OpenRobOps + ROS Ecosystem
The robotics industry is stuck in a fragmentation crisis. While ROS standardized the device layer and Open RMF handles traffic negotiation, a massive gap remains in the middle: the core fleet management layer.
Today, most developers waste months reinventing the wheel. To get a fleet running, teams are forced to build custom cloud infrastructure, communication protocols, and database schemas just to monitor basic robot health. This "build trap" requires specialized skills in cloud security and network resilience that provide zero competitive differentiation for your robot.
We are contributing OpenRobOps (ORO) to the open source robotics community to break this cycle.
Robotics layer cake
We view the robot operations stack as a "layer cake" where three distinct open-source projects complement each other.
- Device Layer (ROS/ROS 2): Manages internal machine state, sensors, and local autonomy like obstacle avoidance.
- Operations Layer (OpenRobOps): Provides the fleet infrastructure, including secure connectivity, real-time observability, and robot health.
- Interoperability Layer (Open RMF): Acts as multi-fleet coordination and traffic deconfliction layer.
In other words, ORO provides the logic to manage a fleet of robots that ROS is lacking and that RMF requires to coordinate multiple robot types.
Bridge to production interoperability
For teams using Open RMF, ORO replaces ad-hoc "Free Fleet" implementations. While Free Fleet is useful for prototypes, it is ephemeral and lacks the security needed for the real world.
ORO brings production-grade capabilities to the open-source ecosystem. It maintains persistent records of state, supports end-to-end encryption, and captures the OS-level metrics necessary for root-cause analysis. Instead of coding custom RMF Fleet Adapters for months, integrators can now use ORO as a universal bridge.
Proven foundation
OpenRobOps 1.0 is a contribution from InOrbit.AI, representing years of development and experience scaling to thousands of robots. By releasing ORO under the Apache 2.0 license, we are giving developers a scalable, open-source solution they can extend and make part of their own commercial offerings.
Core capabilities include:
- Secure Connectivity: Outbound-only MQTTS or WebSockets, eliminating the need for VPNs.
- Adaptive Sampling: Dynamic data rates to prevent network saturation.
- Incident Management: Configurable engine for anomaly detection and alerting.
- Configuration as Code: YAML-based management for CI/CD workflows.
Community support
Our commitment to open source goes back several years. As a founding sponsor of the Open Source Robotics Alliance (OSRA) and an early contributor to Open RMF, we believe the future of robotics depends on community-driven infrastructure.
The work on OpenRobOps is supported by leaders across the robotics industry who recognize the need for a standardized operations layer. Geoffrey Biggs, CTO at Open Robotics, noted that ORO fills a critical gap in the open-source ecosystem by providing a fleet manager with native support for both ROS and Open RMF. Brian Gerkey, CTO at Intrinsic, compared the move to the early days of ROS, stating that ORO provides the necessary building blocks for fleet management that prevent developers from reinventing the wheel
Industrial and service partners are also integrating the platform into real-world applications. Felipe Garcia Lopez, Director of Robotic Systems at Kärcher, described ORO as a "game changer" that provides global access to commercial-grade operations software. Additionally, Florencia Grosso of Ekumen highlighted that a standard fleet management layer is essential for accelerating the transition of robotics from the lab to the real world. Further support comes from academic and industry leaders at the Stanford Robotics Center, Munich Institute for Robotics and Machine Intelligence (MIRMI) and Robotic Crew.
Stop building your own fleet manager. Start building your robot.
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