Technology Category
Intelligent Robots: ManipulationPlanning, Routing, and Scheduling: Activity and Plan RecognitionHumans and AI: User Experience and Usability
Using Mobile AR for Rapid Feasibility Analysis for Deployment of Robots: A Usability Study with Non-Expert Users
🤖 AI Summary
Non-expert users face significant challenges in performing feasibility analysis for robot deployment on automated production lines, due to the complexity and time-consuming nature of conventional digital simulation workflows.
Method: This study proposes a lightweight evaluation method based on mobile augmented reality (AR), marking the first application of smartphone-based AR to industrial robot reachability analysis. The approach integrates real-time spatial perception, 3D kinematic visualization, interactive reachable workspace rendering, and simplified scene modeling—bypassing traditional offline simulation.
Contribution/Results: Evaluated with 22 non-expert users, the method achieved an average assessment time of 9.7 minutes per task, significantly reduced cognitive load, and attained a System Usability Scale (SUS) score of 4.6/5. By eliminating reliance on specialized robotics expertise and simulation software, it enables “capture-and-analyze” on-site evaluation, establishing a novel paradigm for rapid, context-aware decision-making in industrial environments.
Technology Category
Application Category
📝 Abstract
Automating a production line with robotic arms is a complex, demanding task that requires not only substantial resources but also a deep understanding of the automated processes and available technologies and tools. Expert integrators must consider factors such as placement, payload, and robot reach requirements to determine the feasibility of automation. Ideally, such considerations are based on a detailed digital simulation developed before any hardware is deployed. However, this process is often time-consuming and challenging. To simplify these processes, we introduce a much simpler method for the feasibility analysis of robotic arms' reachability, designed for non-experts. We implement this method through a mobile, sensing-based prototype tool. The two-step experimental evaluation included the expert user study results, which helped us identify the difficulty levels of various deployment scenarios and refine the initial prototype. The results of the subsequent quantitative study with 22 non-expert participants utilizing both scenarios indicate that users could complete both simple and complex feasibility analyses in under ten minutes, exhibiting similar cognitive loads and high engagement. Overall, the results suggest that the tool was well-received and rated as highly usable, thereby showing a new path for changing the ease of feasibility analysis for automation.
Problem
Research questions and friction points this paper is trying to address.
Simplifies feasibility analysis for robotic arm deployment
Targets non-experts with mobile AR-based tool
Reduces time and complexity of automation planning
Innovation
Methods, ideas, or system contributions that make the work stand out.
Mobile AR for robotic feasibility analysis
Simplified reachability analysis for non-experts
Sensing-based prototype tool for rapid deployment
🔎 Similar Papers
No similar papers found.
