LTL-A*-A*optimal path planning method applicable to dynamic environment

A technology of optimal path planning and dynamic environment, applied in the direction of adaptive control, general control system, instrument, etc., can solve the problems that cannot be satisfied, must reach other points, etc.

Active Publication Date: 2017-03-15
ZHEJIANG UNIV OF TECH
View PDF6 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the pure A* algorithm is only aimed at simple tasks such as "from point A to point B, avoiding obstacles in the middle", and cannot satisfy practical applications such as keeping within a certain range (safety) and sequential access.

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
  • LTL-A*-A*optimal path planning method applicable to dynamic environment
  • LTL-A*-A*optimal path planning method applicable to dynamic environment
  • LTL-A*-A*optimal path planning method applicable to dynamic environment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention will be further described below in conjunction with accompanying drawing.

[0023] The LTL-A*-A* optimal path planning method suitable for dynamic environments mainly has the following contents: First, the robot operating environment is modeled as a weighted switching system model, and the task requirements are described by the linear temporal logic (LTL) task formula, and Convert it into a graph form (Büchi automata) through the LTL2BA toolkit; then, according to the linear sequential logic theory, the environmental information and task requirements are fused to construct a task-feasible network topology; then, the A* algorithm is used to search on the task-feasible network topology The optimal path; after that, the optimal path on the task-feasible network topology is mapped back to the weighted switching system to obtain the corresponding global optimal path in the environment; finally, when the local environment changes during the robot’s operat...

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 LTL-A*-A*optimal path planning method applicable to dynamic environment. The advantage of meeting complex mission requirements in actual application of linear temporal logic (LTL) and the advantage of being high in search efficiency of the A*algorithm are combined, and the method mainly includes LTL-A*global path optimization and local path optimization based on the A*algorithm. First, the optimal path meeting the task requirement in the environment is partially searched out through LTL-A*global path optimization; then, a robot tracks the global optimal path obtained through searching and detects environment information; finally, when local environment changes, a part segment in the global optimal path cannot continue allowing passage, the local optimal path is searched for by adopting the A*algorithm, the segment not allowing passage is bypassed, and operation continues along the global optimal path to complete an appointed task.

Description

technical field [0001] The present invention relates to the field of optimal path planning in dynamic environments. Aiming at the characteristics of dynamic changes in the working environment of mobile robots, the present invention proposes an LTL-A*-A* optimal path based on linear temporal logic (LTL) The planning method can perform secondary path optimization according to the environment change, so as to ensure that the mobile robot can efficiently complete the target task. Background technique [0002] In recent years, with the development of science and technology, people's demand for intelligent robots in production and life is increasing, and the requirements for the level of intelligence of robots are also getting higher and higher. At present, intelligent robots mainly have four major application areas: industrial robots, exploration robots, service robots, and military robots. According to the scope of application, the capabilities of various intelligent mobile rob...

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
IPC IPC(8): G01C21/20G05B13/04
CPCG01C21/20G05B13/041
Inventor 禹鑫燚郭永奎汪涛卢靓欧林林
Owner ZHEJIANG UNIV OF TECH
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
Try Eureka
PatSnap group products