Robot Operating System (ROS) Roadmap Topical Map

A practical migration timeline for a mid-size fleet (5–20 robots) is 9–18 months: 1–2 months of audit and dependency mapping, 3–6 months porting critical nodes and setting up CI/simulation, 2–4 months of field testing and interoperability (using ros1_bridge as needed), and 3–6 months of staged rollouts and operator training. This assumes dedicated engineers and access to test hardware; include contingency time for third‑party driver updates and custom middleware tuning.

For production, choose an LTS ROS 2 distribution (for example, Humble or the next LTS at the time of planning) because LTS releases prioritize ABI stability, security backports, and longer maintenance windows. Align your internal roadmap to the LTS lifecycle and track the upstream EOL calendar so you can plan upgrades at least 12–18 months before EOL.

Start by checking the ROS Index and package repositories for a native ROS 2 release; if none exists, run an automated dependency analysis (rosdep and ros1_bridge compatibility checks) to identify build, runtime, and API incompatibilities. Prioritize porting by runtime-percentage and hardware-coupling: sensor drivers and safety-critical control loops first, utility nodes later.

Common blockers are middleware assumptions (ROS 1's TCPROS vs ROS 2 DDS QoS), blocking synchronous APIs, reliance on tf1 vs tf2 differences, unsupported third‑party drivers or binary-only packages, and build-system changes (catkin → colcon/CMake conventions). Address these with interface refactors, DDS QoS tuning, vendor engagement for driver updates, and automated CI to catch regressions.

Use ros1_bridge for message-level interoperability between ROS 1 and ROS 2 where native ports are unavailable, and adopt a staged architecture where boundary nodes translate protocols rather than direct coupling across the fleet. Also isolate legacy stacks in containers or VMs so you can upgrade services one subsystem at a time while preserving operational uptime.

Budget for engineering time (estimate 0.5–2 FTE for 6–12 months depending on fleet size), test hardware and simulation licensing, CI/CD and containerization infrastructure, and vendor integration work; for a single robot expect $20k–$75k in engineering plus tools, whereas multi-robot fleets scale non-linearly due to integration and regression testing needs. Include a 20–30% contingency for third‑party driver or middleware tuning.

Implement automated unit tests, hardware-in-the-loop (HIL) or Gazebo integration tests, and nightly regression suites that run against both ROS 1 and ROS 2 environments. Use containerized CI pipelines (GitHub Actions, GitLab CI) with reproducible images to validate builds, run linters and static analysis, and execute end-to-end simulation before any field deployment.

Benchmark the leading DDS vendors (Fast-RTPS/ROS 2 default, RTI Connext, eProsima Fast DDS, CycloneDDS) against your latency, throughput, and reliability targets using representative workloads and network topologies. Define QoS profiles per message type—reliable ordered for commands, best-effort for high-rate sensors—and codify them in your architecture to avoid late-stage interoperability surprises.

ROS 2 adds middleware-level security (DDS Security plugins) and encourages node-level security practices, but you must design key management, authentication, and network isolation for production deployments. Integrate security testing into CI, use signed packages and reproducible builds, and document compliance controls (audit trails, access policies) for regulated environments like automotive or medical robotics.

Use a combination of rosdep for package dependency resolution, rosinstall/rosinstall_generator to snapshot stacks, automated static analysis tools (clang-tidy, flake8) adapted to ROS APIs, and custom scripts to produce a package-level compatibility matrix (ROS1 vs ROS2). Maintain an 'upgrade manifest' that lists blocking packages, workaround status, and owner for each dependency to drive project governance.