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FORT Robotics brings outside-in safety to robots with Nvidia Halos

FORT Robotics brings outside-in safety to robots with Nvidia Halos

Key takeaway

  • FORT Robotics announced it is joining Nvidia's Halos for Robotics ecosystem to bring outside-in safety capabilities to autonomous robots.

  • The new approach uses external infrastructure sensors and AI agents alongside onboard perception to enable robots to operate safely at higher speeds in dynamic warehouse and factory environments, reducing costly slowdowns while protecting workers and infrastructure.

3 Key Points

  1. What happened

    FORT Robotics joined Nvidia's Halos for Robotics ecosystem and is demonstrating an agentic safety application using Nvidia's Outside-In Safety Blueprint this week at the Automate conference in Chicago. The solution combines external infrastructure sensors and visual AI agents with onboard robot perception to deliver real-time functional safety.

  2. Why it matters

    Traditional robot safety systems rely only on onboard sensors and force robots to operate conservatively, slowing them down in dynamic warehouse and factory environments. Outside-In Safety automatically adjusts robot efficiency across changing environments, which means warehouses and factories can run robots faster while keeping workers safe—unlocking cost savings from processes like trailer unloading, inventory replenishment, and product assembly.

  3. What to watch

    FORT is a member of Nvidia's AI Systems Inspection Lab, the world's first ANSI National Accreditation Board (ANAB)-accredited inspection lab designed specifically for physical AI and autonomous systems. The lab verifies functional safety, cybersecurity, and AI compliance for autonomous vehicles, robotics, and sensor technologies.

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Context & Analysis

FORT Robotics, which has long been an industry standard for safety-certified control in autonomous systems, is extending its Trust Layer platform by integrating with Nvidia's Outside-In Safety Blueprint. This collaboration addresses a real operational constraint: robots in real-world settings encounter unpredictable conditions—crowded warehouses, moving workers, changing inventory layouts—that traditional onboard-only safety approaches cannot handle efficiently. By forcing robots into conservative operating modes to guarantee safety, companies lose productivity and return on investment.

The outside-in approach leverages hardware already present in many facilities: building-mounted cameras and other external sensors. Nvidia's IGX Thor compute and Holoscan Sensor Bridge connect these sensors to visual AI agents that continuously monitor the robot's surroundings and anticipate risks. This expanded perception allows robots to modulate their speed and caution dynamically—operating at full efficiency when conditions are clear, and automatically slowing down when workers enter the space or unexpected obstacles appear. For businesses, this means the same robot hardware can deliver both safety and productivity gains without requiring expensive facility redesigns.

The accreditation of FORT and Nvidia through the ANSI National Accreditation Board's first-of-its-kind inspection lab for physical AI signals that safety in autonomous systems is moving from a cost center to a certifiable competitive advantage. Companies that can deploy robots faster and more safely in mixed human-robot environments may capture early market share in warehouse automation and manufacturing.

FAQ

How does outside-in safety differ from traditional robot safety systems?
Traditional systems rely only on onboard sensors and operate under conservative constraints suited to predictable machines in bounded settings. Outside-In Safety uses external infrastructure sensors and visual AI agents to provide real-time perception, allowing robots to dynamically adapt to constantly changing environments while maintaining safety.
What industries will benefit from this solution?
The offering targets warehousing, manufacturing, and other automated industries. Specific processes mentioned include trailer truck unloading, inventory replenishment, and product assembly.
What is the Nvidia AI Systems Inspection Lab?
It is the world's first ANSI National Accreditation Board (ANAB)-accredited inspection lab designed specifically for physical AI and autonomous systems. It provides a unified framework to verify functional safety, cybersecurity, and AI compliance for autonomous vehicles, robotics, and sensor technologies.
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