Article ID Journal Published Year Pages File Type
242161 Advanced Engineering Informatics 2012 12 Pages PDF
Abstract

This research focuses on one of the major challenges in a tele-operated crane system, namely the user interface (UI). This UI should provide rich information retrieved from the field and display it properly in order to enhance the operation and decision-making processes involved in crane activities. In this research, we have designed two UIs specifically for a tele-operated crane system. The first UI is a four view system (quad-view) with a top view, left-side view, right-side view, and global view. The second UI has four views but uses additional guidance from Augmented Reality (AR) technologies. To test the UIs, we used a robot arm (KUKA KR16) to simulate a tele-operated crane in a testing environment. We also compared the UIs we designed against a conventional operation interface (i.e. operator’s view with oral guidance from the ground). We conducted a user test with two groups of participants: 5 crane operators and 30 students. Students constitute a novice group, and their results are interpreted from a statistical perspective. Using the student group, the interface’s learning curve can be evaluated. Operators constitute an expert group, which provides evidences for evaluating if the developed UIs are realistic and fit the needs of the field. We found that use of the UIs we designed resulted in a shorter erection time (336 and 343 s) than if the participants used the conventional operation interface (380 s). A self-evaluated index showing the difficulty of the tasks, the NASA task loading index (TLX), was calculated for each of the UIs. The UIs resulted in a higher TLX (52.0 and 53.2) than the conventional operation interface (32.2). In summary, the two UIs developed in this research are able to assist operators in operating remote cranes more efficiently and with less mental load than by using the conventional operation interface.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
Authors
, , , ,