HORUS Roadmap to Beta

1. Core Framework Enhancements

Goal: Improve Link (process-to-process) communication mechanism for multi-process robotics systems

Tasks:

  • Reduce Link latency: Target sub-nanosecond (currently ~10-20μs for network transport)
    • Optimize TCP socket communication
    • Benchmark against DDS, ZeroMQ, and raw TCP
  • Reliability improvements:
    • Connection recovery and automatic reconnection
    • Heartbeat mechanism for connection health monitoring
    • Message acknowledgment and retry logic
    • Graceful degradation on network issues
  • Discovery mechanism:
    • Automatic node discovery on local network
    • Service advertisement and lookup
  • Security:
    • TLS/SSL encryption for remote connections
    • Authentication and authorization
    • Message signing and verification

1.2 Hub Performance & Features

Tasks:

  • Latency improvements:
    • Optimize cache-line alignment (currently good, validate on ARM)
    • SIMD optimizations for large message copying
    • Lock-free queue optimizations
    • Profile and eliminate any remaining bottlenecks
  • Message history:
    • Configurable history depth per topic
    • Late-joiner support (get last N messages)
    • Message replay capability
  • Topic statistics:
    • Publish rate monitoring
    • Message size tracking
    • Dropped message detection
  • Dynamic type support:
    • Runtime message type registration
    • Generic message containers
    • Type introspection and validation

Validation:

  • Achieve consistent <300ns for 16B messages
  • Benchmark on Raspberry Pi, Jetson, and x86
  • 1000+ topic stress test

1.3 Scheduler Enhancements

Tasks:

  • Real-time scheduling:
    • Priority inheritance for nested node calls
    • CPU affinity/pinning support
    • Real-time thread priority (SCHED_FIFO)
    • Watchdog for missed deadlines
  • Execution control:
    • Rate limiting per node
    • Conditional execution (run only when data available)
    • Node dependency graphs
    • Parallel execution where safe
  • Monitoring:
    • Execution time tracking per node
    • CPU usage per node
    • Memory allocation tracking
    • Publish statistics to dashboard

Validation:

  • 1kHz control loop demonstration
  • Multi-node real-time scheduling test
  • Deterministic execution benchmark

2. Developer Tools

2.1 Dashboard Enhancements

Enhanced features:

  • Topic recording/playback UI
  • Performance profiling view
  • Log filtering and search
  • Configuration editor
  • Remote dashboard (connect to robot over network)

2.2 Remote Deployment (Daemon)

Production Tasks:

  • Versioning & rollback:
    • Deploy specific versions
    • Rollback to previous version
    • Version history tracking
    • Diff between deployed versions
  • Multi-target deployment:
    • Deploy to multiple robots simultaneously
    • Group deployment (fleet management)
    • Staged rollout (canary deployments)
  • Health monitoring:
    • Deployment status tracking
    • Runtime health checks
    • Automatic restart on crash
    • Resource monitoring (CPU, memory, disk)
  • Security:
    • SSH key authentication
    • Encrypted transfers
    • Audit logging
    • Access control (who can deploy what)
  • CI/CD integration:
    • GitHub Actions integration
    • GitLab CI integration
    • Automated deployment on push
    • Deployment webhooks

Validation:

  • Deploy to 10+ robots simultaneously
  • Zero-downtime update demonstration
  • 30-day uptime test with automatic recovery

3. Language Bindings

3.1 Python Bindings

Missing Features:

  • Type hints:
    • Full .pyi stub files
    • Type annotations for all APIs
    • IDE autocomplete support (VSCode, PyCharm)
  • Documentation:
    • Docstrings for all functions
    • Sphinx-compatible documentation
    • Example notebooks (Jupyter)
  • Advanced features:
    • Async/await support (asyncio integration)
    • Context managers for resource cleanup
    • Pythonic error handling
    • NumPy array zero-copy support
    • Pandas DataFrame integration
  • Package distribution:
    • PyPI package (pip install horus-robotics)
    • Wheels for Linux/Mac/Windows
    • Conda package (optional)
  • Testing:
    • pytest test suite
    • Property-based testing (Hypothesis)
    • Performance benchmarks

Validation:

  • 100% type hint coverage
  • Documentation coverage >90%
  • 5+ real Python projects using HORUS

3.2 C Bindings

Missing Features:

  • Complete API coverage:
    • Full Node API
    • Scheduler API
    • All message types
    • Error handling
    • Resource cleanup
  • Header file organization:
    • Single horus.h header
    • Separate headers per module
    • Documentation comments
  • Build system integration:
    • CMake support
    • Meson support
    • pkg-config file
    • Static/dynamic library options
  • Examples:
    • Arduino/embedded examples
    • Linux driver examples
    • Real-time system examples
  • Documentation:
    • Doxygen documentation
    • C API reference guide
    • Migration guide from C++ frameworks

Validation:

  • Compile on embedded Linux (RPi, Jetson)
  • Integration with existing C codebases
  • Performance parity with Rust API

4. Simulation & Visualization

4.1 sim2d

Enhancements:

  • Physics improvements:
    • Configurable physics parameters (friction, damping, etc.)
    • Soft body physics (cables, cloth)
    • Joint constraints (prismatic, revolute)
  • Sensors:
    • 2D LiDAR (ray casting)
    • Wheel encoders with noise
    • IMU simulation
    • Contact sensors
  • Visualization:
    • Robot trail rendering
    • Sensor visualization overlays
    • Performance metrics overlay
    • Recording to GIF/video
  • Scenarios:
    • Pre-built demo worlds
    • Obstacle course generator
    • Multi-robot scenarios
  • Documentation:
    • Tutorial: Build a robot in sim2d
    • API reference
    • Physics parameter guide

Validation:

  • 60 FPS with 10+ robots
  • Sim-to-real transfer demonstration
  • Used in 3+ tutorials

4.2 sim3d

Goal: Production-grade 3D robotics simulator with RL support

**Phase 1: **

  • Basic 3D rendering (Bevy 3D + Rapier3D)
  • URDF robot model loading
  • Transform frame (TF) visualization
  • Basic sensors (3D LiDAR, camera, IMU, GPS)
  • HORUS Hub integration
  • Differential drive kinematics
  • Simple world configuration (YAML)

**Phase 2: **

  • Headless mode (no rendering)
  • Vectorized environments (1000+ parallel)
  • Gymnasium/Gym API (Python)
  • Domain randomization
  • Observation/reward framework
  • Fast reset (<1ms)
  • Example RL tasks (navigation, manipulation)

**Phase 3: **

  • Articulated robots (robot arms, grippers)
  • Advanced sensors (depth camera, RGB-D, force/torque)
  • Scene editor (GUI)
  • Recording/playback system
  • Plugin system
  • ROS2 bridge (optional interop)
  • Gazebo world import
  • Benchmark suite

Validation:

  • 60 FPS visual mode
  • 100K+ steps/sec headless RL mode
  • URDF loading for 20+ robot models
  • Sim-to-real gap <10% for navigation task
  • Complete documentation and tutorials

5. Registry & Ecosystem

5.1 Package Registry

Enhancements:

  • Package features:
    • Dependency resolution (transitive dependencies)
    • Version constraints and compatibility
    • Platform-specific packages (x86, ARM, etc.)
    • Source vs binary packages
    • Package checksums and signatures
  • Discovery & search:
    • Full-text search
    • Tag-based filtering
    • Trending packages
    • Recently updated
    • Most downloaded
    • Quality score/badges
  • Developer tools:
    • Package analytics dashboard
    • Download statistics
    • User feedback/ratings
    • CI/CD integration for auto-publish
    • Pre-publish validation
  • Documentation hosting:
    • Automatic docs generation from source
    • Versioned documentation
    • README rendering
    • Example code highlighting
    • API reference auto-generation
  • Community features:
    • Package comments/discussions
    • Issue tracking integration (GitHub)
    • Contribution guidelines
    • Package ownership transfer
    • Organization accounts

Validation:

  • 100+ packages published
  • 10+ active contributors
  • <500ms package search latency
  • 99.9% uptime

5.2 Standard Library (horus_library)

Planned Nodes:

  • Sensors:
    • Camera drivers (USB, CSI, network)
    • LiDAR drivers (RPLidar, Velodyne, etc.)
    • GPS/GNSS
    • Ultrasonic/IR rangefinders
    • Force/torque sensors
    • Microphones
  • Actuators:
    • Stepper motors
    • Brushless motors (ESC)
    • Linear actuators
    • Pneumatic/hydraulic
  • Control:
    • PID controller (tunable)
    • MPC (Model Predictive Control)
    • State machines
    • Trajectory generators
    • Kalman filters
  • Navigation:
    • Odometry fusion
    • SLAM integration
    • Path planning (A*, RRT, DWA)
    • Localization
    • Obstacle avoidance
  • Perception:
    • Computer vision (OpenCV)
    • Object detection
    • AprilTag detection
    • Point cloud processing
  • Communication:
    • ROS1/ROS2 bridge nodes
    • MQTT bridge
    • WebSocket server
    • HTTP API server

Validation:

  • 50+ production-ready nodes
  • Full test coverage for each node
  • Real hardware validation
  • Documentation and examples for all

6. Performance & Benchmarks

6.1 Comprehensive Benchmarking

Missing Benchmarks:

  • Latency benchmarks:
    • Message size scaling (1B to 10MB)
    • Multi-publisher scenarios
    • Multi-subscriber scenarios
    • Cross-process (Link) latency
    • Comparison vs ROS2, ZeroMQ, MQTT
  • Throughput benchmarks:
    • Messages per second per topic
    • Total system throughput
    • Bandwidth saturation tests
    • Backpressure handling
  • Resource usage:
    • CPU usage per node
    • Memory consumption
    • Shared memory overhead
    • Startup time
    • Shutdown time
  • Scalability:
    • 1 to 1000 nodes
    • 1 to 1000 topics
    • Message size impact
    • Subscriber count impact
  • Real-world scenarios:
    • Drone control loop (1kHz IMU → motors)
    • SLAM pipeline (LiDAR → map → path)
    • Vision pipeline (camera → detection → tracking)
    • Multi-robot coordination
  • Platform benchmarks:
    • x86_64 (Intel, AMD)
    • ARM (Raspberry Pi 4, 5)
    • ARM (Jetson Nano, Xavier, Orin)
    • RISC-V (future)
  • Automated regression testing:
    • CI/CD performance tests
    • Alerting on performance degradation
    • Historical performance tracking
    • Comparison against previous releases

Deliverables:

  • Benchmark suite in benchmarks/ directory
  • Automated benchmark runner
  • Results dashboard/website
  • Comparison charts vs competitors
  • Performance regression CI

Validation:

  • Benchmarks run on every commit
  • Public results dashboard
  • Third-party validation
  • Published benchmark methodology

6.2 Latency Optimization

Target: Maintain <300ns for control messages, <2μs for sensor messages

Optimization Areas:

  • Cache optimization:
    • Profile cache miss rates
    • Optimize data layout
    • Prefetch critical data
  • Lock-free improvements:
    • Validate atomic operations
    • Minimize memory barriers
    • Compare atomic implementations
  • SIMD:
    • Vectorize large message copies
    • Platform-specific optimizations
  • Platform-specific:
    • ARM NEON optimizations
    • x86 AVX/AVX2
    • Cache line sizes per platform
  • Profiling:
    • Continuous profiling in production
    • Flamegraph generation
    • Bottleneck identification

Validation:

  • Maintain current performance on all platforms
  • Document optimization techniques
  • Before/after benchmarks for each optimization

7. Documentation & Testing

7.1 Documentation

Missing/Incomplete:

  • Tutorials:
    • Beginner: First robot in 30 minutes
    • Intermediate: Multi-node system
    • Advanced: Real-time control
    • Expert: Custom language bindings
  • How-to guides:
    • Migrate from ROS2
    • Debug performance issues
    • Deploy to embedded systems
    • Profile and optimize nodes
    • Integrate with existing systems
    • Build custom simulators
  • Reference:
    • Complete API documentation (all crates)
    • Message type reference
    • Error code reference
    • Configuration reference
  • Explanations:
    • Shared memory architecture deep dive
    • Scheduler internals
    • Safety and reliability
    • Performance characteristics
    • When to use HORUS vs alternatives
  • Video tutorials:
    • Quick start screencast
    • Building a robot from scratch
    • sim2d/sim3d tutorials
    • Dashboard usage
    • Deployment to real hardware
  • Example projects:
    • Line-following robot
    • Quadcopter flight controller
    • Robot arm pick-and-place
    • Autonomous rover
    • Multi-robot swarm
    • Vision-based object tracker

Validation:

  • Documentation coverage >90%
  • User testing with newcomers
  • Keep docs in sync with code
  • Search functionality works well

7.2 Testing

Testing Strategy:

  • Unit tests:
    • 90%+ code coverage
    • All public APIs tested
    • Edge cases covered
    • Property-based testing where applicable
  • Integration tests:
    • Multi-node scenarios
    • Cross-language tests (Rust ↔ Python ↔ C)
    • Real hardware tests (CI/CD with hardware)
    • Long-running stress tests
  • Performance tests:
    • Latency regression tests
    • Throughput tests
    • Resource usage tests
    • Run on every commit
  • Acceptance tests:
    • User scenario tests
    • Example projects as tests
    • Documentation examples tested
    • CLI command tests
  • Platform tests:
    • x86_64 Linux
    • ARM Linux (Raspberry Pi)
    • ARM Linux (Jetson)
    • macOS (x86 + ARM)
    • Windows (future)
  • CI/CD:
    • GitHub Actions for all platforms
    • Automated release process
    • Dependency update automation
    • Security scanning

Validation:

  • 90%+ code coverage
  • All tests passing on all platforms
  • <5 minute CI/CD pipeline
  • Zero tolerance for flaky tests