The surveillance of critical infrastructures, industrial facilities, and public spaces requires constant supervision, typically relying on human personnel and fixed camera systems that present limitations in coverage and effectiveness under low-light conditions. These traditional solutions face challenges such as operator fatigue, lack of mobility, and the presence of blind spots, in addition to high operational costs.
In this context, researchers at UMH’s ARVC group have developed an autonomous ground robot equipped with multimodal sensors and AI algorithms for real-time patrol, anomaly detection, and human recognition. Its modular architecture and integrated software enable flexible deployment, coordinated multi-unit operation, and adaptive navigation across diverse indoor and outdoor environments.
Benefits of this technology:
- Achieves 98% human detection accuracy with thermal-visible fusion, covering up to 40 meters
- Operates continuously for up to 4 hours on a single charge
- Eliminates blind spots through autonomous mobile patrols
- Reconfigures routes dynamically in response to obstacles or changes
- Enables centralized control of multiple units via an intuitive interface
The represented institution is seeking commercial feedback on the technology to tailor it to market needs, and is also looking for a collaboration that leads to the commercial exploitation of the presented invention.
Institution: Automation, Robotics and Computer Vision Group (ARVC) at the Universidad Miguel Hernández (UMH)
Financing: AVI línea 1 valorización
Contacto: Ana Carlota de la Cruz Abad / a.cruz@viromii.com