Technology Category
Intelligent Robots: Human-Robot InteractionComputer Vision: Vision for Robotics & Autonomous DrivingNatural Language Processing: Safety and Robustness
Designing Robots to Help Women
🤖 AI Summary
This study addresses gender-specific societal safety risks faced by women—such as covert surveillance and inadequate health support—by pioneering the integration of gendered social challenges into robotic design frameworks. Employing speculative prototyping, it bridges sociotechnical insights with technical implementation to develop robotic applications for anti-spy-camera detection, health assistance, and daily support. In the first phase, a concealed-camera detection prototype was built using a YOLO-based object detection model deployed on an embedded drone platform, achieving 80% detection accuracy (IoU = 0.40) in real-world environments, thereby validating technical feasibility. The work extends human-robot interaction and robotics ethics design dimensions, advances interdisciplinary collaboration paradigms, and provides both methodological foundations and concrete case studies for developing more inclusive and secure technologies.
Technology Category
Application Category
📝 Abstract
Robots are being designed to help people in an increasing variety of settings--but seemingly little attention has been given so far to the specific needs of women, who represent roughly half of the world's population but are underrepresented in robotics. Here we used a speculative prototyping approach to explore this expansive design space: First, we identified some challenges that disproportionately affect women in relation to crime, health, and daily activities, as well as opportunities for designers, which were visualized in five sketches. Then, one of the sketched scenarios was further explored by developing a prototype, of a drone equipped with computer vision to detect hidden cameras that could be used to spy on women. While object detection introduced some errors, hidden cameras were identified with a reasonable accuracy of 80% (Intersection over Union (IoU) score: 0.40). Our aim is that these results could help spark discussion and inspire designers, toward realizing a safer, more inclusive future through responsible use of technology.
Problem
Research questions and friction points this paper is trying to address.
Addressing women's specific needs in robotics design
Developing robots to combat crimes disproportionately affecting women
Creating inclusive technology for a safer future
Innovation
Methods, ideas, or system contributions that make the work stand out.
Speculative prototyping explores women-specific robotics needs.
Robotic drone uses computer vision to detect hidden cameras.
Achieves 80% accuracy in identifying hidden surveillance devices.
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