8 results about "Environmental modeling" patented technology

The invention relates to the technical field of unmanned aerial vehicle automatic inspection, provides an unmanned aerial vehicle take-off and landing platform rapid deployment and path planning method for a building curtain wall, constructs a gradient risk field model fusing geometric structures, environmental risks, visual perception and task regulations, and realizes unified quantitative evaluation of operation environmental risks. And based on the risk field, generating a global safe energy-saving path on the curved surface of the curtain wall through mixed search and path smoothing optimization guided by a risk navigation potential function. Through real-time updating of a local risk field and model prediction control, autonomous obstacle avoidance and smooth return flight of the unmanned aerial vehicle to sudden obstacles are realized. Meanwhile, a dynamic scheduling mechanism considering multi-target cost is introduced, and collaborative optimization of multiple unmanned aerial vehicles and take-off and landing platform resources is achieved. According to the method, full-link closed loop from environment modeling, global planning, real-time control to system scheduling is realized, and the safety, continuity and overall operation efficiency of automatic routing inspection of the super high-rise building curtain wall are improved.

This invention discloses a multi-objective path planning method and system for unmanned surface vessels (USVs) in complex marine environments, belonging to the field of USV path planning technology. The method includes the following steps: environmental modeling is performed using a voxelized raster method based on a terrain grayscale map; distance transformation is used to calculate the Euclidean distance from each free-space grid to the nearest obstacle, providing a quantitative basis for path safety assessment; an improved multi-objective particle swarm optimization method is used to complete a global path search under safety constraints; a three-dimensional constraint dual-level processing mechanism is designed to process the initial path solution set, generating a set of paths to be selected; based on the designed cost function and according to the Pareto dominance principle, the generated set of paths to be selected is filtered to obtain the Pareto front. This invention considers both path length and path safety, and provides a wider range of random paths for multi-objective path planning, offering more and more reasonable path selections.

This invention belongs to the technical field of agricultural environmental control and UAV applications, and relates to a UAV-based microclimate precision control system for forest understory cultivation areas. The system includes: an environmental modeling and initialization module, a prediction and decision-making module, a command execution and observation module, a data verification and extraction module, an error calculation and correction source term generation module, a correction source term propagation and field update module, and a closed-loop iterative scheduling module. By constructing a three-dimensional voxel grid and generating an initial microclimate prediction field, identifying target voxels based on prediction trends and generating predictive control frames, the UAV executes intervention actions and collects observation data. After verification and error calculation, correction source terms are generated. The microclimate prediction field is updated based on predicted airflow propagation, achieving closed-loop iterative control. This invention solves the problems of lagging control and insufficient intervention targeting caused by the lack of dynamic prediction of three-dimensional microclimate fields and digital twin linkage capabilities in existing fixed sensor networks and traditional UAV operation methods.

This invention discloses an adaptive compliant force control method for robotic arms based on reinforcement learning, belonging to the fields of robotics and automation. This method is based on an integrated framework of "reinforcement learning-adaptive compliant force control" for a robotic arm-dexterous hand-six-dimensional force / torque sensor system. It aims to completely eliminate existing problems such as the need for manual parameter tuning during model changes, difficulties in contact dynamics modeling, model parameter estimation, and the frequent need to prove the stability of adaptive laws through intelligent control strategies. It achieves self-learning and self-adaptation of upper-level task planning and lower-level compliant force / position control. After deployment, no repeated manual parameter tuning is required for different working conditions. The same control strategy maintains a high assembly success rate and low peak contact force for workpieces with small gaps, easy deformation, and multiple materials, eliminating bottlenecks in manual calibration, environmental modeling, and online parameter estimation, and enabling rapid "zero-downtime" switching in flexible production lines.

This invention relates to the field of robotics technology and discloses a large-model-driven method and system for navigation and autonomous path planning of a composite robot. The method includes: collecting environmental data through multimodal sensors; inputting the data into a visual-language large model (VLM) to construct a holistic environmental model containing geometric, semantic, and dynamic object information; parsing high-level natural language navigation instructions using the VLM and generating navigation target points based on the holistic environmental model; and finally, coordinating the robot's body movement trajectory and end effector action sequence based on the model and target points, and driving their execution. This invention, by introducing a large model for holistic environmental modeling and task parsing, solves the problems of weak environmental understanding and unnatural human-computer interaction in traditional robot navigation technologies. It achieves deep perception of complex dynamic environments and autonomous planning of high-level instructions, significantly improving the intelligence level and operational efficiency of composite robots in real-world scenarios.

This invention discloses a robot movement path planning method based on ant colony optimization algorithm. It includes the following steps: environmental modeling of the robot's movement space using a grid method to obtain a grid map, with grid coordinates representing the robot's starting and ending positions; generating an initial path on the grid map using a jump-point search algorithm, and calculating the non-uniform initial pheromone concentration distribution along the initial path; searching for the optimal path on the grid map using the ant colony optimization algorithm; eliminating redundant nodes on the optimal path and performing smoothing processing to obtain the robot's movement path. This invention improves convergence speed and search efficiency by using a non-uniform distribution of the initial pheromone concentration in the grid map, and shortens the planned path length by eliminating redundant nodes on the optimal path and performing smoothing processing.

This invention discloses a UAV gas inspection system and method based on dynamic route planning, relating to the field of gas inspection technology. The environmental modeling module acquires basic spatial data and building structure data within the inspection area, constructs a three-dimensional spatial environment model, identifies flyable spaces, and generates a flight space constraint model. The dynamic route planning module acquires a list of inspection targets, filters inspection targets based on the list, and generates a set of candidate inspection waypoints. Based on the candidate waypoint set and the flight space constraint model, a UAV inspection path is generated through coverage optimization and path cost optimization. The gas detection module collects and analyzes gas concentration data in real time, identifies abnormal concentrations, and triggers an alarm mechanism. The privacy protection module performs real-time analysis of the collected inspection images, identifies sensitive areas in the images, and automatically occludes or blurs these sensitive areas, achieving both gas safety detection and user privacy protection.

This invention discloses a real-time wireless communication system for mine shafts, belonging to the field of wireless communication technology. It includes a distributed wireless communication node set, a sparse observation node set, an interference reference acquisition node, and a controller. The distributed wireless communication node set is deployed along the shaft depth to form a multi-hop wireless communication network and carries communication services including at least alarm services. By setting up a sparse observation node set within the shaft and introducing a structured electromagnetic interference reference sequence output by the interference reference acquisition node, the controller can construct and continuously update a shaft propagation parameter field that varies with depth. This allows key propagation characteristics such as propagation attenuation, delay spread, and interference intensity to have quantifiable, alignable, and reproducible expressions. Therefore, compared to schemes relying solely on fixed configurations or single-point empirical measurements, this system can more accurately reflect the differentiated propagation environment along the shaft depth and improve the effectiveness of environmental modeling.