Unlock instant, AI-driven research and patent intelligence for your innovation.

Active perception task path planning method, system, robot and controller

A path planning, mobile robot technology, applied in non-electric variable control, two-dimensional position/channel control, vehicle position/route/altitude control, etc., can solve the problems of low reliability and high consumption of complex task path planning. To achieve the effect of low cost and low consumption

Active Publication Date: 2022-02-11
SHANGHAI JIAOTONG UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of the above-mentioned shortcomings of the prior art, the object of the present invention is to provide an active perception task path planning method, system, robot and controller, which is used to solve the problem that the prior art is unable to move the path planning of complex tasks. , the technical problem of low reliability

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
  • Active perception task path planning method, system, robot and controller
  • Active perception task path planning method, system, robot and controller
  • Active perception task path planning method, system, robot and controller

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Specifically, such as figure 1 As shown, this embodiment provides an active sensing task path planning method, and the active sensing task path planning method includes:

[0056] Step S100, establishing a formalized model and linear sequential logic of the mobile robot to form a task automaton;

[0057] Step S200, constructing a stateful network based on the automaton, and extending the constructed stateful network based on active sensing to obtain a branch network with active sensing strategies;

[0058] Step S300, calculating the distance from each state in the branch network with the active sensing strategy to the endable state to form a task path.

[0059] Steps S100 to S300 of the active sensing task path planning method of this embodiment will be described in detail below.

[0060] Step S100, establishing a formalized model and linear sequential logic of the mobile robot to form a task automaton.

[0061] To synthesize an automaton that completes a task, abstra...

Embodiment 2

[0091] like Figure 7 As shown, this embodiment provides an active-aware task path planning system 100 , and the active-aware task path planning system 100 includes: an automaton construction module 110 , an expansion module 120 and a task path formation module 130 .

[0092] In this embodiment, the automaton building module 110 is used to build a formal model and linear sequential logic of the mobile robot to form an automaton for the task.

[0093] Specifically, in this embodiment, a representation of the formalized model of the mobile robot is:

[0094] G=(S,A,s 0 ,δ,AP,L);

[0095] Among them, S is the state of the robot; A is the action that the robot can take without active perception behavior; s 0 is the initial state of the robot; δ is the transfer function, which indicates the next state that the robot can reach after taking a certain action in the current state; AP is a series of atomic propositions used to characterize the attributes of the robot in certain state...

Embodiment 3

[0108] like Figure 9 As shown, this embodiment provides a controller 101, the controller 101 includes: a processor 1001 and a memory 1002; the memory 1002 is used to store computer programs; the processor 1001 is used to execute the memory 1002 stored computer program, so that the controller 101 executes the steps of the active sensing task path planning method as in Embodiment 1. Since the specific implementation process of the steps of the task path planning method based on motion perception has been described in detail in Embodiment 1, details will not be repeated here.

[0109] The processor 1001 is (Central Processing Unit, central processing unit). The memory 1002 is connected to the processor 1001 through the system bus to complete mutual communication, the memory 1002 is used to store computer programs, and the processor 1001 is used to run the computer programs, so that the processor 1001 executes the active sensing task path planning method. The memory 1002 may i...

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 provides an active perception task path planning method, system, robot and controller. The active perception task path planning method includes: establishing a formal model and linear sequential logic of a mobile robot to form a task automaton; The automaton constructs a state network, and expands the constructed state network based on active perception formation to obtain a branch network with an active perception strategy; distance to form a mission path. The invention comprehensively considers the active perception strategy and the movement strategy, and can better balance the relationship between the two, so that the mobile robot can complete the required complex tasks in a considerable environment, and at the same time, the total consumption can be minimized, and the cost of completing the task can be minimized. minimum.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to the technical field of robot task processing. Background technique [0002] Mobile robot is a comprehensive system that can realize environment perception, dynamic decision-making, action planning, control and execution. With the improvement of computer science and technology, the development of artificial intelligence, sensor technology and communication technology, mobile robot technology has also made great progress. Compared with traditional industrial robots, mobile robots with perception, autonomous decision-making and execution functions have broader prospects. They can replace humans to complete tasks in areas of high repetition, high risk and high complexity, and use mobile robots to achieve better results and higher efficiency. [0003] Robot task planning and motion planning are two basic issues in robotics research. At present, great progress has been made in the mo...

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 Patents(China)
IPC IPC(8): G05D1/02
CPCG05D1/0217G05D2201/0217
Inventor 殷翔赵佳伟李少远
Owner SHANGHAI JIAOTONG UNIV