Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments

Mincong Kong; Chaoqun Xiang; Yaxuan Cao; Yilu Guo

doi:10.47297/wspdecWSP2515-797313.20261001

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments

Volume 10, Issue 1

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments
Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments
Qingdao City University, Qingdao, Shandong, 266106, China
Vol. 10, Issue 1, Pages: 61-66(2026)
Published：30 January 2026
DOI：10.47297/wspdecWSP2515-797313.20261001
Accepted：

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Kong Mincong,Xiang Chaoqun,Cao Yaxuan,et al.Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments[J].Development Economics of China,2026,10(01):61-66.
DOI：

Kong Mincong,Xiang Chaoqun,Cao Yaxuan,et al.Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments[J].Development Economics of China,2026,10(01):61-66. DOI： 10.47297/wspdecWSP2515-797313.20261001.

摘要

Abstract

At present

in most warehouse environments

the accumulation of goods is complex

and the management personnel in the control of goods at the same time with the warehouse mobile robot trajectory interaction

the traditional mobile robot can not be very good on the goods and pedestrians to feed back the correct obstacle avoidance strategy

in order to control the mobile robot in the warehouse environment efficiently and friendly to complete the obstacle avoidance task

this paper proposes a deep reinforcement learning based on the warehouse environment

the mobile robot obstacle avoidance Algorithm.

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Keywords

references

Fiorini P , Shiller Z . Motion planning in dynamic environments using velocity obstacles [J ] . The International Journal of Robotics Research , 1998 , 17 ( 7 ): 760 - 772 .

Mnih V , Kavukcuoglu K , Silver D , et al . Human-level control through deep reinforcement learning [J ] . Nature , 2015 , 518 ( 7540 ) : 529 - 533 .

Chiang H T L , Faust A , Fiser M , et al . Learning navigation behaviors end-to-end with AutoRL [J ] . IEEE Robotics and Automation Letters , 2019 , 4 ( 2 ) : 2007 - 2014 .

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