Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Unmanned vehicle dynamic obstacle avoidance method based on particle filtering

A particle filter and dynamic obstacle avoidance technology, applied in the field of unmanned vehicles, can solve problems such as pose estimation errors

Pending Publication Date: 2022-04-01
HUAIYIN INSTITUTE OF TECHNOLOGY
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the particle filter pose estimation of the existing adaptive Monte Carlo positioning algorithm has the following disadvantages: 1. When the current local environment of the unmanned vehicle has changed greatly compared with the preset static map local area, the current observation There are differences between the data and the preset static local environment. Matching the existing preset static local environment and then adjusting the particle weight will lead to pose estimation errors; 2. When the mileage displacement data has obvious errors, the estimated pose will also be corresponding Obvious error occurred

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
  • Unmanned vehicle dynamic obstacle avoidance method based on particle filtering
  • Unmanned vehicle dynamic obstacle avoidance method based on particle filtering
  • Unmanned vehicle dynamic obstacle avoidance method based on particle filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0054] A dynamic obstacle avoidance method for an unmanned vehicle based on particle filtering, the unmanned vehicle is provided with a total control system, and a motion control system, an inertial navigation system, a laser radar module and an IMU module that are respectively connected to the total control system; The above-mentioned general control system is loaded with maps and unmanned vehicle operating system ROS control software.

[0055] The total control system is based on the STM32 controller. The STM32 controller is connected to the Raspberry Pi platform through the bus, and the Raspberry Pi platform communicates with the host computer through the Wi-Fi wireless network to complete the data return.

[0056] The inertial navigation equipment includes odometers and gyroscopes. The odometers, gyroscopes and lidar ranging devices are connected to the overall control system through signal lines to provide the original data of the unmanned vehicle's own positioning to the ...

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 discloses an unmanned vehicle dynamic obstacle avoidance method based on particle filtering. An unmanned vehicle is provided with a master control system, and a motion control system, an inertial navigation system, a laser radar module and an IMU module which are respectively connected with the master control system. A map and unmanned vehicle operating system ROS control software are loaded in the master control system; the unmanned vehicle judges the speed and the position of the unmanned vehicle through an IMU module, scans the surrounding environment of the unmanned vehicle through a laser radar, compares a picture obtained through scanning with map information, and firstly removes known obstacles on a map; sampling the remaining obstacles by adopting a particle filtering mode, and predicting the movement speed and the movement trend of the obstacles relative to the unmanned vehicle; a DWA algorithm is combined with an obstacle particle filtering mode to avoid moving obstacles; and when the distance between the unmanned vehicle and the moving obstacle reaches a safe distance, the unmanned vehicle continues to move along the global optimal path.

Description

technical field [0001] The invention relates to the technical field of unmanned vehicles, in particular to a particle filter-based dynamic obstacle avoidance method for unmanned vehicles. Background technique [0002] With the rapid development of unmanned vehicle-related technologies, people's demand for unmanned vehicles is getting higher and higher, especially the positioning technology of unmanned vehicles. The positioning technology of unmanned vehicles usually provides the pose (including position and heading angle) of the unmanned vehicle in the world coordinate system in the environment. At the same time, the positioning technology of unmanned vehicles is the key technology for unmanned vehicles to realize autonomous navigation. [0003] For the global positioning of unmanned vehicles in the preset environment map, the existing method is to use particle filter positioning technology to locate mobile unmanned vehicles. The adaptive Monte Carlo algorithm of particle f...

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): G01S17/931G01C21/16G01C21/20
Inventor 魏晓倩赵志国毛康康王瑞万小康庞敏
Owner HUAIYIN INSTITUTE OF TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products