은 스마트 리빙 · 2025
Vega Connect 로봇 제어 인터페이스
by Xueyun Tang and Xiaomeng Tang
- A' Design Award 은상 2025 in 스마트 리빙
- CLIENT: Dexmate Inc.
- Estimated Number of Design Views: 60,037
- Verification code A674F99E2F · Verify this award
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About Vega Connect 로봇 제어 인터페이스
Vega Connect는 가정 사용자를 위해 설계된 로봇 제어 인터페이스입니다. 이 시스템은 모바일 애플리케이션과 웹 포털을 결합합니다. 모바일 애플리케이션을 통해 사용자는 일상적인 언어로 집안일을 요청할 수 있으며, 각 요청은 정밀한 로봇 동작으로 변환되고 진행 상황이 실시간으로 표시됩니다. 3차원 디지털 트윈은 로봇과 그 주변 환경을 표시하여 원격 모니터링을 지원합니다. 웹 포털에서는 각 가정에 맞는 맞춤형 루틴을 생성할 수 있습니다. 이 디자인의 목표는 기술적 교육 없이도 첨단 로봇을 사용할 수 있도록 하는 것입니다.
About the A' Design Award 은상
Vega Connect 로봇 제어 인터페이스, 이 작품은 A' Design Award 은상 수상작으로, 최상급이며 아름답고 인상적인 디자인에 수여되는 비범하게 권위 있는 인정입니다. 은상 수상작은 대단히 뛰어나고 매우 창의적인 작품으로, 디자이너의 탁월한 전문 지식, 재능, 통찰력을 보여 줍니다. Vega Connect 로봇 제어 인터페이스, 이 작품은 훌륭한 대표작으로서 매우 전문적이고 깊이 있게 혁신적일 것으로 기대됩니다. 이 은상 수상 디자인은 예술, 과학, 디자인, 기술의 경계를 넓히는 데 이바지하는 주목할 만하고 찬사를 받는 발명품입니다. Vega Connect 로봇 제어 인터페이스, 이 작품은 모두가 부러워하는 창작물로서 욕망을 일깨우고 긍정적인 감정을 불러오며 경탄과 경이로움을 불러일으킵니다.
Press Kit
- Unique Properties
- Vega Connect redefines human-robot interaction through its pioneering dual-interface system that bridges advanced robotics with an intuitive user experience. Unlike conventional systems requiring technical expertise, our solution transforms complex robotic programming into natural interactions accessible to all users regardless of technical background. The mobile interface enables effortless task delegation through conversational commands, while the complementary web portal offers sophisticated customization capabilities. This architecture represents a paradigm shift in robotics—creating technology that adapts to human communication patterns rather than forcing users to adapt to machines, thereby democratizing access to revolutionary capabilities previously reserved for specialists.
- Dimensions & Packaging
- The Vega Connect system integrates multimodal interaction capabilities enabling humans to control robots via natural language, hand gestures, and facial expressions through advanced LLM/VLM models. The 3D digital twin technology provides immersive visualization of robot operations and surroundings, facilitating seamless remote monitoring and control across unlimited distances. The middleware abstracts complex robotics commands into intuitive interactions, allowing users to automate routine tasks through conversational interfaces and scheduling functionality.
- Tags
- Human-robot interaction, robot interaction system, home robot interface, AI-driven automation, personal robotics, dual-interface system, intuitive robot control, natural language interaction, general-purpose robot
- Production Technology
- Vega Connect bridges the gap in robotics: industrial robots need expertise, while consumer robots are single-purpose. As AI general-purpose robots tackle diverse tasks, seamless human-robot interaction is essential. Dexmate team has developed a multimodal interaction framework utilizing natural language processing, gesture recognition, and intuitive web interfaces. The system employs real-time 3D visualization with digital twin technology, implementing semantic mapping between human commands and robotic execution paths.
- Design Challenge
- The fundamental challenge was reconceptualizing robot interaction for non-technical users while maintaining advanced functionality. Historically, robotics interfaces prioritized engineering precision over usability, creating significant adoption barriers. Our team struggled to develop a system that satisfied both the accessibility needs of everyday users and the precision requirements of complex robotic operations. The breakthrough came through extensive user testing revealing distinct interaction patterns across demographics, leading to our dual-interface architecture. Technical obstacles included developing reliable natural language processing for household contexts and creating abstraction layers that translated simple commands into complex motion sequences while maintaining safety parameters.
- Research
- Our user-centered research combined ethnographic observation and usability testing with 35 households across three generations. We identified critical barriers in robotics adoption through 250+ hours of in-home studies using eye-tracking and think-aloud protocols. Testing revealed traditional interfaces achieved only 27% task completion rates versus 89% with natural language commands. This directly shaped Vega Connect's dual-interface approach, adapting to human behavior rather than forcing humans to adapt to technology.
- Inspiration
- The Vega Connect project addresses a fundamental disparity in robotics: while AI-powered robots grow increasingly capable, their interfaces remain engineered for specialists rather than everyday users. Recognizing that these advanced robots will soon enter domestic settings, Dexmate developed an intuitive interaction system that bridges this accessibility gap. Our solution enables non-technical users to communicate naturally with sophisticated robotic systems, democratizing access to this transformative technology.
- Project Duration
- The Vega Connect robot-control interactive system design and its user testing began in November 2024 in California, USA, and concluded in March 2025. Technical implementation for both web and mobile platforms commenced in January 2025 and is currently ongoing in preparation for a wide market release.
- Operation Flow
- Vega Connect transforms robot control from complex programming to natural conversation. Users simply open the mobile app and request tasks using everyday language or intuitive taps—"clean the kitchen" or "fold laundry"—eliminating technical barriers. The system translates these simple requests into precise robotic actions while providing real-time progress updates. For personalization, the complementary web portal allows users to easily create custom routines specific to their home environment. This dual approach delivers superior results by adapting to human communication patterns rather than forcing users to learn technical commands, making advanced robotics accessible to everyone regardless of technical expertise.
- Patents
- Copyrights belong to Dexmate Inc., 2025
- Image Credits
- Dexmate Inc.