Revolutionizing Robotics with Integrated Solutions

Physical AI is intelligence that survives contact with the real world — dust, vibration, glare, latency, and the gap between a simulation and a Tuesday afternoon in a field. Building it takes every layer below. We build all of them in-house, and we shipped them in our own robot before offering them to you.

• Real-time object detection & classification — YOLO-family, custom-trained on your data
• Depth & 3D vision: Intel RealSense, stereo, structured light
• Camera–IMU–LiDAR sensor fusion for robust scene understanding
• Hand-eye calibration and eye-in-hand vision-guided manipulation
• Edge inference on NVIDIA Jetson, Raspberry Pi, custom platforms

FIELD PROOF

Plant-level weed vs. crop classification, fully on-device, in fields with zero connectivity.

• SLAM & localization in GPS-denied, unstructured environments
• ROS 2 Nav2: costmaps, behavior trees, planners, recovery behaviors
• IMU + wheel + visual odometry fusion — EKF/UKF, robot_localization
• Coverage path planning (boustrophedon, Voronoi)
• Multi-robot & swarm coordination: task allocation, mesh comms

FIELD PROOF

Row-following autonomy on uneven terrain — no RTK base station, no pre-mapping.

• Arm integration: kinematics, motion planning, trajectory execution
• MoveIt 2: planning scenes, collision-aware motion, pick-and-place
• Vision-guided manipulation: detect → localize → grasp, closed loop
• Custom end-effectors, hot-swappable tooling with CAN-based tool ID
• Imitation learning: teleoperation capture, dataset recording, policy training

FIELD PROOF

Vision-guided extraction arm with eye-in-hand depth camera and policies trained on real teleoperation data.

• Linear actuator & gantry system design, modeling, control
• NMPC, adaptive PD, backstepping — Simulink to ROS 2 C++ via codegen
• Vibration and swing-angle suppression for gantry mechanisms
• Motor systems: steppers, closed-loop servos, BLDC
• CAN, I²C, industrial fieldbus integration

BENCH PROOF

Gantry swing-angle control benchmarked across three controller designs, with a working Simulink-to-ROS2 pipeline.

• Gazebo: world building, sensor models, physics tuning
• ros2_control: identical stack in simulation and on hardware
• Sim-to-real workflows: domain randomization, validated transfer
• Cloud simulation infrastructure for parallel testing and CI
• URDF/Xacro modeling and kinematic validation

PIPELINE PROOF

Full digital twin of our field robot — regression-tested in sim before every hardware release.

• Custom datasets: collection, annotation pipelines, domain training
• Reinforcement learning for control and behavior policies
• Imitation learning from demonstration
• Edge optimization: quantization, pruning, CUDA on Jetson-class hardware
• Offline-first inference architectures

FIELD PROOF

Detection models trained on our own field-collected datasets, running in real time on embedded compute.

• ROS 2 architecture (Jazzy/Humble), DDS tuning, multi-machine systems
• micro-ROS on microcontrollers for real-time hardware nodes
• Board bring-up, BSPs, Yocto Linux, device drivers — i.MX8, modern SoCs
• Safety-rated firmware: ISO, SIL, DO-254 heritage
• Wireless field architectures: ESP-NOW, LoRa, cellular gateways

SHIPPED PROOF

Production board bring-up delivered for rail inspection (i.MX8/Yocto) and space camera payloads.