CppCon 2026

What does it take to build a real-time embedded control system in modern C++, simulate its environment, command it from a browser, and watch it fly in 3D — all from the same open source ecosystem? This talk follows that pipeline end-to-end: from a C++23 real-time framework that schedules deterministic control loops across POSIX hosts and bare-metal microcontrollers, to GPU-accelerated simulation with CUDA, to web-based operations and telemetry, to live 3D visualization in Unreal Engine.

Attendees will see how a unified runtime architecture can span embedded control, simulation, diagnostics, operations, and visualization without fragmenting into separate software stacks. The talk explores deterministic scheduling, zero-allocation real-time design, cross-platform deployment, and integrating CUDA compute kernels directly into scheduled control loops without blocking execution. It also covers tooling for validating deterministic real-time behavior, along with techniques for streaming telemetry and sensor data between simulation and visualization layers in real time.

The presentation includes live demonstrations of a quadcopter simulation flying a programmed trajectory with lidar feedback, and a full-fidelity aircraft simulation with closed-loop autopilot, engine dynamics, and atmospheric turbulence — both running through the same real-time framework and rendered live in Unreal Engine. Whether you build flight software, robotics systems, industrial controllers, or simulation infrastructure, this talk presents practical architectural patterns for modern real-time systems in C++ that bridge embedded devices, GPU compute, and interactive visualization.

Large-scale robotics organizations operate diverse fleets of manipulators — 4-DOF arms on rails, 6-DOF standard manipulators on pedestals and fully mobile manipulators — each with different kinematics, hardware vendors, and software teams and researchers.

And engineers and researchers are opinionated.

As a team eventually you have one goal. Re-use as many abstractions; ideas and algorithms as you can while still allowing you the flexibility to explore new algorithms; ideas and approaches.

This talk presents a layered C++ architecture that solves this at scale. We present our core abstrcactions; a header-only Lie group library provides shared spatial math types (SE(3) poses, twists, wrenches); a trajectory library for motion planners and controllers; and a collision detection library from the same.

We will discuss how we moved from virtual functions to C++ concepts with zero overhead and the learnings along the way that allow us to write planning and control algorithms for various robots morphologies and sensing paradigms.

Critically, this architecture balances the needs of production at scale while enabling experimentation: researchers can prototype new collision algorithms, try a new physics engine, or test a novel trajectory representation — all without disrupting production code. The backend boundaries are where new ideas enter the system. You'll leave with three distinct C++ patterns for backend abstraction — compile-time traits, runtime interfaces, and type erasure — and an understanding of when to use each based on performance requirements and the need for experimentation.

C++ runs the world’s systems, and with that comes a responsibility for safety and stability. Avoiding AI entirely gives up on incredible potential benefits, but using AI without guardrails poses significant risks to our critical systems. How does AI fit into this world? This talk examines effective and ineffective approaches to using AI in systems that cannot afford “slop.” We will explore several case studies where AI produced significant value in C++, and several where it did not. The pattern that emerges is consistent: AI thrives when it is orchestrating well-defined, deterministic components, translating between them intelligently without being trusted to reason correctly on its own. When AI is asked to be the system rather than connect the system, things fall apart.

Much of the public criticism of C++ safety comes from vulnerabilities rooted in C patterns: raw pointer arithmetic, unchecked buffer indices, manual memory management. Modern C++ offers real answers to those problems through RAII, smart pointers, containers, and type-safe abstractions. But C++ also has its own distinct safety issues that have nothing to do with its heritage. Temporary lifetime rules that silently create dangling references. Iterator invalidation semantics that differ across containers in ways even experienced developers get wrong. Smart pointer ownership pitfalls that RAII cannot prevent. Coroutine frames that outlive their captured locals. Implicit conversions that turn a safe string into a dangling view between one line and the next. These are purely C++ problems. They compile cleanly, look correct in code review, and ship to production.

A survey of public CVE reports and security-fix commits across prominent open-source C++ projects shows the same patterns recurring again and again. This talk walks through those patterns, in code that looks correct in review, compiles cleanly, and then breaks at runtime. The session is aimed at intermediate-to-experienced C++ developers who already know modern C++ but want a working catalog of the subtle patterns that ship past typical code review.

Recognizing these patterns has long been the domain of library authors and security researchers. This talk distills a catalog from real-world fixes for everyone else: not a prescriptive standard like the Core Guidelines, but a pattern-recognition toolkit any C++ developer can apply in their next code review. The session also makes the case for expanding the community-level safety conversation to give these C++-unique patterns the same attention as the C-heritage debates.

Air-gapped systems used to be protected by what they could not reach. That assumption breaks when telemetry, sensor data, and diagnostic output leave the system and AI model-influenced behavior comes back in, even without a network connection.

This talk examines the C++ engineering decisions that determine whether that data exchange is safe or silently dangerous. The problems are C++-specific and subtle: struct layout and padding that corrupt data silently across serialization boundaries; undefined behavior in type-punned casts that passes tests but breaks under a different compiler or optimization level; ownership and lifetime assumptions that hold inside the system but become dangling references once data crosses a trust boundary; allocator and exception constraints in no-exception embedded environments that make standard validation patterns unavailable.

We will look at how C++ systems in industrial, embedded, and safety-critical environments can export logs, telemetry, and traces into AI pipelines without creating feedback loops that affect production behavior in unverified ways. The engineering controls are concrete: typed serialization boundaries that make layout assumptions explicit, schema validation that survives ABI differences between host and edge, provenance tracking built into ownership types, deterministic guardrails around probabilistic inference outputs, and fail-safe fallbacks that don't rely on the model being correct.

Attendees will leave with a design approach for integrating AI-adjacent workflows into high-integrity C++ systems. One that treats the data boundary as a first-class security surface, not an afterthought.

To navigate safely, a robot must simultaneously ingest high-frequency sensor data, compute complex spatial algorithms, and publish control commands. Historically, frameworks like ROS 2 have handled this via asynchronous callbacks. However, as autonomous stacks scale, relying heavily on unstructured callbacks can obscure control flow, making state synchronization difficult and robust task cancellation notoriously complex.

This talk explores how to transform unstructured, callback-based architectures in a robotics navigation stack into declarative pipelines using structured concurrency (specifically, C++ Senders and Receivers via stdexec). Attendees will dive into two real-world architectural examples: a collision monitor and a waypoint follower, showcasing readable logic pipelines, thread-hopping between an event loop and a static thread pool, and clean task cancellation.