Servodude builds intelligent systems, autonomous robots, and AI-driven engineering solutions — from embedded firmware to deep learning perception stacks.
Seven core pillars powering every intelligent machine Servodude designs, programs, and deploys.
Path planning, SLAM, PID control, and real-time obstacle avoidance for ground and aerial platforms.
ros2 · lidar · slamObject detection, segmentation, tracking, and optical flow using OpenCV, YOLO, and MediaPipe.
opencv · yolo · mediapipeFull-stack robotic middleware — nodes, topics, services, transforms, and hardware abstraction layers.
ros2 · nav2 · moveitDeploying quantized inference models on edge devices — Raspberry Pi, Jetson, STM32, and ESP32.
tflite · jetson · armCNNs, transformers, and reinforcement learning pipelines for perception, prediction, and control.
pytorch · tensorflow · cudaKalman filtering, IMU integration, multi-modal data fusion from LIDAR, cameras, and ultrasonic arrays.
kalman · imu · lidarBrowser-based robot control dashboards, WebSocket telemetry, and live sensor visualization stacks.
websocket · rosbridge · jsReal systems. Deployed code. Machines that move, see, and decide.
A ground robot navigating unknown environments using SLAM-built maps, Nav2 path planning, and real-time LIDAR obstacle avoidance. Runs entirely on-device — no cloud, no remote control.
Real-time hand skeleton tracking via MediaPipe drives a 6-DOF servo arm with inverse kinematics. Gesture vocabularies map to pick-and-place sequences — no physical interface needed.
A CNN trained on multispectral satellite imagery to classify flood-risk zones at 10m resolution. Handles Sentinel-2 band stacking, semantic segmentation, and disaster probability heatmap output.
Engineering collaborations, STEM partnerships, and project commissions — send a signal.