journal article·2020-04-17Open access

Visual Information Requirements for Remotely Supervised Autonomous Agricultural Machines

Uduak Edet, Daniel Mann

Applied Sciences· Volume 10· Issue 8

Abstract

A study to determine the visual requirements for a remote supervisor of an autonomous sprayer was conducted. Observation of a sprayer operator identified 9 distinct “look zones” that occupied his visual attention, with 39% of his time spent viewing the look zone ahead of the sprayer. While observation of the sprayer operator was being completed, additional GoPro cameras were used to record video of the sprayer in operation from 10 distinct perspectives (some look zones were visible from the operator’s seat, but other look zones were selected to display other regions of the sprayer that might be of interest to a sprayer operator). In a subsequent laboratory study, 29 experienced sprayer operators were recruited to view and comment on video clips selected from the video footage collected during the initial ride-along. Only the two views from the perspective of the operator’s seat were rated highly as providing important information even though participants were able to identify relevant information from all ten of the video clips. Generally, participants used the video clips to obtain information about the boom status, the location and movement of the sprayer within the field, the weather conditions (especially the wind), obstacles to be avoided, crop conditions, and field conditions. Sprayer operators with more than 15 years of experience provided more insightful descriptions of the video clips than their less experienced peers. Designers can influence which features the user will perceive by positioning the camera such that those specific features are prominent in the camera’s field of view. Overall, experienced sprayer operators preferred the concept of presenting visual information on an automation interface using live video rather than presenting that same information using some type of graphical display using icons or symbols.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Human-Automation Interaction and Safety · Digital Transformation in Industry · 3D Surveying and Cultural Heritage

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Biosystems Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada

Funding

Natural Sciences and Engineering Research Council of Canada

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