Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Research of dynamic path planning of feeding-pushing robot based on A Star algorithm

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2018 ASABE Annual International Meeting  1800811.(doi:10.13031/aim.201800811)
Authors:   Haotun LV, Xiaoxi CHEN, Gang WU, Shixiong LI, Liu YANG, Yongjun ZHENG
Keywords:   robot applications; A* algorithm; feeding-pushing robot; path planning; dynamic pushing.


With the modernization of agriculture, the automation equipment has been widely used in agriculture and animal husbandry. As an independent robot system, feeding-push robot can be flexibly applied to various dairy farms, pushing forage for cows all day, which can reduce labor and costs and improve feeding efficiency and milk production. During the feed pushing process, if there are a large amount of forage, it would affect the stability of the robot motion and push effect. To deal with these kinds of problems, the path planning method based on A*(A Star) algorithm for dynamic pushing was proposed. Firstly, a dairy farm grid-map was constructed. Secondly, the map was divided into different regions and the terrain cost factor was evaluated based on the characteristics of the region. The robot indirectly estimated the forage amount in the pushing process by collecting the current of the rotary motor. Then, the robot updated the terrain cost factor of corresponding regions and used A * search algorithm to find the path with the minimum cost of movement as the optimal path. Finally, a pushing experiment was conducted in the dairy farm. The experimental results showed that when the robot encountered a large amount of forage ,the robot could actively move away from the feeding fences to reduce the phenomenon of out-of-control motion, which verified the effectiveness of the path planning algorithm.

(Download PDF)    (Export to EndNotes)