Devices operating in real-world environments, such as robots, autonomous machines and drones, must continuously perceive their surroundings, understand context, navigate freely and interact safely and naturally with people and objects in their vicinity. AI enables these devices to interpret complex visual and sensor data, adapt to dynamic environments, and move beyond scripted behavior toward more flexible and intelligent operation across a growing range of platforms, from service and industrial robots to mobile and outdoor systems.

Robotic perception is inherently multi-modal, combining vision (camera) with additional sensors such as depth, IMUs, and lidar to build an accurate understanding of the environment. AI is required to detect objects, estimate depth & motion, and enable outdoor and indoor navigation, the latter often in dynamic and cluttered spaces where traditional localization methods like GPS fall short.

These workloads are latency-sensitive and bandwidth-intensive, making edge execution essential. Hailo accelerates large vision models and sensor-fusion pipelines efficiently, enabling reliable and safe navigation and perception while keeping the device autonomous, responsive and power-efficient.

Many physical AI applications operate in low-light, nighttime, or otherwise visually degraded environments, outdoor service robots, agricultural systems, security and inspection robots, and mobile platforms operating around the clock. In these conditions, sensor noise degrades visibility and downstream perception accuracy. AI-based low-light denoising and video enhancement models significantly improve image quality, enabling reliable detection, navigation, and decision-making.

Hailo’s unique and proprietary vision enhancement algorithms enable superior low-light visibility, preserving color, texture, sharpness, and fine details, and reducing motion blur at extreme low-light conditions (<0.01 LUX). This improves low-light and night-time perception without increasing sensor cost, power consumption, or system complexity.

Voice-to-Action enables seamless human-machine interface, allowing people and robots to interact naturally by converting spoken language into real-world actions. This pipeline typically includes speech-to-text, intent understanding, and decision-making, allowing users to control robots without complex, hardware-based interfaces. Specialized reasoning LLMs can enhance the robot’s ability to perform complex tasks.

Running this pipeline locally ensures low latency, privacy, and reliability, even without network connectivity. Hailo enables highly efficient execution of Whisper-class speech models and small LLMs at the edge, supporting agentic and physical AI capabilities that deliver intuitive, real-time human-robot interaction for service robots, industrial automation and assistive systems.