Robotics & Machine Learning Daily News2024,Issue(Oct.30) :25-26.

Studies Conducted at Xi'an University of Posts and Telecommunications on Robotic s Recently Published (A Petri nets-based modeling method for multi robot path pl anning)

Robotics & Machine Learning Daily News2024,Issue(Oct.30) :25-26.

Studies Conducted at Xi'an University of Posts and Telecommunications on Robotic s Recently Published (A Petri nets-based modeling method for multi robot path pl anning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on robotics are disc ussed in a new report. According to news originating from Xi'an University of Po sts and Telecommunications by NewsRx editors, the research stated, "The construc tion of lunar bases is one of the core enabling technologies in current lunar ex ploration and development plans of various countries." Our news reporters obtained a quote from the research from Xi'an University of P osts and Telecommunications: "However, to eliminate the constraints of high tran sportation costs and limited manned space technology, a new research plan is to employ multi robot teams to build lunar bases. The key to this solution is how t o achieve path planning for complex tasks for multiple robots. Therefore, this a rticle takes the exploration and collection area, lunar soil collection, and lun ar soil transportation in the lunar base construction scene as complex task inpu ts, and studies a multi robot path planning modeling method based on Petri net m odel. Firstly, a Petri net model for multi robot motion was constructed. Meanwhi le, linear temporal logic(LTL) language was used to describe the related tasks o f lunar base construction. Finally, simulation validation was conducted in Matla b software and compared with the modeling method using switching systems."

Key words

Xi'an University of Posts and Telecommun ications/Emerging Technologies/Machine Learning/Robot/Robotics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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