Robot Software Version Verification: A Deployment Evidence Guide

A complete software version record for a robot deployment covers the base operating system and its installed packages; the robot middleware, including all active nodes and their version identifiers; the navigation and planning stack, including the map server, path planner, and obstacle avoidance modules; the perception pipeline, including camera drivers, image processing libraries, and object recognition models; the application layer, including the task execution software and any facility-specific workflow configuration; and any third-party software components embedded in any of these layers.

For robots that rely on cloud-connected services for any part of their functionality, the version of the cloud service API the robot is configured to use should also be part of the version record. The granularity of version tracking should match the granularity at which updates are applied: if the manufacturer distributes updates as a single monolithic package, the monolithic package version is the primary identifier; if individual components can be updated independently, each component should have its own version field in the record.

Software versions can be verified through several methods with varying evidence quality. Direct API query through the robot's software interface is the highest-quality verification method for software that exposes version information programmatically; it reads the version from the running software rather than from a record of what was installed. Package manager queries are reliable for software installed through the operating system's package management system; they show what version the package manager believes is installed, which is normally accurate but may diverge from the running version if software was installed outside the package manager.

Manufacturer device management platforms that report software versions for enrolled devices provide version information at a level of detail that depends on the platform's implementation. Manual file inspection of version files, binary version strings, or manifest files is available for software that does not expose version information through other means. The verification record should note the method used and assess its reliability, since a reviewer needs to understand how the version was determined when assessing the strength of the evidence.

Deployment teams sometimes focus on the application software version because it is the most visible layer and the one most directly associated with behavioral differences, while treating the platform and OS layers as less version-critical. This is a documentation gap with practical consequences. Platform version differences can change the behavior of application software in ways that are not visible from the application version alone.

OS security and behavior patches can modify system call behavior, networking behavior, or device driver behavior in ways that affect robot application performance. A software version record that captures only the application version while treating the platform and OS as fixed creates a systematic blind spot for troubleshooting software-related failures that originate below the application layer. All layers should be included in the version record, even when the expectation is that they will change less frequently than the application layer.

The record should note which layers are under the facility operator's update control and which are under the manufacturer's update control, because this distinction determines who needs to be involved when a version change in that layer needs to be reviewed.

Robot software applications depend on libraries, models, and data files that have their own version identities. Navigation systems depend on map data that changes as the facility layout is updated. Perception systems depend on object recognition model versions that determine what the robot can reliably detect.

Communication libraries have version identities that affect protocol compatibility with other systems. These dependencies are part of the complete software version record because changes to them can affect the behavior of the application software in the same way that changes to the application software itself do. For facility maps, the map version used for each operational session should be part of the software state record, since an outdated map is a common source of navigation failures in facilities that undergo physical changes.

For machine learning models used in perception, the model version, its training data provenance, and its known performance characteristics at the documented version are all part of a complete record that supports investigation of perception-related failures.

Many robot deployments involve iterative software updates during the commissioning and acceptance phase as the deployment team tunes the system's performance and resolves issues found during testing. In this context, version management requires tracking not just the current software state but the sequence of states the system has passed through, together with the test outcomes associated with each state. A version that was found to produce unacceptable behavior during testing should be recorded as a rejected version, not simply overwritten with the successor version.

The sequence of version, test, fail, update, retest, pass events is a critical part of the deployment history that supports the customer's understanding of how the acceptance-verified state was reached. When software is deployed through a mechanism that makes multiple versions available simultaneously, such as a staged rollout across multiple robots in a fleet, the version record must capture the current version for each individual unit rather than only the latest release version.

• Define the complete software stack to be version-tracked: OS, middleware, navigation, perception, application, and dependencies
• Capture software versions for all layers at the start of commissioning in the as-delivered state
• Verify software versions against the deployment specification before beginning acceptance testing
• Record the verification method used for each software component
• Capture a final software version record at the conclusion of acceptance testing
• Update the version record for every software update event, recording the previous version alongside the new version
• Track facility map versions and perception model versions as part of the dependency version record