UI for Deep Sea Robot Operation: Exploring Simplicity & Metaphor
Project Overview
This research focuses on improving the usability of the interface for Long-Range Autonomous Underwater Vehicles (LRAUVs) used by MBARI (Monterey Bay Aquarium Research Institute). Our work examines how interface design can reduce cognitive load, enhance situational awareness, and support scientists and engineers in their mission planning and supervision tasks.
Iterative Research & Design Approach
Our research employed an iterative, mixed-methods approach, integrating both usability testing and human factors analysis.
Understanding User Pain Points
Conducted cognitive walkthroughs (Cog-Walks) to assess friction points in the interface.
Identified challenges such as information overload, hidden critical data, and difficulty in assessing overall system health.
Observed and participated in inter-organization chat channels to identify missing components of skill sharing and team support not visible in the official UI.
Measuring Impact
Task Performance: Measured task time and error rates.
Cognitive Load: Assessed using the NASA-TLX workload index.
User Feedback: Collected via exit interviews to guide design iteration.
Key Design Interventions
Leveraging Metaphor: Introduced metaphorical imagery to simplify system state assessments.
Reducing Cognitive Overload: Reorganized UI to silo backend data while prioritizing essential mission-critical information.
Enhanced Visualization: Improved map and mission planning tools for more intuitive use.
Initial Findings
This research highlights the power of simplicity and metaphor in designing interfaces for complex systems. Our iterative process demonstrates how targeted UX interventions can transform high-stakes operational workflows.
Earlier iterations of the UI over inundated users with unclear message streams, obfuscating the most needed information.
Updated UI portion focused on representing the most commonly desired streams of information that scientist teams used to manage their missions.
Updated path planning and mapping system to help clarify the temporal aspects of the LRAUV missions.