Research on a Visually Assisted Efficient Blind-Guiding System and an Autonomous Shopping Guidance Robot Arm Adapted to the Complex Environment of Farmers' Markets.

Mei Liu, Yunhua Chen, Jinjun Rao, Wojciech Giernacki, Zhiming Wang, Jinbo Chen

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Mei LiuShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.ORCID 0000-0003-0078-7029

Yunhua ChenShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.ORCID 0009-0006-0832-6736

Jinjun RaoShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.ORCID 0000-0001-7998-2091

Wojciech GiernackiInstitute of Robotics and Machine Intelligence, Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, Piotrowo 3a, 60-965 Poznan, Poland.ORCID 0000-0003-1747-4010

Zhiming WangShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.

Jinbo ChenShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is great challenge for visually impaired (VI) people to shop in narrow and crowded farmers' markets. However, there is no research related to guiding them in farmers' markets worldwide. This paper proposes the Radio-Frequency-Visual Tag Positioning and Automatic Detection (RFTPAD) algorithm to quickly build a high-precision navigation map. It combines the advantages of visual beacons and radio-frequency signal beacons to accurately calculate the guide robot's coordinates to correct its positioning error and simultaneously perform the task of mapping and detecting information. Furthermore, this paper proposes the A*-Fixed-Route Navigation (A*-FRN) algorithm, which controls the robot to navigate along fixed routes and prevents it from making frequent detours in crowded aisles. Finally, this study equips the guide robot with a flexible robotic arm and proposes the Intelligent-Robotic-Arm-Guided Shopping (IRAGS) algorithm to guide VI people to quickly select fresh products or guide merchants to pack and weigh products. Multiple experiments conducted in a 1600 m

Indexed as

autonomous shoppingefficient navigationhigh-precision mappingrobotic arm guidancevisual aid

Identifiers

PMID40573670

DOI10.3390/s25123785

PMCPMC12196707

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.