Cost-effective autonomous industrial logistics robot

K. Thangaraj; R. Ragupathy; C. Adrien Periyanayagam; J. Muruganandham; D. Meena

Author(s)

K. Thangaraj Department of Electrical and Electronics Engineering, Sri Manakula Vinayagar Engineering College,Puducherry,India

R. Ragupathy Department of Electrical and Electronics Engineering, Sri Manakula Vinayagar Engineering College,Puducherry,India

C. Adrien Periyanayagam Department of Electrical and Electronics Engineering, Sri Manakula Vinayagar Engineering College,Puducherry,India

J. Muruganandham Department of Electrical and Electronics Engineering, Sri Manakula Vinayagar Engineering College,Puducherry,India

D. Meena Department of Electrical and Electronics Engineering, Sri Manakula Vinayagar Engineering College,Puducherry,India

Abstract

An autonomous logistics robot is designed for the purpose of transporting goods from one location to another without the need for human intervention. In previous models, robots relied on magnetic strips to navigate and reach their destinations. However, these conventional models had some drawbacks; if there were obstacles in their path, the robots would become stuck and unable to proceed towards their destination. To address these issues, a new model has been proposed. This model eliminates the necessity for human intervention and magnetic strips to guide the robot to its destination. Moreover, the cost of this model is significantly lower than that of the conventional approach. Consequently, this proposed model establishes the logistics robot as fully autonomous, eliminating the requirement for human interference. The robot achieves autonomous movement through the utilization of LiDAR Depth sensors and obstacle sensors. The Robotic Operating System (ROS) in conjunction with Raspberry Pi 3 is employed to map the path for the autonomous robot.

Publication Details

Page(s) 509-517

DOI DOI not available

Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 8, Year: 2024

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Keywords

ROS, LiDAR, path mapping, self-localization, autonomous navigation, SLAM

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