Robotics software
built for the real world.

Engineering and operating fleet-scale autonomy where deterministic behavior, diagnostic depth, and bounded latency directly influence mission throughput.

• Autonomy servicesDeveloped multithreaded C++ services governing mission state, navigation events, and robot-health transitions across 300+ machines supporting more than 5,000 daily missions.
• Failure forensicsBuilt Python tooling for ROS2 and MCAP analysis, automating failure reproduction and reducing recurring investigation time from roughly four hours to under 90 minutes.
• Behavior optimizationTuned perception and navigation behavior for dynamic warehouse traffic, reducing unnecessary robot stops by 18% during high-volume operations.
• Edge accelerationOptimized NVIDIA Jetson workloads with CUDA, TensorRT, and concurrent C++, reducing CPU consumption by 24% while bringing critical perception latency to approximately 30 ms.
• Fleet observabilityImplemented AWS telemetry workflows with S3 and CloudWatch to process more than 10 million robot events per day and accelerate fleet-health analysis.
• Simulation at scaleExpanded Gazebo and Isaac Sim validation beyond 15,000 generated scenarios, catching regressions earlier and reducing physical robot testing time by nearly 35%.
• Production diagnosticsInvestigated crashes, communication drops, resource contention, and stale robot state through structured logs, profiling, and deterministic replay, shortening recurring issue resolution from days to same-day fixes.

Built the navigation, estimation, manipulation, validation, and delivery foundations required for dependable autonomous material-handling systems.

• ROS2 navigationEngineered C++ and Python navigation services integrating DDS communication, sensor inputs, and recovery behaviors for more than 250 autonomous missions each day.
• Probabilistic localizationIntegrated LiDAR, stereo cameras, IMU, and wheel encoders; tuned EKF-based sensor fusion and SLAM for more stable pose estimation in industrial environments.
• ManipulationArchitected MoveIt2 and ROS2 Control workflows for collision checking, inverse kinematics, and trajectory execution across more than 18,000 material-handling cycles monthly.
• Accelerated perceptionOptimized PyTorch inference on NVIDIA Jetson with CUDA and TensorRT, achieving approximately 45 ms image-inference latency for real-time inspection.
• Regression engineeringCreated Gazebo environments for navigation, obstacle avoidance, sensor faults, and recovery; GitLab CI coverage reduced release-validation time by 42%.
• Fleet telemetryConnected battery, localization, mission, and fault signals through MQTT and ROS2 DDS across more than 120 robots, accelerating remote troubleshooting and reducing unnecessary field checks.
• Release engineeringContainerized robotics applications with Docker and supported Jenkins delivery pipelines for automated builds, integration tests, configuration validation, and rollback workflows.
• Field diagnosticsDiagnosed navigation, sensor, and communication failures on Linux-based robots using ROS2 diagnostics and system logs to isolate root causes and restore affected systems.