Type
Master's Research
Duration
2 years
Context
Industrial robotics, service robots
Output
Design guidelines + thesis
Context
The Research Question
As robotics systems move from industrial floors into everyday environments — maintenance, infrastructure, healthcare — the interfaces that humans use to control and monitor them become critical. Poor interface design in high-stakes robotic contexts doesn't just create frustration: it creates risk.
This research explored GUI design for service robotics systems, focusing on usability and human-machine interaction in everyday contexts. The central question: what design guidelines produce interfaces that are simultaneously learnable for novice operators and efficient for experienced ones?
Method
Research Approach
The research was conducted in two main contexts: EMMA (a robotic system for turbine maintenance at 13 Robotics) and ROSA (a hydroelectric plant monitoring system at LEAD Coppe/UFRJ). Both involved real operational environments with non-expert users.
- Task analysis: mapping operator workflows to identify cognitive load peaks and decision points
- Usability studies: structured lab testing with operators across skill levels
- Field research: observation in operational environments to capture real usage patterns vs. designed usage patterns
- Quantitative methods: surveys and A/B testing to validate design decisions
Findings
Design Guidelines for HMI
The research produced a set of design guidelines for robotic system interfaces, organized around three principles:
- Transparency of system state: operators need unambiguous feedback about what the robot is doing, why, and what it will do next. Ambiguity in state feedback was the leading cause of operator errors.
- Graceful degradation: interfaces must communicate failure states clearly without triggering panic responses. Alert design required careful calibration of urgency cues.
- Minimal mode switching: complex robotic systems often require operators to switch between monitoring and control modes. Reducing mode transitions significantly improved task completion time and error rate.
Impact
From Research to Practice
The guidelines developed through this research were applied directly to EMMA's operator interface and validated through subsequent usability rounds. The work contributed to broader HMI literature and informed interface standards for the robotics teams involved.
The methodological rigor developed in this research — particularly around task analysis and cognitive load assessment — became foundational to how I approach complex, high-stakes UX challenges in fintech and crypto products today.