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Task cooperation method between mobile robot and static sensor based on sensor network

A mobile robot and sensor network technology, applied in the information field, can solve problems such as insufficient recognition accuracy

Active Publication Date: 2019-08-27
SHANDONG UNIV
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Problems solved by technology

At present, the perception technology about human behavior has insufficient recognition accuracy and cannot meet the existing needs

Method used

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  • Task cooperation method between mobile robot and static sensor based on sensor network
  • Task cooperation method between mobile robot and static sensor based on sensor network
  • Task cooperation method between mobile robot and static sensor based on sensor network

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Experimental program
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Embodiment Construction

[0078] The present invention is described in detail below in conjunction with accompanying drawing:

[0079] Such as figure 1 As shown, the distributed information consistency estimation method of human joint points based on interactive multi-model realizes distributed processing of data and distributed fusion of information by constructing a dynamic distributed RGBD sensor network, and there is no centralized information processing in the network With the fusion center, sensor nodes only exchange information with neighboring nodes, and through a limited number of consistency iterations, the estimation of the perceived target state in the network is consistent.

[0080] The sensor network realizes the transmission of information through wireless communication. Each sensor is connected to a local processor, which can be a microcomputer or an ARM development board. After the local processor processes the information, it exchanges network data with neighboring nodes through wir...

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Abstract

The invention discloses a task cooperation method between a mobile robot and a static sensor based on a sensor network, constructs a dynamic distributed sensor network, and estimates the consistency of the obtained joint point distribution information of the human body; After the consistency is estimated, joint data association based on multi-features of color images and depth images is performed; distributed DTW human behavior intention recognition based on human behavior characteristics; on the basis of behavior recognition results, mobile robots use the contract network method to participate in bidding services. User-specific behaviors for robot services; when the static sensor estimates a certain joint point of the human body and the error exceeds the set value, a close-up viewing task request is initiated, and the adjacent mobile robot bids for the task and executes it to achieve close-up observation of a specific target . On the one hand, the present invention provides close-range observation for observation blind spots, and on the other hand, provides corresponding intelligent services for special behaviors of the human body.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a task cooperation method of a mobile robot and a static sensor based on a sensor network. Background technique [0002] Human behavior recognition based on multiple RGBD cameras has attracted extensive attention from researchers, and has been applied to human behavior detection in operating rooms, factory workshops, automobile assembly, indoor monitoring and other environments, effectively solving the problem of human occlusion and possible human- The robot collision problem has important application value. [0003] At present, human behavior perception based on multiple RGBD sensors is still in a centralized stage, requiring one or more data fusion centers to fuse 3D data and human skeleton joint point data, which requires high computing power and robustness for data fusion centers , weak resistance to network instability and low scalability. [0004] With the developmen...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06T7/20
CPCG06T7/20G06T2207/10024G06T2207/20081G06V40/20
Inventor 刘国良田国会
Owner SHANDONG UNIV
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