Evidence map›Paper›PMID 38544132›Full record

ArticleSensors (Basel, Switzerland)2024

A Robotics Experimental Design Method Based on PDCA: A Case Study of Wall-Following Robots.

Kai-Yi Wong, Shuai-Cheng Pu, Ching-Chang Wong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Kai-Yi WongDepartment of Electrical Engineering, National Sun Yat-sen University, Kaohsiung City 80424, Taiwan.ORCID 0000-0003-3867-701X
Shuai-Cheng PuDepartment of Electrical and Computer Engineering, Tamkang University, New Taipei City 25137, Taiwan.ORCID 0000-0003-3671-0381
Ching-Chang WongDepartment of Electrical and Computer Engineering, Tamkang University, New Taipei City 25137, Taiwan.ORCID 0000-0003-1095-728X

Funding

National Science and Technology Council (NSTC) of the Republic of China NSTC 111-2622-E-110-024
6 · The paper itself

Abstract

There is a lack of research that proposes a complete and interoperable robotics experimental design method to improve students' learning outcomes. Therefore, this study proposes a student-oriented method based on the plan-do-check-act (PDCA) concept to design robotics experiments. The proposed method is based on our teaching experience and multiple practical experiences of allowing students to do hands-on experiments. It consists of eight steps, mainly including experimental goals, experimental activities, robot assembly, robot control, in-class evaluation criteria, and after-class report requirements. The after-class report requirements designed in the proposed method can help students improve their report-writing abilities. A wall-following robotics experiment designed using the PDCA method is proposed, and some students' learning outcomes and after-class reports in this experiment are presented to illustrate the effectiveness of the proposed method. This experiment also helps students to understand the fundamental application of multi-sensor fusion technology in designing an autonomous mobile robot. We can see that the proposed reference examples allow students to quickly assemble two-wheeled mobile robots with four different sensors and to design programs to control these assembled robots. In addition, the proposed in-class evaluation criteria stimulate students' creativity in assembling different wall-following robots or designing different programs to achieve this experiment. We present the learning outcomes of three stages of the wall-following robotics experiment. Three groups of 42, 37, and 44 students participated in the experiment in these three stages, respectively. The ratios of the time required for the robots designed by students to complete the wall-following experiment, less than that of the teaching example, are 3/42 = 7.14%, 26/37 = 70.27%, and 44/44 = 100%, respectively. From the comparison of learning outcomes in the three stages, it can be seen that the proposed PDCA-based design method can indeed improve students' learning outcomes and stimulate their active learning and creativity.

Indexed as

autonomous mobile robotmulti-sensor fusionplan-do-check-act (PDCA)robot assembly and controlrobotics experiment design

Identifiers

PMID38544132
PMCPMC10975071

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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.