Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Obstacle avoidance method of unmanned aerial vehicle in complex dynamic environment

A dynamic environment, UAV technology, applied in three-dimensional position/channel control and other directions, can solve the problem of not being able to predict the trend of dynamic obstacles, and achieve the effect of improving robustness

Active Publication Date: 2022-04-12
SUN YAT SEN UNIV
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of this method is that the movement trend of obstacles is considered, and this method is integrated into the polynomial trajectory optimization algorithm, and the effect of obstacle avoidance is better. The disadvantage is that uniform linear motion cannot predict the trend of all dynamic obstacles. Obstacles with high maneuverability will cause large errors

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Obstacle avoidance method of unmanned aerial vehicle in complex dynamic environment
  • Obstacle avoidance method of unmanned aerial vehicle in complex dynamic environment
  • Obstacle avoidance method of unmanned aerial vehicle in complex dynamic environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Such as figure 1 As shown, a UAV obstacle avoidance method in a complex dynamic environment, including the following steps:

[0054] S1. Introduce the second-order constant velocity model and the third-order constant velocity model. In each model, the obstacle state information is first estimated through the model, and then filtered and predicted through the Kalman filter.

[0055] Consider random disturbances. For the maneuvering target under normal circumstances, that is, when the target moves in a straight line at a constant speed or uniform acceleration in most cases, the following second-order constant velocity (Constant Velocity, CV) model and third-order constant acceleration (Constant Acceleration, CA) model can be used .

[0056] Second-order constant velocity model:

[0057]

[0058] Three-order constant velocity model:

[0059]

[0060] In the formula, p, are the components of the position, velocity and acceleration of the obstacle; w(t) is the me...

Embodiment 2

[0095] This embodiment provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and capable of running on the processor, and the processor executes the computer program to realize the drone described in Embodiment 1 Obstacle avoidance methods in complex dynamic environments.

Embodiment 3

[0097] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the obstacle avoidance method for a UAV in a complex dynamic environment described in Embodiment 1 is implemented.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of autonomous navigation of mobile robots, in particular to an obstacle avoidance method of an unmanned aerial vehicle in a complex dynamic environment. Compared with an existing modeling method which is a constant-speed linear motion object, the method introduces the characteristics of a high-maneuverability target, introduces a plurality of models, and combines the models with an IMM algorithm, so as to predict the track of the obstacle, thereby improving the robustness. On the other hand, due to the fact that sensing has errors, uncertainty is considered during obstacle modeling. When the ellipsoid is modeled, the mass point information of the ellipsoid can be better estimated through a Kalman filter, and a plurality of sub-models can be predicted and estimated in parallel; the size of the ellipsoid is expanded with regard to the lapse of time in consideration of the safety, thereby making it possible to more safely avoid dynamic obstacles.

Description

technical field [0001] The invention relates to the technical field of autonomous navigation of mobile robots, and more specifically, to an obstacle avoidance method for unmanned aerial vehicles in complex dynamic environments. Background technique [0002] The realization of reasonable planning and obstacle avoidance of UAVs in a complex and dynamic environment is a key issue for autonomous navigation of UAVs. In a real flight environment, UAVs often face very complex scenes, and obstacles can be divided into static and dynamic ones, which have very high requirements for the stability and accuracy of UAV trajectory planning algorithms. . For static obstacles, the shapes of different obstacles will vary greatly, and reasonable avoidance is required. For dynamic obstacles, the trajectory is uncertain, and different types of maneuvers will make it difficult to track. The planning algorithm needs a reasonable obstacle prediction mechanism. At the same time, due to the limita...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/10
CPCY02T10/40
Inventor 曾祥伟成慧夏焕明
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com