Learning and Comfort in Human–Robot Interaction: A Review
Source abstract
Abstract
Collaborative robots provide prospective and great solutions to human–robot cooperative tasks. In this paper, we present a comprehensive review for two significant topics in human–robot interaction: robots learning from demonstrations and human comfort. The collaboration quality between the human and the robot has been improved largely by taking advantage of robots learning from demonstrations. Human teaching and robot learning approaches with their corresponding applications are investigated in this review. We also discuss several important issues that need to be paid attention to and addressed in the human–robot teaching–learning process. After that, the factors that may affect human comfort in human–robot interaction are described and discussed. Moreover, the measures utilized to improve human acceptance of robots and human comfort in human–robot interaction are also presented and discussed.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Social Robot Interaction and HRI · Robot Manipulation and Learning · Human-Automation Interaction and Safety
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Automotive Engineering, Clemson University, Greenville, SC 29607, USA
References (100+)
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