. The apparatus according to claim 6, characterized in that, The fused terrain information includes terrain geometric feature parameters, terrain equivalent bearing capacity, lower limit risk, and slip risk.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the terrain sensing method as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the terrain sensing method as described in any one of claims 1-5.

10. A computer program product, said computer program product storing a computer program, characterized in that, When the program is executed by the processor, it implements the terrain-aware method as described in any one of claims 1-5.

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